RAG Assistant Reduces Search Time by 20% and Cuts Cloud Costs

In six months, five engineers at Runiti turned a personal prototype into an enterprise service that automatically indexes Confluence and GitLab, respects access rights, and operates entirely behind the firewall. The average search time fell by 20 percent, so employees now locate needed documents in minutes instead of hours. Deploying the solution on Runiti’s own GPU infrastructure in a regional cloud removes data‑leakage risk and fixes expenses; the company no longer pays licensing fees to third‑party AI platforms. An isolated environment has become a non‑negotiable requirement for any organization handling confidential information. In the pilot, the team replaced a bulky "universal" solution with four specialized agents, simplifying scaling and accelerating the addition of new data sources. Technically, everything runs on a GPU server using in‑house models and API integrations with corporate systems, allowing rapid adaptation of the assistant to evolving business needs without extra per‑request charges. This means you can free up hundreds of person‑hours each month, translate that time into millions of rubles saved, and eliminate unpredictable cloud spend while safeguarding sensitive data. Why this matters: A 20 percent reduction in search latency unlocks significant productivity gains today. Autonomous infrastructure gives you budget certainty and removes the security exposure of public AI services. You can scale the assistant internally without paying per query, keeping costs flat as demand grows.