The operations system for dependable AI agents

Deploy, evaluate, and govern every agent run from one calm workspace. Now live Agent control center
Arrakis control room
DEMO / PREVIEW
Renewal review / weekly RUN-4821
04 / 18

Renewal review

Summarize account movement, surface unusual risk, and prepare a recommendation for the account team.

Run timeline
Context loaded
CRM history and account notes attached
Signals evaluated
18 records checked against renewal policy
Draft prepared
Recommendation and supporting evidence ready
Human review requested
Policy requires an account owner sign-off
Trace preserved. Every tool call, source record, and policy decision is available before approval.
Product teams Operations Developers AI teams Platform teams Support Finance Security

A calmer operating layer for AI agents. Bring context, controls, and human review into one shared system for dependable agent work.

FIG 01 / TRACE Trace planes

Trace-ready by default

Follow each run from prompt to outcome. Keep its evidence in reach.

FIG 02 / WORKERS Coordinated rings

Human-led automation

Give agents room to act, with clear points for human review.

FIG 03 / MOMENTUM Unfolding momentum

Built for operating speed

Bring scattered agent work into one shared operating system.

01 / Operate

Intake and agent operations

Turn incoming signals into routed, labeled, and prioritized work. Arrakis keeps the queue moving while your team decides where judgment matters.

01.0Route signals
Operations board / active signals SYNCED 09:44:12
Unsorted08
Usage spike in workspace 18 Signal · 4 minutes ago needs context
Contract note missing owner Signal · 12 minutes ago
Evaluating03
Renewal recommendation Arrakis Analyst · 2 minutes ago human gate
Expansion risk summary Arrakis Scout · 18 minutes ago
Ready11
Weekly account digest Approved · 24 minutes ago scheduled
Support theme report Approved · 31 minutes ago
Signal queue 12 OPEN
MA
Mara

Can we have Arrakis check the unusual usage pattern before the account call?

routed to review
TO
Tomas

The renewal summary is missing two source links. Keep the draft, but pause sending.

approval required
LI
Lina

Everything else looks clean. Add the workspace owner to the final notification.

@arrakis route this as high priority and assign it to me
Send
routing policy active
02 / Plan

Shape the work before it runs

Plan agent programs with product milestones, policies, and clear owners. Keep dependencies visible before they become incidents.

02.0Map the system
SEP OCT NOV DEC JAN
Agent programs
Renewal intelligence94
Signal foundation27
Decision quality18
Mobile approvals06
Regional rollout21
Voice of customer09
1815222961320274
Evidence pass
source coverage
Workspace pilot
internal pilot
Approval design
policy review
Quality baseline
evaluation set
03 / Build

Move work with agents

Delegate 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 worker
arrakis-runner / staging / activity.log
$ preparing worker environment
loading policy pack: account-review-v3
checking connector scopes
retrieving evaluation set / 120 examples
planning tool sequence
waiting for a human checkpoint...

trace: 9f4a-22c7-18b1
policy: outbound-message requires approval
Available workers 5 READY
RA Arrakis Analyst agent
AS Atlas Scout agent
BQ Beacon Query agent
QT Quarry Triage agent
TD Tide Drafting agent
connected Beacon CRM Quarry DB Tide mail
04 / Review

Review decisions before release

See what changed, why the worker changed it, and which evidence supports the result. Discuss, revise, and approve without leaving the run.

04.0Inspect output
arrakis-policies / renewal / recommendation.ts
Arrakis / latest trace
01import { review } from "arrakis"
02import { account } from "./context"
03const summary = await review(account)
04 
05if (summary.confidence > 0.8) {
06  sendRecommendation(summary)
07}
08 
09return summary.text
10 
11export default renewalWorker
12 
13// output is ready for review
01import { review } from "arrakis"
02import { account } from "./context"
03const trace = await review(account)
04 
05if (trace.confidence > 0.8) {
06  await requestApproval(trace)
07}
08 
09return trace.withEvidence()
10 
11export default renewalWorker
12 
13// approval is required before delivery
05 / Govern

Know what your agents learn

Take the guesswork out of quality with evaluations, scorecards, and security evidence that show what needs attention before scale makes it expensive.

05.0Monitor quality
Run quality ALL WORKERS
100806040200
Analyst
Scout
Triage
Evaluation scorecard Review
Renewal review / latest batch
Grounded recommendations Evidence matched to account context
96%
Safe tool behavior Scope and approval checks passed
99%
Useful handoffs Clear next action for the owner
93%
Trace completeness Sources and decisions preserved
100%
Review controls · scoped credentials · exportable audit trail

Arrakis field notes

Approval gates

Pause high-impact actions until the right person has reviewed the evidence.

Scoped connectors

Give each worker only the systems and permissions its task actually needs.

Replayable traces

Re-run a decision against new context without losing the original path.

Evaluation studio

Compare workers against the same examples before promoting a new version.

See the full operating record

See what each agent did, follow the evidence, and bring a person into the decision when it matters.

Keep decisions visibleHuman review at the right moment

Start with a focused workflow. Review the outcome, adjust the controls, and build from what you learn.

Build with clear boundariesA deliberate path from trial to routine
Explore a practical operating model for AI agents. Explore the workflow

Make every agent run a trusted one.

Explore a focused workflow for your team.

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