The lifecycle
Build: author the checks
Everything downstream runs on artifacts you author from your own policies, regulations, and domain knowledge:- Datasets and rubrics in Evaluation define what good looks like before you build. See datasets and rubrics.
- Tasks and verifiers in Environments turn those definitions into scored, simulated episodes. Each environment bundles an app, backend, task definitions, and verifiers that score session and device state.
- Policies in the control plane encode which actions are consequential and what must hold before they execute, including latches that activate only on the action they govern. See policy authoring and verifier crafting.
- Domain writing from Expert Review: your invited specialists author scenarios and success criteria in their specialty, which feed the Environments task banks. See domain writing.
Gate: every change runs the suite
Before an agent change ships, it clears two kinds of pre-deployment checks:- Eval suites run against the Evaluation API and a threshold check fails the pipeline when scores regress. See CI/CD quality gates.
- Simulation runs in Environments score multi-step behavior in realistic, stateful apps: you call the eval API at
https://agi.akhara.ai, and each episode returns a terminal reward of+1,0, or-1plus a full trajectory. See scores and stats.
Run: the gateway verifies every step
At runtime, your agent passes through the Akhara gateway on every step. The PEP (an SDK in your runtime) intercepts inputs, model output, deliveries, and consequential tool calls, and asks the PDP athttps://api.akhara.dev for a verdict: ALLOW, WARN, BLOCK, or ESCALATE. On ALLOW for a consequential action, the PDP mints a one-time permit; downstream services should refuse to execute without one. The PDP decides and never executes tools itself, and enforcement is fail-closed by default.
Every verdict is written to an append-only evidence feed. You can seal a decision and later verify it, so audit does not depend on trusting the logs. See the control plane architecture for the full request lifecycle.
Learn: production feeds the next iteration
The evidence trail and captured trajectories close the loop:- Your org-invited specialists in Expert Review review agent runs: trajectories, scores, failures, and policy-sensitive cases the automated checks flagged or missed.
- Their findings tighten rubrics, tasks, and policies, which flow back into the build-time artifacts.
- The next CI run gates against the updated suites, so a regression that production surfaced is caught before it ships again.
What moves between products
For per-term definitions across the suite, see the glossary.

