Telegram Bot/CRM/PARS

Budget: 1800 USD Deadline: 7 days

I saw that the presentation mentions monitoring 800+ chats, user collection, and CRM for operators. The main headache in such systems is not writing the code but not burning the account during the initial parsing of history. That's when Telegram throws FloodWait and PeerFlood, and hasty user bots get banned within half an hour. Therefore, I will build the architecture around this risk.

What I will specifically do:
User bot on Telethon with an asynchronous queue and smart limits — FloodWait is handled automatically, pauses between requests are dynamic, not a fixed sleep.
Parsing 800+ chats in batches with prioritization — first active, then archived, to avoid expiration and overloading the API.
CRM part on C# MVP: operators see new leads in real-time, take them into work, statuses, dialogue history.
Storage in PostgreSQL — structure for analytics and user search.
Everything in Docker containers, so deployment is a one-liner.

One nuance that others will miss: the first run of parsing history on 800 chats is the most dangerous moment. I gradually warm up the account, increasing the load so that Telegram perceives the activity as organic. This is the difference between "works for a week" and "banned on the first day."

After delivery, I won't disappear — I will be available for any edits and improvements. I am currently free and can start today. Message me, and I will draft a plan for the first stage with estimates by blocks within an hour. Expand

Budget: 2000 USD Deadline: 14 days

📌Hello.👋
⭐️My name is Andrey.
⭐️My work experience: 12 years+

• ➡️I can show works specifically on bot development
• 🎨Portfolio: Freelancehunt
• ✅Work rating on Behance (over 600,000 views)
• 💼More works here: Dribbble

Budget: 480 USD Deadline: 10 days

⚡ The main risk here is not the code, but account bans. 800+ chats and initial parsing of history is exactly the moment when Telegram starts throwing FloodWait and PeerFlood, and hasty user bots catch limits in batches. If the architecture does not hold per-account limits from day one and cannot seamlessly transfer a chat from a limited account to a live one, the system will choke under mass load.

The second subtle point is the ONLY source of truth. With 5, and then 10-20 accounts, who specifically monitors a particular chat should be determined by a single distribution table in PostgreSQL, not by logic inside the worker. Otherwise, there will be user duplicates and repeated parsing of the same chat by two sessions.

Here's how I see it. Each Telethon user bot is a separate session with its own throttling and backoff. The dispatcher distributes chats by account_id, balances the load, and when an account is banned, its chats auto-migrate while the rest continue to work. Grouping strictly by telegram id - one card, even if a person has written in 20 chats.

I suggest starting not with all 14 points at once, but with a narrow MVP slice: 1) Telethon infrastructure on N accounts plus PostgreSQL schema plus handling FloodWait/PeerFlood; 2) operator bot with queue and statuses; 3) admin section (accounts, chats, operators, parser); 4) Docker plus launch and backup instructions. This way, you quickly see live lead collection, and we can fine-tune the rest step by step.

I have previously built systems with a similar profile: Telegram bots, parsing large volumes, cards on PostgreSQL, Docker builds. For example, a real estate and auto aggregator catalog (pinger) - there, it's all about data flow and object cards at scale.

To avoid guessing. How many accounts do we start with and what is the actual pace of adding chats in the first weeks? And how to prioritize lead distribution to operators - by freshness of activity, by chat, or just a simple queue? Please write in the correspondence, and let's break down the stages in more detail. Expand

Budget: 2000 USD Deadline: 7 days

Hello, I have worked on a Telegram parsing system — user bots on Telethon, monitoring 800+ chats, collecting 50,000+ users, and a bot for operators. Very similar to your task!

Question regarding the essence: how do you plan to distribute clients among operators — evenly in turn or taking into account statuses (for example, "Call back" returns to the same operator)? And how many accounts do you want to connect at the start of the MVP?

I suggest we get in touch; I will provide you with free technical consultation and we can create a development plan + I will tell you about my team!

Budget: 500 USD Deadline: 5 days

Hello,

I can develop this Telegram client search automation system as an MVP using Python, Telethon, PostgreSQL, Docker, and Telegram Bot API.

I will build a scalable architecture that supports:

* Multiple Telegram accounts with independent Telethon sessions
* Automatic chat distribution and load balancing
* Continuous parsing and monitoring with proper FloodWait/reconnection handling
* PostgreSQL for users, messages, chats, operators, and processing history
* Operator and admin Telegram bots
* Dockerized deployment with clear setup, update, and backup instructions

The system will be designed for future scaling to thousands of chats, additional accounts, CRM integration, and new features without major refactoring.

I focus on clean architecture, reliability, and maintainable code. I'd be happy to discuss the implementation details and timeline.

Best regards. Expand

Budget: 450 USD Deadline: 12 days

Hello. My name is Vladimir, I am a NodeJS and Python developer, as well as the founder of the engineering agency Vaysed. I have thoroughly studied the technical assignment for developing an MVP system for automatic client search in Telegram. I understand that you need to create a fault-tolerant infrastructure based on a pool of Telethon accounts for parsing 800 or more chats, with load balancing, bypassing blocks, and delivering unique leads to operators through a bot, without using a web panel.

To implement this task, I propose designing a scalable microservice architecture. The administrative and operator interfaces will be developed on the modern asynchronous framework aiogram 3, which will ensure a high response speed of the interface. The pool of user bots on Telethon will be managed by a central coordinator, which will dynamically distribute chats among active sessions, intercept FloodWait errors, and smoothly transfer tasks to free accounts. We will deploy the database on PostgreSQL for reliable storage of activity history and strict deduplication of users by their Telegram ID. To eliminate collisions when issuing a client card to two operators at once, I will implement a system of instant locks based on Redis. The entire architecture will be packaged in Docker with detailed instructions for quick deployment via docker-compose.

I have relevant experience in building high-load Telegram systems. In the Lumos project, I successfully implemented complex asynchronous monitoring and real-time streaming data processing. And while developing the PAYBACK CARTEL system, I designed a deep role model from scratch, access distribution algorithms, and synchronization of large data arrays, which fully covers the logic of your sales department and administrative management.

You can view my portfolio at this link: Freelancehunt

I suggest discussing the technical details of the chat distribution algorithm and session protection mechanisms in private messages.

Budget: 300 USD Deadline: 12 days

Hello, Alex! I have thoroughly studied your technical assignment. The task is large-scale but absolutely feasible with the right architecture design for the workers. I have experience working with asynchronous scripts in Python 3.12 and am ready to create a fault-tolerant MVP based on Telethon, PostgreSQL, and Docker according to all points of the technical specification.

I fully understand that for stable processing of 800+ chats, a regular round-robin load balancer will not work — the system will simply burn out the accounts. I propose architectural solutions for each critical node:

1. Protection against bans and FloodWait during initial parsing:
Mass loading of history is the most dangerous moment. I will implement step-by-step parsing of history in batches through asyncio.Queue with dynamic pauses and handling of FloodWait/PeerFlood at the level of the basic Telethon client with exponential backoff. If one account temporarily goes into restriction, the system will automatically reassign its chats to other live sessions from the pool.
2. Centralized load balancer (Single source of truth):
Distribution of chats among account_id will be strictly managed through a central table in PostgreSQL. This will completely eliminate the situation where the same chat is monitored by two sessions simultaneously, creating duplicate leads. Adding or disabling accounts by the administrator will occur on the fly without changing the configuration code.
3. Atomic operator queue (Protection against race conditions):
To prevent two managers from intercepting one client, lead assignment will occur atomically at the PostgreSQL database level using status triggers. As soon as an operator opens a card, its status changes, and it disappears from the output for others. Merging user cards from different chats will strictly follow the unique Telegram ID.
4. Containerization and Docker:
I will deploy the system based on microservice logic. I will prepare clean Dockerfile and docker-compose.yml, set up volumes for storing the database and Telethon session files, so that restarting containers does not lead to data loss. I will provide clear instructions for launching with one command, backing up (pg_dump), and updating.

The budget and timeframe of 12 days I mentioned are allocated for the complete implementation of all 14 points of your technical specification "turnkey" without cutting functionality.

Please let me know what period of history (depth in days or hours) needs to be collected during the initial parsing of new chats? Expand

Budget: 2000 USD Deadline: 30 days

Hello.
We are ready to start immediately.
We will provide you with excellent results that will perfectly meet your requirements.
The current requirements are very precise.
So, I think we can start working right away.
One question I have is whether I must use C#.

Can I use another stack?

Do I have to use C#?

Budget: 350 USD Deadline: 14 days

Good day, Alex.
I have reviewed the specifications in detail. The main difficulty here is not in parsing messages itself, but in reliably distributing 800+ chats among Telethon accounts without duplicates, correctly handling FloodWait/PeerFlood, and continuing the system's operation if one of the accounts is temporarily restricted.
For the first version, I propose the following architecture:
— each Telegram account has a separate Telethon session and its own limits;
— the distribution of chats among accounts is stored centrally in PostgreSQL;
— one chat by default is processed by only one account;
— users are strictly grouped by Telegram ID;
— a client is atomically assigned to an operator, so two operators will not receive the same card;
— FloodWait, PeerFlood, reconnect, and temporary blocks are handled without stopping the entire system.
The first phase will include:
— support for up to 5 Telegram accounts;
— import and management of the chat list;
— initial collection of history and monitoring of new messages;
— PostgreSQL with a structure for users, chats, messages, and activity;
— an operator bot with a queue and statuses;
— a basic administrative section;
— Docker Compose and instructions for launching and backing up.

After stable testing on a limited number of accounts and chats, we can scale the system to the full volume of 800+ chats in a separate phase, add advanced statistics, and CRM integrations.
Before starting, we need to clarify the number of accounts and operators in the first version, as well as the history period that needs to be loaded from each chat. Expand

Budget: 1500 USD Deadline: 30 days

Good day.
I have experience in developing applications using Telethon sessions for collecting and processing information, creating mailings, etc. I am interested in your project and could take on its execution.

Budget: 50 USD Deadline: 1 day

Good day, Alex.

Your 800+ chats during the initial parsing of the history will definitely trigger FloodWait within the first few minutes — that’s why load balancing between accounts should be built not on round-robin, but on adaptive tracking of limits for each Telethon session with a queue of delayed retries. Your system will continue collecting while the blocked account waits, and the others will pick up its chats without duplication. Each lead in the operators' queue is atomically secured in PostgreSQL — the second operator will not see it.

Options:

≈13 days: 250–350 USD
Basic functionality for launch with a limited number of accounts and chats.
- Support for up to 5 Telegram accounts
- Automatic collection of messages from a specified list of chats
- Simple lead queue for operators with status changes
- Basic administrative functionality for chat management
- Deployment via Docker

or

≈24 days: 450–650 USD
Full-fledged automation system with adaptive balancing and extended management.
- Scalable support for 20+ accounts with adaptive load distribution
- Full cycle of initial history parsing with FloodWait handling
- Complete user card with message history from all chats
- Flexible lead reissue system (30/60/90 days)
- Full administrative section with statistics and rights management

or

≈40 days: 800–1000 USD
Maximally resilient system with enhanced protection against blocks and optimization for big data.
- Database optimization for processing thousands of chats and millions of messages
- Advanced anti-flood system and automatic session reconnection
- Bulk data import/export module and integration API templates
- Priority support and maintenance after launch for a month
- Complete set of instructions for backup and scaling Expand

Budget: 300 USD Deadline: 10 days

Good day!

I will create an MVP according to your specifications: Telethon user bots (N accounts) + operator bot + admin section + PostgreSQL + Docker, without a web panel.

Critical points that I will implement from day one:

- separate session/throttling for each account + correct handling of FloodWait / PeerFlood / reconnect;
- a single source of truth in PostgreSQL: distribution of chats by account_id without duplicates (and auto-migration of chats when an account is restricted);
- deduplication of users strictly by Telegram ID — one card even with 20 chats;
- queue of operators with client fixation + statuses + reissue after N days.

MVP components:

- user bot infrastructure + database schema + parsing history / live monitoring;
- operator bot (queue, card, statuses);
- admin (accounts, chat import/export, operators, parser, statistics);
- docker-compose + instructions for launching/updating/backing up.

Question: how many accounts and chats at the start, and is the reissue of clients never or after N days?
I am ready to start in phases after a brief agreement. Expand

Budget: 12345 USD Deadline: 3 days

Hello! Do you already have a rough idea of how many Telegram accounts you plan to use at the start so that I can assess the load on the balancer?

I will be able to provide more precise timelines and budget in personal correspondence.

Here’s how I will implement this project:
1. I will deploy userbots on Telethon with automatic chat distribution and handling of Telegram restrictions.
2. I will create a Telegram bot for operators with a client queue and statuses, as well as an admin panel for managing accounts, chats, and statistics.
3. I will set up PostgreSQL, Docker configuration, and foresee the possibility of scaling to 20+ accounts without changing the code.

Thank you for considering my proposal. I look forward to the opportunity to collaborate with you!

Budget: 370 USD Deadline: 5 days

Good day, I am a Python developer with extensive experience in developing Telegram bots of various complexity. I can complete your order quickly and efficiently. Write to discuss the details; I am ready to start today. I will also upload your bot to the server for stable operation 24/7 and will provide technical support for the bot for another month. This is included in the cost.

Budget: 1000 USD Deadline: 28 days

Ready to take on the development of a client search automation system in Telegram. I have experience working with Telethon, PostgreSQL, and Docker. I will ensure all requirements of the technical specifications are met.

Budget: 50 USD Deadline: 1 day

Hello. To build this system, I will use a modular architecture based on Telethon, which will allow for efficient scaling of work with numerous Telegram accounts and chats, utilizing an asynchronous task queue for flexible load distribution and resilience to network failures. The focus will be on reliable handling of Telegram limits and automatic recovery, while ensuring optimized data storage in PostgreSQL for quick access by operators and administrators. I have experience implementing high-performance parsers and automation systems that use similar principles, with ready-made solutions for Docker deployment and monitoring. I suggest discussing all implementation details, final budget, and timelines in private messages.

Budget: 500 USD Deadline: 14 days

The task is to create a system on user bots that monitors 800+ chats, parses potential clients, and distributes leads to operators via a bot.

I am building it this way: Telethon workers in separate Docker containers (one container = one account), adding a new account = launching a container with env variables, without modifying the code. Chats are stored in PostgreSQL linked to account_id, the load balancer, when adding a chat, looks at the current load of each account and assigns it to the least loaded one. FloodWait and PeerFlood are intercepted at the level of the basic Telethon client with exponential backoff and auto-reassignment of the chat to another account in case of a ban.

The key risk: Telegram aggressively bans accounts during mass history parsing. I perform the initial parsing with delays and batching through a queue (asyncio.Queue) to avoid exhausting accounts in the first days.

How many operators will be working simultaneously, and is there a need for lead prioritization logic (for example, by user activity or by chat)?