</ AI Telegram Bot Aggregator for Electronics Supplier >

A Telegram bot AI aggregator for digital services was created for an electronic components supplier. The vulnerability of traditional parsing was resolved by implementing an LLM model for data collection. Result: a fault-tolerant service that autonomously bypasses protection systems to find the best prices.

300+

daily processed links

100%

independence from design changes

24/7

autonomous search for best prices

Client

A supplier of electronic components for development and DIY: modules, sensors, controllers, and devices. Offering a wide range, quality control, and consulting support.

Voltik

Partnering since 2025

Client website

"Using neural networks for information gathering exceeded all our expectations. We've forgotten about the constant parsing errors when third-party sites update. The bot runs like clockwork, and customers are satisfied with accurate prices."

Head of Promotion Department

Alexander

Creating a Smart Digital Goods Aggregator

The client was a major supplier of electronic components and devices for DIY development. The company identified an open niche in the virtual services market. An ambitious goal emerged — to develop a convenient platform that would help users quickly find the most favorable payment options for foreign services, PlayStation Plus subscriptions, Steam top-ups, and Apple ID cards. The project was prompted by the absence of a unified hub: buyers had to manually monitor dozens of scattered websites with different commission rates. The task was to create an intuitive tool that would consolidate all offers in one window, save users time, and ensure pricing transparency in the digital products market.

Client Request: Vulnerability of Traditional Parsing

The main challenge was the instability of data collection. Traditional parsers are rigidly tied to HTML tags and CSS classes. Any minor change in design or layout on the source website would break the script. Additionally, many marketplaces use aggressive anti-bot systems that instantly block automated requests, making regular price monitoring impossible.

Solution: Implementing LLM for Data Extraction

We completely abandoned standard selector-based collection. Over two months, the team built a new architecture: the script downloads the page, strips all code from it, leaving only plain text. This array is then passed to a neural network with a special prompt. The AI independently finds the essence, structures the information, and sends normalized product and price data to our database.

Stack: Python, LLM, PostgreSQL, Telegram API

The technology choice was driven by the task specifics. Python enabled rapid development of protection bypass mechanisms and page loading. LLM model integration became the system's core, guaranteeing complete independence from visual changes on websites. PostgreSQL reliably stores normalized data, while Telegram API allowed us to create a convenient interface with a follow-up notification system for collecting feedback.

Impact: Complete Autonomy and 300+ Links Daily

A fault-tolerant service operating 24/7 was created. The bot processes over 300 links daily and completely autonomously, updating prices without human intervention. Thanks to the AI approach, we achieved 100% independence from design changes on vendor platforms. Maintenance and parser repair costs dropped to zero, while users gained instant access to the best market offers.

Future Plans - Expanding Database and Smart Analytics

In the next six months, we intend to increase the number of daily processed sources to a thousand, connecting Asian and European marketplaces. We're also preparing to implement predictive analytics: the system will forecast seasonal discounts and notify users in advance about the best time to purchase subscriptions.

Implement AI Parsing in Your Processes Today

Artificial intelligence technologies have reached a level where routine data collection can be completely entrusted to algorithms. Eliminate constant script failures and blocks to focus on business growth and sales.

discuss a project

</ Our team >

Julia

Client Relations Specialist. She genuinely loves interacting with people, values trust, and makes sure every client feels cared for, supported, and confident in their choice. She also writes the “TechnoInvestor” column on our corporate blog.

@jamcaj

Vitaly

Lead Developer. Responsible for project architecture and the implementation of innovative solutions. Specializes in AI and draws inspiration from cutting-edge development and automation technologies. Hosts the “TechnoCoder” segment on the company's video blog

@eva3613

Vladimir

UX Designer. Develops intuitive and aesthetically pleasing interfaces, ensuring the logic, usability, and visual consistency of every digital solution the company creates. Writes the “TechnoDesigner” column for the corporate video blog

@XerucuS

Mikhail

AI developer and expert. Develops Telegram and WhatsApp bots, implements CRM and automation, and applies AI technologies to optimize UX/UI and drive project growth.

@Oerby2

Natalia

Lawyer. Ensures legal reliability and transparency in client relationships, reviews contracts, and protects clients’ interests at every stage of their interaction with the company

@assa13nv

Vladimir

Representative of the Laboratory in the U.S. (Florida). Developer.

@vlad_bykanov

Igor

Executive and business consultant. ERP/CRM and process automation developer. Tech evangelist—helps clients grow their businesses using modern technologies and solutions.

@lhtsu

</ Contacts >

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</ AI Telegram Bot Aggregator for Electronics Supplier >

Client

Creating a Smart Digital Goods Aggregator

Client Request: Vulnerability of Traditional Parsing

Solution: Implementing LLM for Data Extraction

Stack: Python, LLM, PostgreSQL, Telegram API

Impact: Complete Autonomy and 300+ Links Daily

Future Plans - Expanding Database and Smart Analytics

Implement AI Parsing in Your Processes Today

</ Our team >

Julia

Vitaly

Vladimir

Mikhail

Natalia

Vladimir

Igor

</ Contacts >

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