Grounded retrieval
Use RAG for narrative evidence and typed knowledge graphs for exact entities and relationships.
For platform and security teams
Enterprise AI agents: grounded, self-hosted, accountable.
Move beyond demo-ware with an agent runtime designed around data control, exact retrieval, scoped tools, authenticated context, and visible execution.
Production requirements
What enterprise AI agents need to reach users
Security boundaries
Scope tools per agent, forward identity, and require confirmation for consequential operations.
Data residency
Self-host the Go runtime, PostgreSQL, and model configuration inside your environment.
Operational evidence
Trace structured run events, review audit data, and monitor runtime health.
Reliability
Grounded AI agents: answers from your records, not guesswork
The market is full of AI that looks impressive in a demo and then makes things up in front of a customer. SyntheticBrew grounds answers in your data: a knowledge-graph taxonomy gives the agent typed, deterministic retrieval, and RAG covers your documents. The agent answers from your records — and can be instructed to refuse when the evidence is missing.
For done-for-you builds, an eval harness scores every answer for groundedness and correct citation on your real data before launch — reliability you can measure.
Governance
AI agent governance: audit logs, scoped keys, security zones
Know what every agent did, and limit what each one can do.
Immutable audit log
Every administrative action is recorded — who changed what and when — for security, compliance, and governance reviews.
Least-privilege API keys
Scope keys to exactly what each integration needs: chat, tasks, agents, config, or admin. Revoke any key instantly.
Tool security zones
Tools are tiered by risk. Dangerous actions require explicit confirmation, and agents see only the tools they are configured for.
Secure by default
Secure AI agents: identity, keys, and billing you never have to babysit
Tamper-proof auth
Every API request is verified against an Ed25519-signed token. Forged tokens, downgrade attacks, and replay attempts are rejected at the door.
Zero secret management
No passwords, no rotating shared keys, no .env to leak. Self-hosted runs out of the box; plug in your existing IdP with one public key.
Bring your own LLM keys
Pass per-customer LLM API keys via request headers — used once, never stored, never logged. Clean per-tenant billing without vendor lock-in.
No double-billing, ever
If usage tracking cannot reach the cloud, requests stop — instead of silently double-counting later. Your invoice always matches reality.
Control plane
Separate what users can do from what operators manage
Optional two-port mode splits the runtime into an external data plane — the chat and agent APIs your product calls — and an internal admin plane carrying the dashboard and management APIs, which you keep behind a VPN or firewall.
- External data plane for chat and agent APIs
- Internal admin plane behind your VPN or firewall
- Ed25519-signed JWT authentication
- Scoped API keys and BYOK
- Per-agent tool access with confirmation boundaries
Verifiable up front
Open-source enterprise AI you can vet before you commit
The runtime your agents run on is open source. Your engineers can read it, run it, and stress-test it before a contract is signed — proof it is production-grade, not a surprise at handover. Most enterprise AI vendors are a black box until then.
Questions
Enterprise AI agents: common questions
What makes an AI agent "enterprise-grade"?
Reliability and control. The agent must be grounded in your data, auditable, scoped to least privilege, and deployable on infrastructure you control. SyntheticBrew is built in Go as a single production binary with those properties built in — not a prototyping toolkit.
How do you keep enterprise AI agents grounded instead of guessing?
Grounding. Knowledge graphs give the agent typed, deterministic retrieval over your real records, and RAG covers unstructured documents. You can also instruct the agent to say "I don't know" rather than guess. For done-for-you builds, an eval harness scores every answer for groundedness and correct citation before launch.
Can we keep our data on our own infrastructure?
Yes. SyntheticBrew is self-hosted — deploy with Docker Compose, Kubernetes using Helm, or a standalone binary alongside PostgreSQL, on-premise or in your private cloud, with your own LLM keys. Your data and conversations never leave your environment.
Do you offer a done-for-you build?
Yes. We deliver a production agent in your platform to a measured bar — accepted against evals on your real data — then hand it over for you to run. Fixed scope, fixed price, no lock-in. Book a fit call to scope it.
Evaluate the exact runtime you will operate.
The engine is open source, so your team can inspect and test the system before a production decision.