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Использование LLM в автоматизации рутинных задач

Использование мультимодальной модели для навигации в браузере
Использование мультимодальной модели для навигации в браузере

Всем привет!

На связи Георгий Бредис, Deep Learning Engineer из команды Intelligent Content в SberDevices. Наша команда занимается задачами автоматизации бизнес-процессов путем извлечения информации из неструктурированного контента и созданием сервисом суммаризации и поиска на основе LLM. В данный момент мы исследуем новые способы извлечения информации из интерфейсов, что открывает новые возможности для автоматизации процессов в сфере RPA.

В этой статье речь пойдет об использовании больших языковых моделей для работы с браузером, как одного из самых распространенных примеров интерфейса.

В первой части я расскажу, как такие модели строятся, чем отличаются разные подходы и какие проблемы они решают.

Во второй части проведу обзор существующих бенчмарков и подходов для данной задачи.

Наконец, в заключении, я поделюсь нашими собственными разработками. Это:

  • Мультимодальный инструктивный бенчмарк на скриншотах на русском языке;

  • Domain-based LLM, решающая подобные задачи.

Базовая идея

При правильной подготовке большие языковые модели, работающие в браузере, способны автоматически выполнять задачи в интернете, имитируя действия человека. Подобные модели могут переходить по веб-страницам, заполнять формы, кликать по ссылкам и собирать данные, и всё это без прямого участия пользователя. Основная идея заключается в том, чтобы автоматизировать рутинные задачи. Далее мы обсудим, как эту задачу можно решить, и проведём обзор возможных подходов.

Основные подходы

Веб-страницы можно описать несколькими способами:

  1. HTML (а также CSS и JavaScript) — используется для создания и структурирования контента на веб-страницах, включая текст, изображения и ссылки.

  2. DOM-структура — графовое (более точно — древовидное) представление веб-страницы. Служит для более эффективного взаимодействия со структурой страницы.

  3. Изображение — в конечном итоге пользователь, как правило, взаимодействует только с визуальным отображением веб-сайтов, что представляется в виде наборов изображений.

Каждый из описанных выше способов может представлять входные данные для модели. На выходе ожидается текст, который нужно использовать для совершения действий и планирования. Так что базово любая модель представляет собой комбинацию энкодера (кодировщика) определённой модальности (или нескольких модальностей, например HTML и изображения) и текстового декодера.

В зависимости от выбора входных данных будет меняться и структура модели, а также формат и процедура сбора данных для дообучения. Модели на веб-домене можно разбить на две группы: те, что работают на изображениях (image-based), и те, что работают с текстом в виде HTML (text-based). Ниже мы более подробно рассмотрим каждый из видов моделей, обсудим их сильные и слабые стороны, а после перейдём к конкретным подходам.

Image-Based Models (скриншоты)

Модели, работающие с изображениями, нарезают изображения на мелкие кусочки (патчи, англ. patches), которые затем подаются в визуальный энкодер или в текстовую модель (через проекцию). У данных подходов есть несколько ограничений. Среди них основные следующие.

  • Ограниченность контекста на одном изображении. Это вводит дополнительную ось взаимодействия с прокруткой страницы (scroll).

  • Так как подобным моделям нужно оперировать с признаками низких уровней (веб-элементы, текст на изображении), то необходимо использовать энкодеры высоких разрешений. Чем больше разрешение у энкодера, тем больше токенов поступят на вход модели. Это сильно ограничивает возможность общаться с моделью и задавать дополнительные вопросы. При использовании энкодеров на маленьком разрешении модель не может найти правильные элементы для взаимодействия. Вдобавок к предыдущим проблемам, энкодеры на маленьком разрешении больше и имеют более качественные фичи.

  • Способ идентификации. По идее, каждый элемент веб-страницы имеет уникальный идентификатор, но при использовании исключительно изображения мы должны предсказывать координаты элементов без возможности использовать идентификатор напрямую. Это приводит к ряду проблем, таких как способ определения элемента (центр или ограничивающую рамку) и вложенность.

Text-Based Models (HTML)

Модели, работающие на HTML-страницах, как правило, обрабатывают HTML-код страницы перед тем, как отдать её декодеру (LLM). Это нужно, чтобы ненужная информация из HTML не забивала контекст, так как очень часто код страницы содержит большое количество шума. Часть подходов основывается на фильтрации HTML-документа, другие используют сложные механизмы внимания и эвристики, чтобы обходить сложность обработки HTML. Среди основных ограничений выделим следующие.

  • Шум. как упоминалось выше, HTML-код одной страницы наполнен большим количеством ненужной информации. Так что его необходимо дополнительно обрабатывать.

  • Неподходящие стандартные способы обучения моделей. Поскольку для анализа HTML необходимо ориентироваться в иерархической структуре страницы (модель должна понимать отношения между элементами дерева и текстами внутри них), обучение таким задачам, как span corruption или fill-in-the-middle с относительно короткими спанами не позволяет добиться появления желаемых свойств.

  • Ограниченность на домене. HTML-код встречается только в браузере. Несмотря на изначально поставленную задачу, мы хотим получить обобщаемую модель, которая сможет взаимодействовать не только с веб-страницами, но и с мобильными интерфейсами, десктопными приложениями, документами. Также HTML-код плохо передает визуальные свойства изображения.

Mixed Models

Помимо упомянутых способов обработки веб-страниц, существуют комбинированные подходы, а также есть возможность добавлять токены от DOM-структуры страницы. Из-за слишком узкой направленности и сложного инференса подобных моделей мы не будем останавливаться на них в этой статье. Если вам интересно узнать больше о таких подходах, напишите об этом в комментариях.

Далее перейдём к обсуждению бенчмарков, ведь ни одна модель машинного обучения не строится без правильных метрик.

Бенчмарки

Среди бенчмарков можно выделить несколько категорий:

  • web VQA — вопросы для одной страницы (очень похожие по домену на DocVQA. Кстати, DocVQA наша команда тоже занималась, ссылка1, ссылка2);

  • single-hop взаимодействие со страницей (например, нажать на нужную кнопку);

  • multi-hop взаимодействия. Которые, в свою очередь, подразделяются на оффлайн и онлайн. Первые предполагают оценку модели на изображениях и заранее отобранной стратегии взаимодействия с сайтом. Вторые предполагают оценку в среде, то есть оценку качества достижения цели, а не следования конкретному маршруту.

Ниже мы обсудим основные на данный момент англоязычные бенчмарки и способы их перевода. Основной фокус будет сделан на десктопных сайтах, с некоторыми отсылками на мобильные приложения. Также, несмотря на полноту работы, будут упущены некоторые знакомые многим бенчмарки (такие как MiniWob++), так как они не позволяют оценить качество модели на реальной задаче.

Web VQA

В данном разделе обсудим основные способы оценки качества понимания веб-страниц, возможность извлечения информации и связь с похожими доменами. Во избежание громоздкости этого раздела упустим бенчмарки общего VQA, так или иначе имеющие пересечения с веб-доменом.

WebSRC

Основной бенчмарк по извлечению информации для моделей на веб-домене по формату очень похож на DocVQA, ChartQA и т. д. Фокус в работе сделан на нахождение информации на веб-странице и создании базовых моделей для решения этой задачи. Это главный бенчмарк для оценки возможности моделей извлекать информацию из веб-страниц.

Web Navigation

Рассмотрим несколько базовых (иногда совсем новых) работ по оценке различных аспектов веб-навигации у моделей.

ScreenSpot

Довольно новый датасет, представленный в работе SeeClick. Представляет из себя single-hop вопросы на составление пары координата-действие по заданной инструкции. Подобный бенчмарк позволяет оценить базовое качество модели, не переходя к более сложным офлайновым бенчмаркам.

Untitled
ScreenSpot

Mind2Web

В данный момент ключевой бенчмарк для любых систем, стремящихся автоматизировать взаимодействие с браузером. Он представляет из себя офлайн-среду для оценки ряда действий возвращаемых моделью. Включает качество оценки определения элемента взаимодействия, определения типа взаимодействия и их сочетание. Покрывает довольно большое кол-во доменов и хорошо задокументирован.

Этот multi-hop бенчмарк является примером офлайновой оценки модели, что не позволяет действительно оценить качество последней и является только прокси-метрикой, так как на реальных сайтах достичь цели можно множественными траекториями. Для решения этой проблемы используются так называемые онлайн-бенчмарки, но их невозможно использовать без среды, что также ограничивает их применение.

В последнее время появляется все больше бенчмарков наподобие Mind2Web, среди которых можно выделить довольно примечательный OmniACT, оценивающий качество понимания моделью среды при помощи генерации кода (что в будущем может стать основным способом взаимодействия с интерфейсами!).

Open-Source and Papers

Среди всех работ по взаимодействию с веб-страницами можно выделить два основных направления, первый — на основе GPT4V (возможно, в скором времени к ним добавятся и новые модели с возможностью вызова по API, но пока не позволяет качество), второй — создание отдельных доменных моделей.

API-Based модели

Эта категория подходов использует API GPT4V (пока только эта модель), подаёт изображения или отфильтрованный HTML-текст на вход модели, а получает действие и какой-то способ определить элемент. Основной проблемой является необходимость определения элементов взаимодействия, поэтому используются различные способы граундинга (от англ. grounding — приземление) предсказаний модели на интерфейс. Далее пройдёмся более подробно по каждому из них:

Image Annotation (Set-of-Marks)

В данном случае на вход модели поступают скриншоты с подсвеченными элементами для возможного взаимодействия. Это можно сделать через инструменты управления браузером (playwright) или при помощи расширений (например, через vimium, как это делает VimGPT, что, по сути, очень похоже на предыдущий подход). В таком случае изображение выглядит так (в примере использован vimium), а модель должна вернуть выбор элемента (в виде набора символов) и тип действия.

Из довольно известных данный подход использован в работах WebVoyager, VimGPT и SeeAct (оставшиеся два метода предложены в этой же работе и ее предшественнике).

Untitled
Звук Set of marks

Element Attributes

В данном подходе модели предлагается сгенерировать детальное описание элемента для взаимодействия, после чего происходит поиск по данной DOM-структуре на наличие подобных элементов. Этот метод также рассматривался как один из основных в работе SeeAct.

Textual Choices

Подход, берущий идею из Mind2Act. Основная идея — возьмём возможные кликабельные элементы из HTML-страницы, выберем лучшие (например при помощи энкодера по типу DeBERTa) и подадим на вход LLM с просьбой выбрать лучшие. В результате из подходов на основе API модель показывает лучшее качество. Ограничением является многостадийность и необходимость создания отдельной модели ранжирования.

Несмотря на кажущуюся простоту использования подходов на основе API, у них есть существенные недостатки: необходимость эвристик для правильной подачи данных в LLM. Так что существует желание сделать отдельную веб-модель, которую можно будет эффективно и несложно использовать.

Standalone-модели

Среди standalone-моделей также существует некоторая дихотомия на модели, работающие с изображениями, и на модели, работающие с текстом.

CogAgent

На данный момент одна из самых интересных работ по созданию модели, работающей на интерфейсе. Как упоминалось выше, при стандартном кодировании изображения и подаче его в текстовый декодер посредством эмбеддингов патчей (фактически токенов изображения) мы сталкиваемся с двумя фундаментальными ограничениями:

  • невозможно эффективно использовать высокое разрешение (забьётся контекст);

  • невозможно использовать энкодеры только маленького разрешения: на вход декодеру будет поступать малое количество полезной информации для низкоуровневых действий.

CogAgent решает обе проблемы посредством создания энкодера высокого разрешения и добавления его в модель посредством кросс-внимания (англ. cross-attention) со слоями декодера. Это позволяет эффективно использовать контекст и одновременно с этим обрабатывать изображения высокого разрешения. Архитектура модели представлена ниже.

Untitled
CogAgent

Основным ограничением такого подхода является долгое предобучение модели на большом количестве данных, чтобы слои кросс-внимания правильно встроились в декодер. CogAgent показывает лучшее качество на Mind2Web из числа image-based моделей, а также хорошее качество на стандартных text-rich VQA-бенчмарках.

SeeClick

Можно сказать, что данная работа является CogAgent на минималках. В ней авторы используют стандартный подход в стиле LLaVA к подаче изображения в декодер (а если быть точнее, то используют уже готовую QWEN-VL), кодируют изображение среднего разрешения (448×448) и подают напрямую в декодер. Несмотря на простоту модельного подхода, авторы собирают качественный датасет, направленный на понимание скриншота и координат, что в конечном счета и даёт основной прирост. В него входят такие задачи, как text2point, point2text (где модель просят восстановить координаты по тексту и текст по координатам). Модель показывает не очень высокое качество на бенчмарке Mind2Web, но довольно хорошо справляется с задачей ScreenSpot, где нужно найти элемент и действие, а не понимать, на какой стадии выполнения задачи находится модель.

ScreenAI

В данной работе используется довольно простая идея от схожих моделей для обработки скриншотов (pix2struct) и документов (UDOP). Нарезаем изображение с учётом отношения сторон (pix2struct patching), представляем патчи в виде эмбеддингов, конкатенируем с текстом и отправляем в мультимодальную T5. Модель учится на нескольких задачах восстановления структуры изображения на большом количестве разнообразных веб-данных и изображениях графиков. В результате модель показывает хорошее качество на классических DocVQA-бенчмарках и WebSRC.

HTML-T5-XXL

Текстовая T5-модель, работающая на HTML, на данный момент имеет самые высокие метрики на бенчмарке Mind2Web. Из предположения о двух проблемах при работе с HTML: семантической сложностью соотношения тегов с текстом и необходимостью специфически понимать контекст (так как структура вложенная) — авторы применяют два основных подходы для их решения. Для решения первой проблемы авторы увеличивают длину спанов для денойзинга. Это позволяет модели лучше понимать структуру HTML. Для решения второй — комбинируют глобальное и локальное внимание для обработки вложенной структуры в HTML.

Cуществует ещё несколько работ, созданных для работы с веб-страницами, но они либо неинтересные (например, DualVCR) в рамках данной статьи, либо устарели и имеют преемников (Mind2Act → SeeAct).

Связанные и достойные упоминания

Работы выше создавались для взаимодействия с интерфейсным доменом, поэтому их важно было рассмотреть отдельно. Но помимо них есть ряд идей из других работ, достойных обсуждения.

FUYU

Работа от Adept.ai (основатели — авторы статьи «Attention Is All You Need»). Изображения нарезаются на патчи, обрабатываются линейным слоем и отдаются на вход авторегрессионному декодеру. Основной плюс — можно использовать изображение любого разрешения.

LLaVA-Next (изначально LLaVA-1.6)

Продолжение линейки модели LLaVA, в этот раз нарезаем изображение на кропы (например, 800×800 → 672×672 → 4×(336×336)), и каждый из кропов обрабатываем моделью типа ViT. Модель не разрабатывалась непосредственно для веб-домена, но является важной вехой в обработки text-rich изображений.

LaVague

Открытая текстовая модель для взаимодействия с браузером. Авторы используют Gemma-7b для непосредственных взаимодействий, а решают проблему зашумленности HTML-документа посредством RAG. В итоге решение работает, и довольно неплохо.

skyvern

Фреймворк из последнего батча YC, в котором большое внимание уделяется возможности конфигурировать пайплайн. Основное достоинство работы — это грамотная инженерная смесь разных практик. Взаимодействие происходит благодаря комбинации из подходов image annotation и textual choices с многоэтапной обработкой. В конечном итоге фреймворк способен совершать сложные действия.

Closed-Source

Помимо большого количества академических и открытых работ, выделим несколько компаний, которые занимаются подобными задачами автоматизации. Несмотря на растущее число подобных стартапов, на текущий момент, хочется отметить несколько наиболее интересных. Также не включены стартапы, на продукты которых (на данный момент) нельзя посмотреть, например в виде демо-видео или небольшого приложения.

Adept.AI

Компания от авторов «Attention Is All You Need», подарила нам работу Fuyu-8B, а также несколько других открытых моделей для работы с интерфейсами, пока не релизили продукт, но обещает быть очень интересным.

HyperWrite.AI

Ребята делают «Self-Operating-Computer» и даже готовят свою модель. Помимо интересного демо, есть возможность записаться в waitlist. Есть обертки над разными LVLM-моделями и даже возможность поднять всё локально (тут конечно LLaVA-модели).

Induced.AI

Интересная работа с красивым демо, но с малым количеством технических деталей. По результатам сильно напоминает VimGPT, хотя авторы на своем дискорд сервере говорят, что решение построено на отдельных моделях и не привязано напрямую к GPT4V. Интересно посмотреть что получится у них дальше, компания уже подняла раунд у солидных инвесторов.

Проделанная работа

Как было сказано ранее, мы разработали модель на базе текстового декодера GigaChat и собрали бенчмарк. Далее расскажем подробнее о самой модели и бенчмарке, а также покажем демо взаимодействия текущей модели с реальным веб-интерфейсом.

Бенчмарк

Для разработки веб-моделей (как, в общем-то, и для разработки любого рода моделей машинного обучения) необходим валидационный сет. Задачи, решаемые в браузере, требуют оценивать точность взаимодействия и качество планирования, для этого мы разработали два способа оценки.

Первый наподобие ScreenSpot, в котором наибольшее внимание уделяется нахождению элемента взаимодействия и способа взаимодействия с ним. Данный сет был собран при помощи рендеринга скриншотов и выделения кликабельных элементов. Также данный бенчмарк можно улучшить посредством добавления человеческих описаний элементов (для перехода модели в домен естественного языка).

Для оценки возможности модели работать в веб-среде мы разработали фреймворк WebFollower для сбора offline multi-hop взаимодействия с сайтами. Основная идея заимствована из Mind2Web. Пример разметки сайта можно найти ниже:

В рамках данного демо было решено отключить возможность оставлять комментарии. Но в общем случае они предполагаются на каждом действии — такая возможность необходима для простого перехода из multi-hop в single-hop. В итоге мы собрали около 500 демонстраций на различных доменах и сайтах и в скором времени собираемся опубликовать их.

Мы планируем выложить часть бенчмарков в открытый доступ (некоторые из них можно будет найти в MERA) и опубликовать код для создания разметки своего сайта в формате Mind2Web.

Подход и сбор данных

Представляем разработанную модель. В процессе разработки мы опробовали несколько разных подходов. В данной статье решили представить метод с координатами как наиболее интересный для визуализации.

Для непосредственного обучения модели мы адаптировали подход из LLaVA и обучили модель на двух задачах: планирование взаимодействия с интерфейсом и нахождение подходящего элемента. Для улучшения понимания моделью высокого разрешения использовали подход с нарезкой изображения, как в LLaVA-Next.

Архитектура:

Untitled
Untitled

Во время обучения модели мы активно взаимодействовали с коллегами из AIRI FusionBrain, благодаря чему нам удалось добиться лучшего качества модели, за что им большое спасибо. Кстати ребята разрабатывают свой фреймворк для мультимодального обучения, а недавно у них состоялся релиз OmniFusion 1.1.

Для задачи ориентирования на веб-странице мы подготовили обучающий набор данных на понимание веб-страницы. Во многом опирались на работы коллег и опыт команды в разработке мультимодальных text-rich моделей. В результате были включены четыре задачи:

  1. описание веб-элемента;

  2. нахождение координат веб-элемента по описанию;

  3. нахождение веб-элемента по координатам;

  4. перевод изображения в HTML-код.

В будущем мы планируем расширить сет данными из классических OCR-задач, но на веб-домене, а также добавить задачи на суммаризацию информации. Подобную работу проделывали коллеги в статье Enhancing Vision-Language Pre-training with Rich Supervisions.

Для сбора скриншотов мы использовали playwright, где с каждого сайта собирали изображение, HTML и VDOM (DOM c координатами). После, изображения были нарезаны и отфильтрованы для грамотного соотношения с веб-элементами. Также данные такого формата можно использовать и для создания Set-of-Marks на изображении, что было сделано в части экспериментов.

Примеры обучающих данных:

Untitled
Untitled
{
    "tag_name": "button",
    "text": "Все о товаре",
    "bbox": {
        "x": 608,
        "y": 490,
        "width": 148.16668701171875,
        "height": 40
    },
    "center": {
        "x": 682.0833435058594
        "y": 510
    }
    "segment": 0
}

В итоге нам удалось добиться понимания моделью координат. Это позволило перейти к следующим этапам и опробовать несколько гипотез.

  • Навыки извлечения информации (как в стандартных экстрактивных VQA-задачах).

  • Навыки чтения веб-страницы.

  • Понимание координат элементов и умение соотнести информацию об элементе и изображении.

Далее пришло время инструктивных данных для планирования. Для этого мы использовали внутренние данные, собранные в формате Mind2Web, а также перевели Mind2Web в multi-hop парадигме. После обучения на итоговых инструкциях у модели появились базовые возможности к планированию и соотношению действий с необходимым элементом.

Демо работы итоговой модели:

Что дальше?

Качество модели складывается из многих составляющих. Из них можно выделить те, на которые мы сделаем упор в ближайшее время:

  • Качество извлечения информации из изображений. Это необходимо для лучшего нахождения элементов и out-of-domain возможностей модели.

  • Навыки модели к планированию. Для этого нужно собрать больше качественных инструктивных данных, которые описывают декомпозицию комплексной задачи на простые действия.

  • Возможности рефлексии, чтобы на каждом шаге взаимодействия модель смогла перестроить план, согласно текущему состоянию среды.

Помимо этого мы планируем опубликовать бенчмарк, сравнение разных моделей на нем, а также больше информации о нашей модели и процессе обучения. Для большего количества технических деталей следите за будущими новостями.

На связи с вами

Такжы мы сейчас активно нанимаем! Откликайтесь на вакансию, если хотите присоединиться к нашей команде.

Статью подготовил: Георгий Бредис. Помогали в редакции: Даниил Водолазский, Дмитрий Головин, Максим Брегеда, Игорь Галицкий, Сергей Марков. Обложку подготовила: Александра Гаскевич. За помощь в технической части спасибо Елизавете Гончаровой.

Также напомню о том, что в Telegram-канале Salute AI мы с коллегами начали делиться наработками в области машинного обучения и другими рабочими моментами. А в соответствующем чатике Salute AI Community можно пообщаться с нами лично.

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  • 07.09.23 16:24 CherryTeam

    Cherry Team atlyginimų skaičiavimo programa yra labai naudingas įrankis įmonėms, kai reikia efektyviai valdyti ir skaičiuoti darbuotojų atlyginimus. Ši programinė įranga, turinti išsamias funkcijas ir patogią naudotojo sąsają, suteikia daug privalumų, kurie padeda supaprastinti darbo užmokesčio skaičiavimo procesus ir pagerinti finansų valdymą. Štai keletas pagrindinių priežasčių, kodėl Cherry Team atlyginimų skaičiavimo programa yra naudinga įmonėms: Automatizuoti ir tikslūs skaičiavimai: Atlyginimų skaičiavimai rankiniu būdu gali būti klaidingi ir reikalauti daug laiko. Programinė įranga Cherry Team automatizuoja visą atlyginimų skaičiavimo procesą, todėl nebereikia atlikti skaičiavimų rankiniu būdu ir sumažėja klaidų rizika. Tiksliai apskaičiuodama atlyginimus, įskaitant tokius veiksnius, kaip pagrindinis atlyginimas, viršvalandžiai, premijos, išskaitos ir mokesčiai, programa užtikrina tikslius ir be klaidų darbo užmokesčio skaičiavimo rezultatus. Sutaupoma laiko ir išlaidų: Darbo užmokesčio valdymas gali būti daug darbo jėgos reikalaujanti užduotis, reikalaujanti daug laiko ir išteklių. Programa Cherry Team supaprastina ir pagreitina darbo užmokesčio skaičiavimo procesą, nes automatizuoja skaičiavimus, generuoja darbo užmokesčio žiniaraščius ir tvarko išskaičiuojamus mokesčius. Šis automatizavimas padeda įmonėms sutaupyti daug laiko ir pastangų, todėl žmogiškųjų išteklių ir finansų komandos gali sutelkti dėmesį į strategiškai svarbesnę veiklą. Be to, racionalizuodamos darbo užmokesčio operacijas, įmonės gali sumažinti administracines išlaidas, susijusias su rankiniu darbo užmokesčio tvarkymu. Mokesčių ir darbo teisės aktų laikymasis: Įmonėms labai svarbu laikytis mokesčių ir darbo teisės aktų, kad išvengtų baudų ir teisinių problemų. Programinė įranga Cherry Team seka besikeičiančius mokesčių įstatymus ir darbo reglamentus, užtikrindama tikslius skaičiavimus ir teisinių reikalavimų laikymąsi. Programa gali dirbti su sudėtingais mokesčių scenarijais, pavyzdžiui, keliomis mokesčių grupėmis ir įvairių rūšių atskaitymais, todėl užtikrina atitiktį reikalavimams ir kartu sumažina klaidų riziką. Ataskaitų rengimas ir analizė: Programa Cherry Team siūlo patikimas ataskaitų teikimo ir analizės galimybes, suteikiančias įmonėms vertingų įžvalgų apie darbo užmokesčio duomenis. Ji gali generuoti ataskaitas apie įvairius aspektus, pavyzdžiui, darbo užmokesčio paskirstymą, išskaičiuojamus mokesčius ir darbo sąnaudas. Šios ataskaitos leidžia įmonėms analizuoti darbo užmokesčio tendencijas, nustatyti tobulintinas sritis ir priimti pagrįstus finansinius sprendimus. Pasinaudodamos duomenimis pagrįstomis įžvalgomis, įmonės gali optimizuoti savo darbo užmokesčio strategijas ir veiksmingai kontroliuoti išlaidas. Integracija su kitomis sistemomis: Cherry Team programinė įranga dažnai sklandžiai integruojama su kitomis personalo ir apskaitos sistemomis. Tokia integracija leidžia automatiškai perkelti atitinkamus duomenis, pavyzdžiui, informaciją apie darbuotojus ir finansinius įrašus, todėl nebereikia dubliuoti duomenų. Supaprastintas duomenų srautas tarp sistemų padidina bendrą efektyvumą ir sumažina duomenų klaidų ar neatitikimų riziką. Cherry Team atlyginimų apskaičiavimo programa įmonėms teikia didelę naudą - automatiniai ir tikslūs skaičiavimai, laiko ir sąnaudų taupymas, atitiktis mokesčių ir darbo teisės aktų reikalavimams, ataskaitų teikimo ir analizės galimybės bei integracija su kitomis sistemomis. Naudodamos šią programinę įrangą įmonės gali supaprastinti darbo užmokesčio skaičiavimo procesus, užtikrinti tikslumą ir atitiktį reikalavimams, padidinti darbuotojų pasitenkinimą ir gauti vertingų įžvalgų apie savo finansinius duomenis. Programa Cherry Team pasirodo esanti nepakeičiamas įrankis įmonėms, siekiančioms efektyviai ir veiksmingai valdyti darbo užmokestį. https://cherryteam.lt/lt/

  • 08.10.23 01:30 davec8080

    The "Shibarium for this confirmed rug pull is a BEP-20 project not related at all to Shibarium, SHIB, BONE or LEASH. The Plot Thickens. Someone posted the actual transactions!!!! https://bscscan.com/tx/0xa846ea0367c89c3f0bbfcc221cceea4c90d8f56ead2eb479d4cee41c75e02c97 It seems the article is true!!!! And it's also FUD. Let me explain. Check this link: https://bscscan.com/token/0x5a752c9fe3520522ea88f37a41c3ddd97c022c2f So there really is a "Shibarium" token. And somebody did a rug pull with it. CONFIRMED. But the "Shibarium" token for this confirmed rug pull is a BEP-20 project not related at all to Shibarium, SHIB, BONE or LEASH.

  • 24.06.24 04:31 tashandiarisha

    Web-site. https://trustgeekshackexpert.com/ Tele-Gram, trustgeekshackexpert During the pandemic, I ventured into the world of cryptocurrency trading. My father loaned me $10,000, which I used to purchase my first bitcoins. With diligent research and some luck, I managed to grow my investment to over $350,000 in just a couple of years. I was thrilled with my success, but my excitement was short-lived when I decided to switch brokers and inadvertently fell victim to a phishing attack. While creating a new account, I received what seemed like a legitimate email requesting verification. Without second-guessing, I provided my information, only to realize later that I had lost access to my email and cryptocurrency wallets. Panic set in as I watched my hard-earned assets disappear before my eyes. Desperate to recover my funds, I scoured the internet for solutions. That's when I stumbled upon the Trust Geeks Hack Expert on the Internet. The service claimed to specialize in recovering lost crypto assets, and I decided to take a chance. Upon contacting them, the team swung into action immediately. They guided me through the entire recovery process with professionalism and efficiency. The advantages of using the Trust Geeks Hack Expert Tool became apparent from the start. Their team was knowledgeable and empathetic, understanding the urgency and stress of my situation. They employed advanced security measures to ensure my information was handled safely and securely. One of the key benefits of the Trust Geeks Hack Expert Tool was its user-friendly interface, which made a complex process much more manageable for someone like me, who isn't particularly tech-savvy. They also offered 24/7 support, so I never felt alone during recovery. Their transparent communication and regular updates kept me informed and reassured throughout. The Trust Geeks Hack Expert Tool is the best solution for anyone facing similar issues. Their swift response, expertise, and customer-centric approach set them apart from other recovery services. Thanks to their efforts, I regained access to my accounts and my substantial crypto assets. The experience taught me a valuable lesson about online security and showed me the incredible potential of the Trust Geeks Hack Expert Tool. Email:: trustgeekshackexpert{@}fastservice{.}com WhatsApp  + 1.7.1.9.4.9.2.2.6.9.3

  • 26.06.24 18:46 Jacobethannn098

    LEGAL RECOUP FOR CRYPTO THEFT BY ADRIAN LAMO HACKER

  • 26.06.24 18:46 Jacobethannn098

    Reach Out To Adrian Lamo Hacker via email: [email protected] / WhatsApp: ‪+1 (909) 739‑0269‬ Adrian Lamo Hacker is a formidable force in the realm of cybersecurity, offering a comprehensive suite of services designed to protect individuals and organizations from the pervasive threat of digital scams and fraud. With an impressive track record of recovering over $950 million, including substantial sums from high-profile scams such as a $600 million fake investment platform and a $1.5 million romance scam, Adrian Lamo Hacker has established itself as a leader in the field. One of the key strengths of Adrian Lamo Hacker lies in its unparalleled expertise in scam detection. The company leverages cutting-edge methodologies to defend against a wide range of digital threats, including phishing emails, fraudulent websites, and deceitful schemes. This proactive approach to identifying and neutralizing potential scams is crucial in an increasingly complex and interconnected digital landscape. Adrian Lamo Hacker's tailored risk assessments serve as a powerful tool for fortifying cybersecurity. By identifying vulnerabilities and potential points of exploitation, the company empowers its clients to take proactive measures to strengthen their digital defenses. This personalized approach to risk assessment ensures that each client receives targeted and effective protection against cyber threats. In the event of a security incident, Adrian Lamo Hacker's rapid incident response capabilities come into play. The company's vigilant monitoring and swift mitigation strategies ensure that any potential breaches or scams are addressed in real-time, minimizing the impact on its clients' digital assets and reputation. This proactive stance towards incident response is essential in an era where cyber threats can materialize with alarming speed and sophistication. In addition to its robust defense and incident response capabilities, Adrian Lamo Hacker is committed to empowering its clients to recognize and thwart common scam tactics. By fostering enlightenment in the digital realm, the company goes beyond simply safeguarding its clients; it equips them with the knowledge and awareness needed to navigate the digital landscape with confidence and resilience. Adrian Lamo Hacker services extend to genuine hacking, offering an additional layer of protection for its clients. This may include ethical hacking or penetration testing, which can help identify and address security vulnerabilities before malicious actors have the chance to exploit them. By offering genuine hacking services, Adrian Lamo Hacker demonstrates its commitment to providing holistic cybersecurity solutions that address both defensive and offensive aspects of digital protection. Adrian Lamo Hacker stands out as a premier provider of cybersecurity services, offering unparalleled expertise in scam detection, rapid incident response, tailored risk assessments, and genuine hacking capabilities. With a proven track record of recovering significant sums from various scams, the company has earned a reputation for excellence in combating digital fraud. Through its proactive and empowering approach, Adrian Lamo Hacker is a true ally for individuals and organizations seeking to navigate the digital realm with confidence.

  • 04.07.24 04:49 ZionNaomi

    For over twenty years, I've dedicated myself to the dynamic world of marketing, constantly seeking innovative strategies to elevate brand visibility in an ever-evolving landscape. So when the meteoric rise of Bitcoin captured my attention as a potential avenue for investment diversification, I seized the opportunity, allocating $20,000 to the digital currency. Witnessing my investment burgeon to an impressive $70,000 over time instilled in me a sense of financial promise and stability.However, amidst the euphoria of financial growth, a sudden and unforeseen oversight brought me crashing back to reality during a critical business trip—I had misplaced my hardware wallet. The realization that I had lost access to the cornerstone of my financial security struck me with profound dismay. Desperate for a solution, I turned to the expertise of Daniel Meuli Web Recovery.Their response was swift . With meticulous precision, they embarked on the intricate process of retracing the elusive path of my lost funds. Through their unwavering dedication, they managed to recover a substantial portion of my investment, offering a glimmer of hope amidst the shadows of uncertainty. The support provided by Daniel Meuli Web Recovery extended beyond mere financial restitution. Recognizing the imperative of fortifying against future vulnerabilities, they generously shared invaluable insights on securing digital assets. Their guidance encompassed crucial aspects such as implementing hardware wallet backups and fortifying security protocols, equipping me with recovered funds and newfound knowledge to navigate the digital landscape securely.In retrospect, this experience served as a poignant reminder of the critical importance of diligence and preparedness in safeguarding one's assets. Thanks to the expertise and unwavering support extended by Daniel Meuli Web Recovery, I emerged from the ordeal with renewed resilience and vigilance. Empowered by their guidance and fortified by enhanced security measures, I now approach the future with unwavering confidence.The heights of financial promise to the depths of loss and back again has been a humbling one, underscoring the volatility and unpredictability inherent in the digital realm. Yet, through adversity, I have emerged stronger, armed with a newfound appreciation for the importance of diligence, preparedness, and the invaluable support of experts like Daniel Meuli Web Recovery.As I persist in traversing the digital landscape, I do so with a judicious blend of vigilance and fortitude, cognizant that with adequate safeguards and the backing of reliable confidants, I possess the fortitude to withstand any adversity that may arise. For this, I remain eternally appreciative. Email Danielmeuliweberecovery @ email . c om WhatsApp + 393 512 013 528

  • 13.07.24 21:13 michaelharrell825

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  • 17.07.24 02:26 thompsonrickey

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  • 22.11.24 04:41 [email protected]

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  • 24.11.24 02:21 [email protected]

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  • 26.11.24 21:59 [email protected]

    In a world brimming with enticing investment opportunities, it is crucial to tread carefully. The rise of digital currencies has attracted many eager investors, but along with this excitement lurk deceitful characters ready to exploit the unsuspecting. I learned this lesson the hard way, and I want to share my story in the hopes that it can save someone from making the same mistakes I did. It all began innocently enough when I came across an engaging individual on Facebook. Lured in by promises of high returns in the cryptocurrency market, I felt the electric thrill of potential wealth coursing through me. Initial investments returned some profits, and that exhilarating taste of success fueled my ambition. Encouraged by a meager withdrawal, I decided to commit even more funds. This was the moment I let my guard down, blinded by greed. As time went on, the red flags started to multiply. The moment I tried to withdraw my earnings, a cascade of unreasonable fees appeared like a thick mist, obscuring the truth. “Just a little more,” they said, “Just until the next phase.” I watched my hard-earned money slip through my fingers as I scraped together every last cent to pay those relentless fees. My trust had become my downfall. In the end, I lost not just a significant amount of cash, but my peace of mind about $1.1 million vanished into the abyss of false promises and hollow guarantees. But despair birthed hope. After a cascade of letdowns, I enlisted the help of KAY-NINE CYBER SERVICES, a team that specializes in reclaiming lost funds from scams. Amazingly, they worked tirelessly to piece together what had been ripped away, providing me with honest guidance when I felt utterly defeated. Their expertise in navigating the treacherous waters of crypto recovery was a lifeline I desperately needed. To anyone reading this, please let my story serve as a warning. High returns often come wrapped in the guise of deception. Protect your investments, scrutinize every opportunity, and trust your instincts. Remember, the allure of quick riches can lead you straight to heartbreak, but with cautious determination and support, it is possible to begin healing from such devastating loss. Stay informed, stay vigilant, and may you choose your investment paths wisely. Email: kaynine @ cyberservices . com

  • 26.11.24 23:12 rickrobinson8

    FAST SOLUTION FOR CYPTOCURRENCY RECOVERY SPARTAN TECH GROUP RETRIEVAL

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  • 27.11.24 00:39 [email protected]

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  • 27.11.24 09:10 Michal Novotny

    The biggest issue with cryptocurrency is that it is unregulated, wh ich is why different people can come up with different fake stories all the time, and it is unfortunate that platforms like Facebook and others only care about the money they make from them through ads. I saw an ad on Facebook for Cointiger and fell into the scam, losing over $30,000. I reported it to Facebook, but they did nothing until I discovered deftrecoup . c o m from a crypto community; they retrieved approximately 95% of the total amount I lost.

  • 01.12.24 17:21 KollanderMurdasanu

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  • 02.12.24 23:02 ytre89

    Online crypto investment can seem like a promising opportunity, but it's crucial to recognize that there are no guarantees. My experience serves as a stark reminder of this reality. I was drawn in by the allure of high returns and the persuasive marketing tactics employed by various brokers. Their polished presentations and testimonials made it seem easy to profit from cryptocurrency trading. Everything appeared to be legitimate. I received enticing messages about the potential for substantial gains, and the brokers seemed knowledgeable and professional. Driven by excitement and the fear of missing out, I invested a significant amount of my savings. The promise of quick profits overshadowed the red flags I should have noticed. I trusted these brokers without conducting proper research, which was a major mistake. As time went on, I realized that the promised returns were nothing but illusions. My attempts to withdraw funds were met with endless excuses and delays. It became painfully clear that I had fallen victim. The reality hit hard: my hard-earned money was gone, I lost my peace of mind and sanity. In my desperation, I sought help from a company called DEFTRECOUP. That was the turning point for me as I had a good conversation and eventually filed a complaint via DEFTRECOUP COM. They were quite delicate and ensured I got out of the most difficult situation of my life in one piece.

  • 04.12.24 22:24 andreygagloev

    When I first heard about Bitcoin back in 2018, I was skeptical. The idea of a decentralized, digital currency seemed too good to be true. But I was intrigued as I learned more about the technology behind it and its potential. I started small, investing just a few hundred dollars, dipping my toes into the cryptocurrency waters. At first, it was exhilarating to watch the value of my investment grow exponentially. I felt like I was part of the future, an early adopter of this revolutionary new asset. But that euphoria was short-lived. One day, I logged into my digital wallet only to find it empty - my Bitcoin had vanished without a trace. It turned out that the online exchange I had trusted had been hacked, and my funds were stolen. I was devastated, both financially and emotionally. All the potential I had seen in Bitcoin was tainted by the harsh reality that with decentralization came a lack of regulation and oversight. My hard-earned money was gone, lost to the ether of the digital world. This experience taught me a painful lesson about the price of trust in the uncharted territory of cryptocurrency. While the technology holds incredible promise, the risks can be catastrophic if you don't approach it with extreme caution. My Bitcoin investment gamble had failed, and I was left to pick up the pieces, wiser but poorer for having placed my faith in the wrong hands. My sincere appreciation goes to MUYERN TRUST HACKER. You are my hero in recovering my lost funds. Send a direct m a i l ( muyerntrusted ( @ ) mail-me ( . )c o m ) or message on whats app : + 1 ( 4-4-0 ) ( 3 -3 -5 ) ( 0-2-0-5 )

  • 12.12.24 00:35 amandagregory

    HOW TO HIRE A HACKER TO RECOVER STOLEN BITCOIN WITH FASTFUND RECOVERY

  • 12.12.24 00:35 amandagregory

    HOW TO HIRE A HACKER TO RECOVER STOLEN BITCOIN WITH FASTFUND RECOVERY... A few months ago, I made a huge mistake. I invested in what seemed like a legitimate crypto opportunity, only to find out I’d been scammed. I lost a significant amount of money, and the scam platform vanished overnight. I felt completely lost.I had heard of Fastfund Recovery and decided to reach out, even though I was skeptical. From the first conversation, they made me feel heard and understood. They explained the recovery process clearly and kept me updated every step of the way.Within weeks, Fastfund Recovery successfully to recovered my lost funds—something I honestly didn’t think was possible. Their team was professional, transparent, and genuinely caring. I can’t thank them enough for turning a nightmare into a hopeful outcome. If you’re in a similar situation, don’t hesitate to contact them. They truly deliver on their promises. Gmail::: fastfundrecovery8(@)gmail com .....Whatsapp ::: 1::807::::500::::7554

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  • 27.12.24 00:21 swiftdream

    I lost about $475,000.00 USD to a fake cryptocurrency trading platform a few weeks back after I got lured into the trading platform with the intent of earning a 15% profit daily trading on the platform. It was a hell of a time for me as I could hardly pay my bills and got me ruined financially. I had to confide in a close friend of mine who then introduced me to this crypto recovery team with the best recovery SWIFTDREAM i contacted them and they were able to completely recover my stolen digital assets with ease. Their service was superb, and my problems were solved in swift action, It only took them 48 hours to investigate and track down those scammers and my funds were returned to me. I strongly recommend this team to anyone going through a similar situation with their investment or fund theft to look up this team for the best appropriate solution to avoid losing huge funds to these scammers. Send complaint to Email: info [email protected]

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  • 04.01.25 04:56 florencestella

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  • 18.01.25 12:41 michaeldavenport218

    I was recently scammed out of $53,000 by a fraudulent Bitcoin investment scheme, which added significant stress to my already difficult health issues, as I was also facing cancer surgery expenses. Desperate to recover my funds, I spent hours researching and consulting other victims, which led me to discover the excellent reputation of Capital Crypto Recover, I came across a Google post It was only after spending many hours researching and asking other victims for advice that I discovered Capital Crypto Recovery’s stellar reputation. I decided to contact them because of their successful recovery record and encouraging client testimonials. I had no idea that this would be the pivotal moment in my fight against cryptocurrency theft. Thanks to their expert team, I was able to recover my lost cryptocurrency back. The process was intricate, but Capital Crypto Recovery's commitment to utilizing the latest technology ensured a successful outcome. I highly recommend their services to anyone who has fallen victim to cryptocurrency fraud. For assistance, contact [email protected] Capital Crypto Recover on Telegram OR Call Number +1 (336)390-6684 via email: [email protected]

  • 18.01.25 12:41 michaeldavenport218

    I was recently scammed out of $53,000 by a fraudulent Bitcoin investment scheme, which added significant stress to my already difficult health issues, as I was also facing cancer surgery expenses. Desperate to recover my funds, I spent hours researching and consulting other victims, which led me to discover the excellent reputation of Capital Crypto Recover, I came across a Google post It was only after spending many hours researching and asking other victims for advice that I discovered Capital Crypto Recovery’s stellar reputation. I decided to contact them because of their successful recovery record and encouraging client testimonials. I had no idea that this would be the pivotal moment in my fight against cryptocurrency theft. Thanks to their expert team, I was able to recover my lost cryptocurrency back. The process was intricate, but Capital Crypto Recovery's commitment to utilizing the latest technology ensured a successful outcome. I highly recommend their services to anyone who has fallen victim to cryptocurrency fraud. For assistance, contact [email protected] Capital Crypto Recover on Telegram OR Call Number +1 (336)390-6684 via email: [email protected]

  • 20.01.25 15:39 patricialovick86

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  • 22.01.25 21:43 DoraJaimes23

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  • 23.01.25 02:36 [email protected]

    After falling victim to a fraudulent Bitcoin mining scam, I found myself in a desperate situation. I had invested $50,000 into a cloud mining website called Miningpool, which turned out to be a complete scam. For months, I tried reaching out to the company, but I was unable to access my funds, and I quickly realized I had been taken for a ride. In my search for help, I came across TrustGeeks Hack Expert, a service that claimed to help people recover lost funds from crypto scams. Though skeptical at first, I decided to give them a try. Here’s my experience with their service.When I initially contacted TrustGeeks Hack Expert Email.. Trustgeekshackexpert{At}fastservice{Dot}com , I was understandably hesitant. Like many others, I had been tricked into believing my Bitcoin investments were legitimate, only to discover they were locked in a non-spendable wallet with no way of accessing them. However, after sharing my story and details about the scam, the team assured me they had handled similar cases and had the expertise to help. They requested basic information about my investment and began their investigation immediately. The recovery process was nothing short of professional. Unlike many other services that promise quick fixes but fail to deliver, TrustGeeks Hack Expert kept me informed at every stage. They regularly updated me on their progress and were completely transparent about the challenges they faced. There were moments when I wondered if the process would work, but the team’s professionalism and reassurance gave me hope. They were honest about the time it would take and did not make any unrealistic promises, which I truly appreciated. After several weeks of work, TrustGeeks Hack Expert successfully recovered not just my $50,000 investment, but also the so-called profits that had been locked away in the scam's non-spendable wallet. This was a huge relief, as I had resigned myself to the idea that I had lost everything. The entire recovery process was discreet and handled with the utmost care, ensuring that the scam company remained unaware of the recovery efforts, which helped prevent further complications. TeleGram iD. Trustgeekshackexpert & What's A p p +1 7 1 9 4 9 2 2 6 9 3

  • 23.01.25 02:37 [email protected]

    After falling victim to a fraudulent Bitcoin mining scam, I found myself in a desperate situation. I had invested $50,000 into a cloud mining website called Miningpool, which turned out to be a complete scam. For months, I tried reaching out to the company, but I was unable to access my funds, and I quickly realized I had been taken for a ride. In my search for help, I came across TrustGeeks Hack Expert, a service that claimed to help people recover lost funds from crypto scams. Though skeptical at first, I decided to give them a try. Here’s my experience with their service.When I initially contacted TrustGeeks Hack Expert Email.. Trustgeekshackexpert{At}fastservice{Dot}com , I was understandably hesitant. Like many others, I had been tricked into believing my Bitcoin investments were legitimate, only to discover they were locked in a non-spendable wallet with no way of accessing them. However, after sharing my story and details about the scam, the team assured me they had handled similar cases and had the expertise to help. They requested basic information about my investment and began their investigation immediately. The recovery process was nothing short of professional. Unlike many other services that promise quick fixes but fail to deliver, TrustGeeks Hack Expert kept me informed at every stage. They regularly updated me on their progress and were completely transparent about the challenges they faced. There were moments when I wondered if the process would work, but the team’s professionalism and reassurance gave me hope. They were honest about the time it would take and did not make any unrealistic promises, which I truly appreciated. After several weeks of work, TrustGeeks Hack Expert successfully recovered not just my $50,000 investment, but also the so-called profits that had been locked away in the scam's non-spendable wallet. This was a huge relief, as I had resigned myself to the idea that I had lost everything. The entire recovery process was discreet and handled with the utmost care, ensuring that the scam company remained unaware of the recovery efforts, which helped prevent further complications. TeleGram iD. Trustgeekshackexpert & What's A p p +1 7 1 9 4 9 2 2 6 9 3

  • 23.01.25 14:20 nellymargaret

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  • 26.01.25 03:54 [email protected]

    Losing access to my crypto wallet account was one of the most stressful experiences ever. After spending countless hours building up my portfolio, I suddenly found myself locked out of my account without access. To make matters worse, the email address I had linked to my wallet was no longer active. When I tried reaching out, I received an error message stating that the domain was no longer in use, leaving me in complete confusion and panic. It was as though everything I had worked so hard for was gone, and I had no idea how to get it back. The hardest part wasn’t just the loss of access it was the feeling of helplessness. Crypto transactions are often irreversible, and since my wallet held significant investments, the thought that my hard-earned money could be lost forever was incredibly disheartening. I spent hours scouring forums and searching for ways to recover my funds, but most of the advice seemed either too vague or too complicated to be of any real help. With no support from the wallet provider and my email account out of reach, I was left feeling like I had no way to fix the situation.That’s when I found out about Trust Geeks Hack Expert . I was hesitant at first, but after reading about their expertise in recovering lost crypto wallets, I decided to give them a try. I reached out to their team, and from the very beginning, they were professional, understanding, and empathetic to my situation. They quickly assured me that there was a way to recover my wallet, and they got to work immediately.Thanks to Trust Geeks Hack Expert , my wallet and funds were recovered, and I couldn’t be more grateful. The process wasn’t easy, but their team guided me through each step with precision and care. The sense of relief I felt when I regained access to my crypto wallet and saw my funds safely back in place was indescribable. If you find yourself in a similar situation, I highly recommend reaching out to Trust Geeks Hack Expert. contact Them through EMAIL: [email protected] + WEBSITE. HTTPS://TRUSTGEEKSHACKEXPERT.COM + TELE GRAM: TRUSTGEEKSHACKEXPERT

  • 28.01.25 21:48 [email protected]

    It’s unfortunate that many people have become victims of scams, and some are facing challenges accessing their Bitcoin wallets. However, there's excellent news! With Chris Wang, you can count on top-notch service that guarantees results in hacking. We have successfully helped both individuals and organizations recover lost files, passwords, funds, and more. If you need assistance, don’t hesitate—check out recoverypro247 on Google Mail! What specific methods does Chris Wang use to recover lost funds and passwords? Are there any guarantees regarding the success rate of the recovery services offered? What are the initial steps to begin the recovery process with recoverypro247? this things i tend to ask

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