Control infrastructure for agents in production

Moji runs each agentic workflow as priced, tracked steps inside a stateful runtime. Runs are held inside committed budget thresholds and acceptance criteria, with failed steps recovered in line.

Watch your agents operate inside a fixed budget

Connect one production service or repository.

Check the work where it is produced. Every step carries your acceptance criteria.

Your acceptance checks run on each step as it completes. A problem is caught at its source, with the run and its state still available to recover.

  • Checks from your own repository

    The quality bar is yours, defined by your own acceptance checks.

  • Pass or fail on every step

    Each step is verified in the path, while the rest of the work keeps moving.

  • Measured on the connected workflow

    Every verdict is captured with the step and run that produced it.

Your acceptance check, at every step
  • schema validretrieve
  • citations resolvedraft
  • totals reconcileverify
  • policy passpublish
4/4 passed · captured live on the dashboard
Triaged in line · the decision engine sizes the recovery
  • draftpassed
  • fact checkfailed · triagedpassed · attempt 2
  • publishin flight
only the failed step re-ran · the job kept moving

Failures fixed in place

When a step fails, the decision engine classifies the failure and sizes the recovery. Moji re-runs that step with the rest of the job's state intact.

  • Triaged in line

    The decision engine classifies the failure where it happened and sizes the recovery.

  • State stays intact

    Completed steps and evidence remain attached to the run.

  • Only the failed step is redone

    The job returns to the step that failed instead of starting again.

A budget set before the agents run

The quote is a priced multi-step structure. Each step has an assigned model and effort level, a predicted price and an acceptance check. The total becomes the job budget; a run that would exceed it is held with its state intact.

  • A spending cap per job

    Every model call is metered against it, down to the cached token.

  • Latency, tracked honestly

    Delivery time is reported at the 95th percentile, where the slow jobs live.

  • Your quality bar, written in

    The checks come from your own repository and apply to every job.

Every call metered · per step, under the cap
Cap $0.40 · recommended from your runs
Finished at $0.29, inside the cap

The evidence to expand autonomy. One report for the whole run.

The dashboard answers what ran, what it cost, what passed and what needs a decision. Each measure traces back to the line, step, item and attempt.

First-pass yield

Jobs finished correctly with no human help.

Exception rate

Jobs that needed a person, and at which step.

p95 cycle time

How long jobs take, measured at the slow end.

Budget reliability

Jobs delivered inside their cap.

Supervised first runsThe report builds confidenceAutonomous, passively monitored

Every workflow starts supervised. The team expands autonomy when the report supplies the evidence.

Connect one production workflow

The primary route connects a service or repository from the firm's AI stack. Teams can use the same controls for bounded work delegated through coding agents.

  • Your AI stackConnect one service or repository. Observe first, then put control in path where needed.
  • Your coding agentControl background jobs, schedules and repeated batches inside team rules.
  • Connection depthObserve measures and prices; Run in path adds live checks and recovery.

Cloud, VPC and SDK-only are deployment choices inside the firm route. They describe where the runtime sits, not a third way into the product.

Moji runtime deployment
Cloud

Moji operates the runtime.

VPC

The runtime is deployed in the customer's cloud account.

SDK-only

Controls run in the connected service. Model calls keep their existing provider path.

Your model calls are encrypted in transit and handled under a data processing agreement.

The controls are split across separate systems

Scored after the run

Evaluation platforms score finished work after the run. They do not hold the state needed to recover the failed step.

Capped at the key

Gateways meter calls and cap spend per key. They do not set and hold the budget for a whole multi-step job.

Retried blind

Workflow runtimes preserve execution state and retry errors. Output checks and the job budget usually live elsewhere.

Teams try to do bits and pieces of this manually. Moji holds the budget, the checks and the run state together while the work moves.

For teams operating multi-step AI work in production

The clearest fit is a workflow where inference is a material operating cost, a wrong result matters, and recovering one failed step is better than restarting the job.

Firm AI stack

Start with one production workflow and its acceptance criteria. The report shows whether its budget and quality thresholds held before the team expands the scope.

Coding-agent team

Use Moji for work handed off beyond an attended chat: background jobs, scheduled work and repeated batches. The agent keeps its own reasoning; Moji controls the budget, checks and recovery around the work.

Teams can expand autonomy when the connected workflow repeatedly holds its budget and quality thresholds.

Request early access

Moji is in early access with a small number of design partners. Leave your work email and, if you like, a line about the workflow you would hand off, and we will come to you.

team@mojisystems.com