
A Model of the AI-Native SDLC
Coding agents have collapsed the time it takes to write code, but delivery has not kept pace.
Read the whitepaper →Develocity encodes a decade of build and test expertise into a context engineering layer, with agents and engines that govern and accelerate software delivery.

Trusted by engineering teams at
Why now
Now the bottleneck is the toolchain itself. Develocity governs and accelerates delivery.
Attributing
AI ships machine-scale change with no accountable owner.
Gating
Manual policy gates can't keep pace with AI-scale change.
Iterating
Agent loops outpace the pipeline and multiply its cost.
Diagnosing
AI multiplies build failures and inefficiencies.
How it works
Unify build, test, and dependency signal scattered across every repo and toolchain, local and CI, in one place.
Turn raw signal into meaning — what failed, what's slow, what's inefficient — and why, and what it costs.
Serve that context via the IDE, Develocity Analytics, and MCP servers.
Universal coverage
Build systems, package managers, CI, repositories, IDEs. Wherever your software is built, across every region and team, Develocity sees it.

Coding agents have collapsed the time it takes to write code, but delivery has not kept pace.
Read the whitepaper →
No AI, however smart, can guarantee that a change breaks nothing that worked before. With agents making more changes, regression tests matter more, not less.
Read the post →
Anthropic proved test selection is mandatory at agentic volume, and what building it costs. You don't have to: Predictive Test Selection has you covered.
Read the post →
Organization-wide build optimization with Develocity Agents, observability for Docker builds, and Trusted Artifact Isolation for Universal Cache.
Read the release notes →Talk to us, or take a self-guided look at how it works.
Develocity comes from the creators of Gradle Build Tool, one of the world's most widely used build systems, with over 100 million monthly downloads.
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