Examples of Agent Systems
AI agents built on our technologies already demonstrate nearly 100% accuracy in tasks where classical algorithms fail.
Each of them is an example of the 98–100 principles applied in practice.
Digger4Data
An autonomous agent for intelligent search and data aggregation.
Finds and combines specific data from databases containing millions of documents in dozens of formats.
Understands complex structures: PDFs with attachments, tables, presentations, images, scans, and links.
Supports over 20 file formats and uses an adaptive data processing system.
Six months of industrial operation have shown maximum accuracy and reliability in specialized analytical tasks.
Mail2Mail
An AI agent for corporate correspondence.
Independently reads, classifies, and processes incoming emails, understands sender intent, and analyzes attachments of any type — from documents and spreadsheets to archives and images.
Determines the appropriate routing and generates a correct response.
Operates around the clock without human intervention, servicing multiple mailboxes simultaneously.
Does not lose emails, avoids duplicates, and is protected against loops.
A built-in web interface allows rule management and process monitoring.
More than two months of operation have confirmed high accuracy of interpretation and reliable processing of message flows.
Trip2Count
An intelligent business travel and expense management system.
Automatically collects all trip data: routes, timing, expenses, documents, and reports.
Builds a time-based pipeline of the trip, prepares data for accounting, invoicing, and payroll.
Supports document input in any format — photo, screenshot, file, or email.
A built-in agent oversees the process, checks documents, closes travel records, and issues reminders.
The beta version already demonstrates maximum ease of use for employees and full automation of document workflow.
Biz3 2.0
An AI platform for intelligent procurement and offer analysis.
Processes complex estimates and requests for any category of goods — from construction materials to auto parts and equipment.
The user sets parameters (deadlines, priorities, budget, criteria), and the system finds optimal supplier combinations balancing price, quality, and delivery time.
The main feature is semantic search by meaning, not by keywords:
"Find the best offers balancing price and quality with delivery in under a week for these VINs."
The system analyzes supplier databases, checks reputation, and considers logistics and client conditions.
Integrates with Google Merchant Center, Amazon, Alibaba, WooCommerce, Shopify, Magento, and other platforms.
Supports import via schema.org and connection through an MCP interface to ChatGPT, Claude, Cursor, or corporate systems.
The Biz3 2.0 architecture supports local markets and manufacturers.
Its goal is to turn the procurement process into a dialogue between human and system, where finding the optimum becomes a natural outcome of interaction.
A demo version is available.