MergeLoom

About MergeLoom

MergeLoom turns approved tickets into review-ready pull and merge requests, positioning itself as a delivery system around coding agents rather than another coding agent. Work starts where it already lives — Jira, Linear, GitHub, GitLab, Azure DevOps or Monday.dev — and the run ends at a PR or MR that a human still has to review, with PR/MR review mandatory by design and audit trails on every run. The differentiating piece is the Context Engine, which maps the wider system, service links, docs and rules before the run starts, so the agent is not inferring architecture from whichever repo happens to be open; the product calls out cross-repo awareness and impact analysis before edits as the concrete outputs. Quality Agents gate the run and review the result, and a self-learning loop feeds rejected PRs, failed validations and Review Agent findings back into the next run so the same rejection is not paid for twice. Agent Fleets are scoped rather than free-running: you set the mandate, restrict which repos and files are in play, and cap both spend and the number of open PRs. Models are bring-your-own, covering OpenAI, Claude and private models, so an approved model path can be kept intact. Pricing is explicitly not per-seat — the stated model is cost per outcome — and there is a free entry point plus a booked demo.

Key Features

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