Agents · For Engineers

Already have an agent?
Bring it. We'll govern it.

Connect your existing agent — LangChain, CrewAI, AutoGen, or raw REST — via a single adapter endpoint. Orchestrik wraps it with the full governance layer: audit trail, credential vault, tenant isolation, connector access. Your logic stays untouched.

REST / WebhookAdapter interface
ZeroChanges to your agent logic
FullAudit trail from day one
AnyFramework supported

Works with any HTTP-callable agent, including

LC
LangChain
CA
CrewAI
AG
AutoGen
LI
LlamaIndex
</>
Custom REST
WH
Webhook
The problem

What every custom agent is missing — and has to rebuild from scratch

Your agent has no audit trail

It ran. It did something. Somewhere in a log file there might be a record of what. When a compliance team asks what your agent did to a customer record last Tuesday, you can't answer cleanly.

Credentials live in environment variables

Database URLs, API keys, service tokens — hardcoded or in .env files, passed directly into agent prompts. No rotation, no access policy, no audit of who used what.

No tenant isolation

Your agent runs in one process and sees all data. There's no boundary between what agent A is allowed to see versus agent B, or between customer X's data and customer Y's.

Governance is an afterthought bolted on top

Rate limiting here, a try/catch there, some logging middleware if you remembered. Every agent reinvents the same layer — inconsistently. One agent has it; the next one doesn't.

How it works

One integration point. The full infrastructure layer.

01

Connect your agent via REST or webhook

Your agent exposes an endpoint or listens on a webhook. Orchestrik calls it with the task payload — or receives the event — through a typed adapter. No SDK to install. No framework to change. One integration point.

Adapter spec: documented OpenAPI schema; test endpoint provided for validation
02

Orchestrik wraps the invocation

When a task is dispatched to your agent, Orchestrik handles the infrastructure layer: credential injection from the vault, connector bindings, tenant context, memory scope, resource limits. Your agent receives the task payload. It never touches a raw secret.

Your agent receives: task payload + resolved context. Not: raw credentials.
03

Your agent runs — unchanged

Your agent executes its logic exactly as it always has. LangChain, CrewAI, AutoGen, a custom Python script, a Node.js service — it doesn't matter. Orchestrik doesn't inspect or modify your agent's internal logic.

Supported: any HTTP-callable agent; async patterns (polling, callbacks) supported
04

Full trace written automatically

Every invocation — the input, the connector calls your agent made through the Orchestrik layer, the output, the duration, the outcome — is captured as a structured trace. Your agent gets an audit trail without writing a single logging line.

Trace: immutable, append-only, same schema as all other Orchestrik agents
What you get

The infrastructure layer your agent is missing

Credential vault access

Your agent accesses secrets by name through the vault API. No credentials in prompts, no env vars, no rotation downtime.

35+ native connectors

Your agent can call Zendesk, Salesforce, ServiceNow, PostgreSQL, or any other connector in the library — without managing those integrations itself.

Tenant isolation

Each agent invocation runs in a scoped context. Data boundaries enforced at the platform layer, not in your agent code.

Structured audit trace

Full invocation trace written automatically. No logging code required in your agent.

Resource governance

CPU, memory, and wall-clock limits set at deployment time. Enforced by the runtime — your agent can't exceed them accidentally.

Retry and failure policy

Retry with backoff, dead letter queuing, and escalation paths configured in the control plane. Your agent just returns a result or an error.

What stays exactly the same

Your agent logic is not touched.

Orchestrik wraps the invocation context — it doesn't inspect, modify, or instrument your agent's internal code. If you want to update your agent logic, you deploy it the same way you always have. The adapter stays constant.

You keep control of

  • Your agent's code, language, and framework
  • Your deployment pipeline and CI/CD
  • Your prompt engineering and model choice — including in-house or self-hosted LLMs
  • Your agent's update and release cadence
  • Where your agent runs (your infra or ours)

Bring your agent to the demo

We'll connect it to the adapter endpoint live. You'll see the credential vault injection, the connector call, and the audit trace it produces — from your actual agent, not a demo agent.