Governed Docker containers.
Every Loop run executes inside a dedicated Docker container with network limits, file system limits, and no persistent state. Your code is isolated from the agent and from every other tenant.
Releezy Loop
Releezy Loop puts AI coding agents to work on your backlog — inside isolated containers, under hard spending limits, with an audit trail and a human review queue on every run. Every execution lands on the Guardian scoreboard alongside your humans.
Loop is not another AI agent builder. It is the governance layer your team needs to put AI coding tools into production without losing visibility, spend control, or the ability to roll back.
Schedule a demoThe product
Runs stream in live with status, model, tokens, and cost. Hard limits stop a runaway agent before the invoice does — and every action lands in the audit log.
Releezy Loop — runs with live status and per-run cost.
Most teams do not fail at AI because the tools are bad. They fail because nobody built the controls to run the tools safely.
Every Loop run executes inside a dedicated Docker container with network limits, file system limits, and no persistent state. Your code is isolated from the agent and from every other tenant.
Hard caps on token spend per run, per project, per tenant. When the limit hits, the run stops. No surprises on the invoice.
Every agent action is an audit event in a structured log. When something goes wrong, you know exactly what happened and when.
No agent merges without review. Loop routes every output into a queue where humans decide. The queue has backpressure, so agents cannot flood your team.
On identical benchmarks, the same model performs dramatically differently depending on the scaffold around it. Loop is the scaffold.
The same Claude Opus 4.5 scored 42% on a public benchmark (CORE-Bench) with one scaffold and 95% with another. The model is the commodity. The harness is the difference.
Anthropic engineering (Kapoor), SWE-Bench Claude Code (2026)
Loop does not build AI coding tools. Loop orchestrates the best ones. When Claude 5, GPT-6, or the next frontier model ships, every Loop customer gets the upgrade automatically. You are long the capability curve, not short it.
Loop is not just a runner. Every execution feeds Guardian's measurement loop, and every Guardian signal flows back into the agent's context on the next run. Your project history, your review standards, your team's accumulated patterns — all of it shapes what the agent sees before it writes a single line. The loop closes on itself, and every run gets smarter than the last.
A 30-minute demo on your repository. Your agents will run under Loop in governed containers.
Schedule a demoReleezy Suite
The scoreboard.
Discover the truth about who writes and who reviews code on your team — human or AI. No guessing. No surprises on your next deploy.
Open GuardianThe governed harness.
Picture your senior engineers back to architecture, while AI agents handle the repetitive work — under governance, audit, and spend control.
Open LoopThe customized code reviewer.
A code reviewer that already knows your project rules — measured shoulder to shoulder with your humans from the first comment.
Open ReviewerThe discovery agent.
First, the right problem. Then, the code. The discovery agent turns real user signal into a backlog worth building.
Open PlanAgentic-readiness assessment.
Advisor runs a deep, multi-agent analysis of any repository and scores how ready it is for AI-agent work — then turns every gap into an actionable issue.
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