GitLab Orbit, Now Generally Available, Makes AI Agents More Accurate and Less Expensive to Run

Ryan Harvey, Head of AI engineering, Compare the Market

“What GitLab Orbit gave us was something we'd been chasing for a while: the knowledge graph that backs an AI code reviewer that actually understands our codebase, not just the diff in front of it”

Ryan Harvey, Head of AI engineering, Compare the Market

“We tested it against retrieval-augmented generation and a few other approaches across real merge requests, and the gap was clear: better comment placement, better summaries of what actually changed.”

Ryan Harvey, Head of AI engineering, Compare the Market

“RAG, which we'd assumed would be the natural solution, ended up performing worse than no context at all.”

Ryan Harvey, Head of AI engineering, Compare the Market

“For us, that result spoke for itself.”

Arnal Dayaratna, Research vice president, software development, IDC

“As organizations extend AI agents beyond code generation into the rest of software delivery, the quality of the context those agents work from matters as much as the models themselves,”

Arnal Dayaratna, Research vice president, software development, IDC

“Because GitLab already captures data across the software lifecycle, it is positioned to give agents a more complete view of how software is built and delivered, which can help organizations improve results and better manage the cost of AI at scale.”

Manav Khurana, Chief product and marketing officer, GitLab

“AI agents are only as accurate and efficient as the context they work from.”

Manav Khurana, Chief product and marketing officer, GitLab

“Orbit gives every agent in the governed software factory the full record of how an organization builds and ships software, so teams make decisions they can trust, keep spend predictable, and answer questions they never could before.”