AI System for Tender Search and Analysis for RJ Tech

Client

RJ Tech is a UK technology company working with tender opportunities and participating in procurement across the UK and Scotland.

Problem

Tender opportunities are published across multiple sources, use different data structures, and are often duplicated between platforms.

The RJ Tech team had to regularly check these sources, review a large number of new listings, and manually determine which tenders were potentially relevant to the company’s profile, capabilities, and requirements.

A significant share of the discovered tenders turned out to be irrelevant, while the initial assessment of each opportunity required a separate review of the description, conditions, deadlines, procurement category, and other parameters.

As a result, a considerable amount of time was spent on searching, cleaning, and initially filtering information before the team could move on to a detailed review of a promising tender and make a decision about participation.

Solution

For RJ Tech, we developed a custom web system that automates the full initial tender workflow — from data collection to preparing a structured result for further review.

The system automatically retrieves new tenders from connected sources, normalizes the data into a consistent structure, and checks records for duplicates.

After the initial processing, tenders pass through predefined filtering logic that removes clearly irrelevant opportunities and helps the team focus on potentially valuable procurement opportunities.

For selected tenders, AI analysis is applied: the system reviews the content, key requirements, and other available parameters, then generates a concise annotation that helps the team quickly understand the opportunity and assess its potential relevance.

All results are stored in a single web interface, where the team can review discovered tenders, processing results, and AI-generated annotations without repeatedly working across several external sources.

As a result, the solution does not replace the team’s expert decision on whether to participate in a tender. Instead, it automates the most routine part of the workflow: collection → cleaning → deduplication → initial filtering → AI analysis → result storage