Endform raises €1.5M to speed up testing and reduce CI load in the era of AI-generated code

Swedish startup Endform has raised €1.5M in seed funding to tackle one of the most frustrating problems in modern development: waiting in CI pipelines. Against the backdrop of the AI code generation boom, this delay becomes more pronounced — teams can write and change code faster and faster, but verification increasingly can't keep pace.

CI Bottleneck

Endform's idea is built on a simple reality: in development, the slowdown isn't code writing itself, but the time between a commit and confirmation that all tests have passed.

When a company accelerates feature releases, the volume of automated checks grows too. Add AI tools that help developers produce more changes in the same timeframe, and the CI queue quickly becomes a constant source of idle time.

The team has seemingly already completed the work, but the release actually hinges on waiting for a green status. This problem isn't new, but now it's becoming more expensive. If a slow pipeline used to merely frustrate teams, it now directly eats into gains from AI coding.

Code generation shortens the time to pull request, but doesn't eliminate the risk of breakages, regressions, and flaky tests. As a result, the bottleneck simply shifts: instead of a shortage of engineering time, companies face a shortage of validation speed. This is precisely the gap Endform is trying to fill.

"Code review has always had a bottleneck — not the code itself, but

the waiting."

Betting on Tests

Endform is a Swedish startup in the testing segment, and the €1.5M raised should help it attack the bottleneck at the CI process level.

From the published description, it's clear the company isn't betting on another code generator, but on an infrastructure layer around it: on what happens after code is written and before it reaches production. This is a less visible part of development, but this is where time is lost, especially in teams with large numbers of automated tests.

Looking at the core pain points, teams expect quite specific results from such solutions:

• shorten test run time without losing coverage
• prioritize the most important checks for each change
• find flaky and duplicate tests faster
• reduce rerun counts and wasted waiting time
• return feedback to developers closer to the moment of code writing

This is why even a relatively modest seed round looks timely. In infrastructure products, value often emerges not from flashy marketing, but from consistently eliminating delays that every team feels daily. If Endform can prove it reduces waiting time without compromising quality, it will have a clear pitch for CTOs and engineering managers: the same engineering staff starts delivering results faster.

Why Now

The round size isn't huge by infrastructure market standards, but it's logical for an early-stage company: the problem is clear, the market is only intensifying, and the effect of the solution is easy to measure in hours of waiting, engineer costs, and release speed.

The more aggressively companies deploy AI assistants in IDEs and code generation, the starker the contrast becomes between fast code creation and slow verification loops.

For teams, this is no longer an abstract optimization, but an economics question. If each pull request waits longer in the queue, context switches increase, reviews stall, and developers either split changes into smaller pieces or accumulate them into larger batches. Both scenarios hurt release predictability.

This is why tools that speed up the testing and CI layer have a chance to become a mandatory part of AI-first development, rather than a niche DevOps add-on.

What This Means

Endform is trying to profit not from the hype around AI code, but from its side effect — an overloaded change verification system. If the startup can indeed reduce CI waiting time without sacrificing quality, the winners won't just be test teams, but the entire development cycle from PR to release.