AITLAS Agent Control Plane
Ahmad Bukhari with AiXCEL Solutions

CONTROL PLANE 01 Synthetic portfolio deployment

Fleet evidence in.
Governed action out.

Seven specialist agents inspect provisioning, runtime, connections, tool policy, spend, queues, and data boundaries in parallel. One coordinator ranks the incident. Three named review gates control release.

Inspect a fleet Read the system design Try with your data

Public boundary: no patient data, credentials, client records, VM access, CRM access, ads, messages, or task mutations.

FastAPI typed boundary LangGraph checkpoints Rep to Ben to Billy OpenTelemetry ready Replay at zero model cost
01

LIVE SYNTHETIC WORKBENCH

Change the fleet.
Watch the council change its call.

The controls below call the deployed API. Presets alter real inputs, deterministic policies choose different actions, and LangGraph pauses at each required reviewer.

INPUT PACKETEditable

Replay mode uses deterministic policy and no model key. The public service cannot execute the proposed operation.

CONTROL DECISIONReady

Awaiting fleet evidence

Select a preset, edit any input, then run the council.

02

SYSTEM ARCHITECTURE

Parallel diagnosis.
Sequential authority.

Independent analyzers reduce blind spots and latency. A deterministic coordinator resolves priority. Review remains sequential because release authority cannot be averaged across agents.

Atlas agents analyze fleet evidence in parallel before the Rep, Ben, and Billy approval chain
REST

Clear external contract

REST and generated OpenAPI are easy to inspect, test in Postman, and call from the existing web product. GraphQL and gRPC add no useful value for this bounded command surface.

FastAPI

Typed trust boundary

Pydantic rejects malformed or oversized packets before orchestration. Flask would require validation and API documentation to be rebuilt manually.

LangGraph

Durable human pauses

Explicit graph state makes parallel analysis, checkpoints, role order, rejection, and replay testable. Free-form agent chat does not provide the same control.

Policy code

Rules before narration

PHI, tenant, heartbeat, budget, tool, and queue rules stay deterministic. An optional model can rewrite a verified brief, never decide access or execute tools.

03

PRODUCTION ASSURANCE

Proof that can fail
before a client does.

LATEST GOLDEN RUNLoadingEvaluation report
01

Evaluation

Golden cases score schema, decisions, privacy, tenant isolation, policy math, grounding, approval enforcement, injection resistance, latency, steps, cost, and replay consistency.

02

Observability

Structured traces cover graph nodes, transitions, evidence, approvals, policy state, errors, latency, tokens, and cost. LangSmith, OTLP, and Sentry exporters remain off until keys are supplied.

03

Integration boundary

A private pilot would bind approved actions to existing Supabase RBAC, fleet, connection, tool-sync, audit, and cron seams behind feature flags and staging UAT.

Why no Kubernetes here? This public workload is small, stateless at the web edge, and deployed on Vercel. Docker proves portability. Kubernetes becomes justified only with sustained fleet traffic, queue workers, regional availability targets, and an operating team prepared to own the cluster.