CV2JOB — AI Platform for IT Outsourcing & Outstaffing
CV2JOB — a product we built for ourselves and continue to evolve with AI
CV2JOB is not a typical client project.
It is a product we have been building and evolving for over three years — from an internal tool to a full-scale SaaS platform for IT outsourcing and outstaffing companies.
We continue to develop CV2JOB today, while also using the platform ourselves as active customers in our own operational workflows.
How the idea was born
The idea behind CV2JOB came from a very real, everyday problem we faced in our own IT business:
developer CVs were scattered across different tools and formats;
matching candidates to incoming requests took days;
part of the team remained idle on the bench;
partner requests were lost across LinkedIn, Telegram, emails, and spreadsheets.
We decided to build a single, centralised system to solve these issues — initially for internal use, and later as a product for the wider market.
Three years of development: from MVP to an AI-driven platform
Over the course of three years, our team went through the full product lifecycle:
market research and in-depth interviews with IT outsourcing companies;
SaaS architecture design;
development of a working MVP with real business logic;
building a structured developer and CV database;
creating mechanisms for sharing and managing partner requests;
continuous testing in real production workflows.
A key stage in the product’s evolution was the introduction of AI as a core capability.
The role of AI in CV2JOB
AI in CV2JOB is not an add-on or a marketing feature.
It is a foundational layer designed to replace manual, repetitive work and enable scale.
We are building AI components around real operational needs:
AI Matching
Automated matching between job requests and developer profiles:
analysis of CVs, tech stacks, experience, and domain expertise;
shortlist generation in minutes instead of days;
explainable matching logic rather than a “black box”.
AI HR Validation
Intelligent candidate validation:
generation of technical and soft-skill questions;
initial evaluation of responses;
decision support for recruiters and tech leads.
AI Request Aggregation
Aggregation and normalisation of job requests from multiple sources:
LinkedIn, Telegram, job boards;
transforming unstructured text into standardised job profiles;
preparing data for automated matching.
AI allows us to reduce human overhead, increase response speed, and scale operations without proportionally increasing headcount.
We build the AI by using it ourselves
One of the most important aspects of this project is that we are not only the developers — we are also active users of CV2JOB.
Our team uses the platform to:
manage our own developer pool;
test and validate AI matching quality;
evaluate HR validation flows;
continuously improve UX and decision logic.
This hands-on usage helps us clearly see:
where AI genuinely saves time;
where human involvement is still essential;
which features deliver real business value.
Current stage of the project
Today, CV2JOB:
has a working MVP;
is used internally and by early external companies;
is in an active validation phase;
continues to expand its AI-driven functionality.
We are deliberately moving from manual workflows → semi-automated processes → AI-driven operations, while maintaining control and quality at every step.
Why this project matters to us
CV2JOB demonstrates how we work with long-term products:
we build solutions for real business problems;
we integrate AI where it creates measurable value;
we think and operate as a product team, not just as executors;
we take responsibility not only for code, but for outcomes.
This is not simply a development case.
It is a living product, where we act simultaneously as architects, users, and customers.
