Trace-ready by default
Follow each run from prompt to outcome. Keep its evidence in reach.
A calmer operating layer for AI agents. Bring context, controls, and human review into one shared system for dependable agent work.
Turn incoming signals into routed, labeled, and prioritized work. Arrakis keeps the queue moving while your team decides where judgment matters.
01.0Route signalsPlan agent programs with product milestones, policies, and clear owners. Keep dependencies visible before they become incidents.
02.0Map the systemDelegate repeatable work to purpose-built workers, connect the systems they need, and keep a human close to the moments that carry risk.
03.0Deploy a workerSee what changed, why the worker changed it, and which evidence supports the result. Discuss, revise, and approve without leaving the run.
04.0Inspect outputimport { review } from "arrakis"import { account } from "./context"const summary = await review(account) if (summary.confidence > 0.8) { sendRecommendation(summary)} return summary.text export default renewalWorker // output is ready for reviewimport { review } from "arrakis"import { account } from "./context"const trace = await review(account) if (trace.confidence > 0.8) { await requestApproval(trace)} return trace.withEvidence() export default renewalWorker // approval is required before deliveryTake the guesswork out of quality with evaluations, scorecards, and security evidence that show what needs attention before scale makes it expensive.
05.0Monitor qualityPause high-impact actions until the right person has reviewed the evidence.
Give each worker only the systems and permissions its task actually needs.
Re-run a decision against new context without losing the original path.
Compare workers against the same examples before promoting a new version.
Explore a focused workflow for your team.