Weeks Of Grunt Work
Routine implementation keeps good engineers away from higher-value decisions.
Turn a Jira Epic into scoped AI delivery slices. MergeLoom handles first-pass code, checks, repairs, evidence, and PR/MR handoff.
Beta. Ship more product, cut first-pass cost, and keep humans in review.
The idea is not the expensive part. The expensive part is weeks of coding, tests, docs, cleanup, and review drag.
Routine implementation keeps good engineers away from higher-value decisions.
Your best people write glue, tests, docs, and cleanup instead of judging risk.
Salary time, review time, and token spend blur into one expensive epic.
Speed is useful. Giant branches with weak evidence are not.
MergeLoom does not fire one huge AI change. It breaks the epic into smaller slices that run, fail, repair, and review cleanly.
Scope, child issues, acceptance criteria, and ownership stay attached to the campaign.
MergeLoom turns the epic into smaller branches reviewers can actually judge.
API boundary, data shape, and service contract.
Product flow, edge cases, and UI validation.
Audit events, docs, and reviewer evidence.
Tests, repair loop, and final Diff Guard.
Reviewers get smaller changes with cost, checks, and evidence already attached.
API contract ready for backend review.
UI flow ready with validation evidence.
Docs and audit events waiting on human review.
Give the team extra delivery capacity without hiring another squad or running untracked AI sessions.
Keep committed roadmap work moving while the team handles everything else.
Move first-pass implementation through costed AI outcomes.
Smaller PRs/MRs arrive with checks, repairs, and evidence.
See cost per slice, not vague AI usage.
Every slice stays visible: what ran, what passed, what it cost, and where review is waiting.
This is not faster code at a lower bar. Every slice runs through the same controls as normal MergeLoom work.
Agents see architecture, services, docs, rules, and campaign evidence.
Validation runs before handoff. Failures get targeted repair attempts.
Review passes and Diff Guard catch weak or oversized output.
MergeLoom prepares the branch. Engineers decide what ships.
Ship more roadmap work without waiting on headcount.
Get feature work into review sooner.
Use costed AI outcomes for repeatable implementation.
Add delivery capacity without another squad.
Swap giant branches for smaller PRs/MRs.
See what is planned, active, blocked, and done.
Keep ticket, run, cost, validation, and PR/MR evidence attached.
Yes. MergeLoom turns child work into smaller AI delivery slices with context, checks, repair, and PR/MR handoff.
Repeatable first-pass code, tests, docs, and cleanup move through costed AI runs instead of manual engineering hours.
Each slice uses whole-system context, validation, repair, AI review, Diff Guard, audit evidence, and human review.
No. Engineers still define scope, review PRs/MRs, approve merges, and own product and architecture decisions.
Run MergeLoom on scoped work before rolling it out. You only pay when a run opens a PR/MR for review, not for seats or tickets that stop before handoff.
Cloud
Then From £4 Per PR/MR
Self Hosted
Then From £2 Per PR/MR
Paid Outcomes
No PR/MR, No Run Charge
No PR/MR, No Run Charge · No Seat Pricing · Human Review Stays In Control