Telegram Scraping & Intelligence System

@devendrathakur12

I’ve worked with Telegram Userbots using Telethon/Pyrogram and MTProto-based automation, including session handling, channel monitoring, message processing, and bot interaction flows. I’m ready to review your fully prepared technical specifications document and map it into the implementation before touching the code. For the hybrid backend, I’d evaluate Rust for concurrent ingestion and Python for NLP/LLM pipelines, with SQLite/PostgreSQL plus a search index for message retrieval and categorization. The GUI can be built around a Windows-native dashboard with indexed search, media filters, analytics, and backups. I’d specifically validate private-channel access, bot keyboard state changes, flood-wait errors, and Telegram session limits before scaling workers. Send the technical specs document and your 100+ references, and I can start immediately.

@denisSolution

Hi, I'm Denis, a full-stack developer with experience building data extraction systems and backend automation. I've worked with Telethon and Pyrogram on userbot projects and understand MTProto implementations and scraping trade-offs. I understand your needs: a system to discover and monitor Telegram channels, extract financial data like wallet addresses, classify content semantically, and present it through a clean desktop interface. The hybrid Rust/Python approach balances performance with development speed effectively. I've built similar data pipelines where the core challenge was reliable classification and search. Semantic search quality depends on chunking strategy and context handling, especially with multilingual content. RTL language support is manageable with proper preprocessing. My approach: start with a thorough technical review to validate architecture and identify bottlenecks early. Then focus on the core scraping engine and data pipeline first—get it stable and monitored—before layering in classification and GUI. This keeps risk low and validates assumptions before heavy dashboard investment. Key variables I need to understand: Telegram's rate limiting constraints and your session management strategy for 24/7 operation. These typically drive architecture decisions more than anything else. I'm ready to start immediately. Let's discuss the details. Thanks, Denis.

@sumitsthakur

My experience with Telegram userbots extends to both Telethon and Pyrogram, as well as direct MTProto implementations, including approaches leveraging Rust. I am fully prepared and keen to discuss the detailed technical specifications document you have prepared for this project. Your comprehensive vision for a specialized Telegram Intelligence & Scraping System, featuring a hybrid Rust/Python backend, a robust desktop GUI on Windows VPS, and core functionalities like automated discovery, bot interaction, and financial extraction, is well understood. I will prioritize the implementation of your AI classification and multi-language translation engine using modern LLM APIs for precise semantic searching. My approach will focus on high efficiency and rapid delivery, leveraging advanced AI coding environments to accelerate development and ensure a smooth, integrated system for monitoring and analysis. I am also open to discussing any alternative technical suggestions that could enhance efficiency while achieving the desired outcomes. I am confident in delivering this complex system effectively and look forward to reviewing the documentation with you.

@PINESCRIPTERR

Hi, I have experience with Python automation, scraping, API integrations, data pipelines and AI/LLM workflows, including Telegram automation with Telethon/Pyrogram and MTProto-based systems. I’m ready to review your fully prepared technical specification and work directly from it. I can build the system as a modular Python/Rust backend with persistent workers for Telegram collection, session management, message/media processing and structured storage. For authorised channels, groups and bots, I can implement continuous monitoring, bot interaction and dynamic Inline Keyboard handling while respecting Telegram rate limits and access controls. The intelligence layer can handle structured extraction, semantic classification/search and multilingual LTR/RTL translation through LLM APIs. I’ll separate collection, enrichment, classification and indexing so the system remains maintainable and scalable. For the Windows dashboard, I can implement live monitoring, search, media categorisation, analytics and backup/restore, with logging, reconnection and process supervision for reliable 24/7 operation. I’ll use AI coding tools where they improve development efficiency without sacrificing code quality, testing or security, and I’m happy to suggest alternatives from your provided tool/reference list where they offer a better architecture. Best regards, Houssame

@maxscender

I have hands-on experience building Telegram userbots with Telethon/Pyrogram and Rust MTProto, and I’m ready to discuss your fully prepared technical specs. I’d approach this by mapping your documented workflow into a modular hybrid backend: Rust for high-concurrency MTProto scraping and session handling, Python for LLM-driven classification, translation, and semantic indexing, with a lightweight Windows GUI that reads from a unified data layer. I’d treat the bot/spam filter as a critical-path component, implementing behavioral and heuristic checks at ingestion time so junk never pollutes the intelligence pipeline. I’d also use AI-assisted development to accelerate delivery and keep engineering overhead low, while producing clear documentation as we go. I’m fully prepared to execute from your existing specs and make practical adjustments where they improve reliability or efficiency.

@MuhammadUzair16

Hi, I am a software engineer with over 16 years of experience, including Telegram userbots built with Telethon/Pyrogram and MTProto-based automation. I am ready to review and discuss your fully prepared technical specifications document. I understand that this is more than a basic scraper: it requires reliable 24/7 account handling, channel/group discovery, bot interaction with inline keyboards, structured payment and wallet extraction, semantic classification, multilingual LTR/RTL translation, and a practical Windows dashboard. I can build the system with a maintainable Python/Rust architecture, robust session management, searchable storage, media categorization, analytics, backups, logging, and recovery safeguards. I also use modern AI development tools effectively while keeping the resulting code controlled, testable, and documented. Before starting, I would like to confirm the expected number of Telegram accounts and whether the GUI must run interactively on the VPS or connect remotely. Given the breadth of the system, my bid covers a clearly defined first production milestone; I am flexible about structuring the remaining scope into practical milestones after reviewing the specification. Please contact me to discuss details.

@rosscarter1011

Hey, I've built plenty of Telegram userbots using both Telethon and Pyrogram for automated channel scraping and handling inline keyboard flows. I am ready to dive into your technical specs document and get this Windows VPS setup moving. Handling financial extractions like crypto addresses alongside semantic LLM filtering is right in my wheelhouse. Do you already have the specific LLM API provider picked out for the translation engine?

@TeraByte26

Hi Khaled Waiting for your response in chat! Best Regards.

@longngoc2307

Perfect Match "TELEGRAM USERBOT SCRAPING & INTELLIGENCE SYSTEM" — you need a 24/7 MTProto pipeline that can monitor authorized sources, classify content, and make the data searchable. I can work with Telethon/Pyrogram-style MTProto userbots and am ready to review your fully prepared technical specifications. I’d keep the scraper, indexing, AI classification, translation, and Windows dashboard as separate services so failures in one part don’t stop collection. For private channels/groups, access should remain limited to accounts and sources you are authorized to monitor. The financial extraction layer can then normalize detected plans, wallet addresses, and payment methods without changing the source content. Can you share the technical specification document and confirm which sources are explicitly authorized for automated collection? Looking forward to work with you

@muneeb6767

I have experience building Telegram automation/scraping systems with Python, Telethon/Pyrogram, MTProto and bot interaction, including message extraction and structured data processing. I’m ready to review your fully prepared technical specs document and discuss the most efficient architecture for the hybrid scraping, AI classification/translation, and Windows dashboard.

@gotucat

Hi, I reviewed the project and understand the main requirement: building a 24/7 Telegram Intelligence & Scraping System with a hybrid backend and Windows dashboard. I’m ready to discuss the fully prepared technical specs document and can briefly share relevant Telegram Userbot experience with Telethon/Pyrogram or Rust MTProto. I can implement public and private channel discovery, continuous scraping, bot interaction, payment-data extraction, semantic search, multilingual LTR/RTL translation, media categorization, analytics, indexing, and backups. The architecture can combine Rust/Python, MTProto, Web-Z, Userbots, and API integrations while applying Web Security and clean Coding practices. I’ll keep the system reliable, organized, responsive, and manageable on a Windows VPS, with careful handling of scraping workflows and data. Let’s discuss here now.

@Microlent

Hi, I’m familiar with Telegram Userbot development using Telethon/Pyrogram and MTProto-based architectures, including Telegram automation, channel/group monitoring, message processing, bot interaction, and Python-based scraping pipelines. I’m ready to review your fully prepared technical specifications document and discuss the architecture, workflow, toolset, and delivery plan in detail. Your hybrid Rust/Python + MTProto + AI/NLP approach is technically interesting, particularly the combination of continuous content collection, bot interaction, financial-data extraction, semantic classification, multilingual translation, and a Windows monitoring dashboard. I can work closely with the provided documentation and also evaluate whether parts of the system can be implemented more efficiently using alternative libraries, services, or architecture without compromising reliability. I understand that you specifically want a developer who can work intelligently with modern AI coding tools, move quickly, and avoid unnecessary engineering overhead. Please share the technical specifications document. Let’s connect on chat and go through the architecture and implementation plan.

@juanpablomacf

My experience with Telegram userbots is hands-on: I've built scraping and automation flows using Telethon for session-based MTProto access, plus Pyrogram for higher-level bot interactions when inline keyboards or dynamic callbacks needed cleaner handling. I'm comfortable running persistent userbot sessions on Windows VPS environments, dealing with rate limits, session regeneration, and the quirks of private-channel joins. I'm ready to go through your full technical spec document whenever you want. The part that usually gets messy in systems like yours isn't the scraping - it's coordinating MTProto userbot actions with backend logic so channel discovery, bot interactions, and financial extraction don't collide or create duplicate tasks. For the AI layer, I'd start by defining the semantic categories before wiring LLM calls. The biggest risk is letting the classifier drift when multilingual content mixes slang, trading jargon, or crypto terminology. Clean pre-processing and consistent embeddings matter more than model choice. A few quick questions: - Are your userbot sessions already authenticated, or should I generate fresh MTProto sessions from scratch? - Does the dashboard need real-time push updates, or is a short polling interval acceptable? - For financial extraction, should crypto addresses be validated (checksum, format) or simply detected? Ready to discuss the full spec and propose optimizations if helpful. Juan Pablo

@NaveenSingh09

Hello, I’ve carefully reviewed your requirements and have the expertise to deliver this project with high quality, on time, and to your expectations. With 6+ years of hands-on experience in Python automation, social media growth, and AI-driven workflows, I’m confident I can deliver the results you need. With extensive experience building Telegram userbot solutions using Telethon and Pyrogram, I can quickly set up a hybrid scraping engine that automates channel discovery, bot interaction, and data extraction. My approach will start by designing a modular Rust/Python pipeline that pulls raw messages via MTProto, then uses regex and heuristic rules to flag subscription plans, crypto wallets, and payment links. Next, I will integrate a translation layer powered by an LLM API, ensuring clean LTR/RTL support, and build a semantic classifier to separate trading‑signal channels from general news. The desktop dashboard will be a lightweight Win‑UI app that displays indexed content, media tags, and subscriber stats, with backup hooks. I will leverage open‑source libraries and AI‑assisted coding to keep the build efficient. Let’s discuss your specs and move forward. Looking forward to discussing the project details further on chat. Best regards, NAVEEN THAKUR

@techmadigital

Hi, I have hands-on experience with Telegram userbots using Telethon and Pyrogram, including MTProto channel scraping, bot automation with inline keyboards, and extracting wallet addresses and payment details. I am ready to review your prepared technical specs document immediately. I would focus on the hybrid Rust and Python backend, the semantic search and multi-language translation engine, and the Windows desktop dashboard with monitoring, categorization, and backup. I build with authentication, API integrations, testing, and deployment included. I use modern AI coding tools to move quickly while keeping code clean and documented. Thanks, Nikhil Preferred & Verified Freelancer | 5 Star Rating | 100% Project Completion

@manishashree12

Hello there, I have extensive experience working with Telegram Userbots using Telethon and Pyrogram. I am fully prepared to discuss the technical specs document for your Telegram Intelligence & Scraping System. Leveraging a hybrid backend of Rust/Python with MTProto/Web-Z/Userbots and a desktop GUI dashboard, I can automate scraping, interact with bots, and implement AI classification seamlessly. I am open to alternative technical suggestions to optimize efficiency. Let's discuss how I can accelerate delivery and lower engineering overhead for your project. Thanks, Manisha

@arslanshahid386

Hi, I noticed you're developing a Telegram Intelligence & Scraping System that operates on a Windows VPS around the clock. With my experience using Telethon and Pyrogram for creating Telegram Userbots, I can effectively contribute to your project’s hybrid backend. Leveraging Python's robust data scraping capabilities and ensuring web security will be pivotal in achieving your system's goals. I'm ready to delve into the technical specs document to ensure alignment with your requirements. Could you share more about the specific functionalities you envision for the desktop GUI dashboard?

@codeandcommand

I have built Telegram userbots with both Telethon and Pyrogram, handling session pools, flood wait limits, and channel scraping without triggering bans. For this intelligence system I would set up rotating sessions, store scraped data in a structured database, and layer basic NLP filtering on top for OSINT flagging. These numbers are based on the post as written, we will refine them after a quick scope conversation. I can start today. Want me to send a quick scope doc?

@Sv3nie

Hi, First thing I'd hand you is the Rust MTProto scraper running on your VPS, then the AI tagging and dashboard on top. Rust is my core work, Python bots alongside it. Lets get in contact first.