The enterprise-grade control plane for AI. Control what your AI is allowed to do, and prove every decision it makes.
On-prem. Deterministic. Versioned and replayable.
When a customer, an auditor, or a regulator disputes a decision months later, can you replay exactly what happened - on the policy that was live at the time?
Swiftward™ is the control plane that lets you answer yes. You write your policy as versioned code, test it against real traffic before it goes live, and replay any past decision on the exact version that was in force. It runs on your infrastructure; nothing leaves your environment.
Every decision your AI makes runs through one engine, on a policy you version like code. You choose how each call is made:
- A deterministic rule - fast, exact, and replayable to the same verdict and record hash, every time.
- A model's judgment - defer the call to a model where nuance matters; the input and output are recorded.
- A human in the loop - route flagged calls to a reviewer, with the workflow and screens built in.
The engine is deterministic, so the decisions you build that way reproduce exactly. You do not reconstruct a disputed decision from logs and memory - you replay it.
+-----------------------------------------------------------------------+
| Config / white-label / embeddable UI everything declarative |
+-----------------------------------------------------------------------+
| Rules packs & gateways LLM | MCP | network | FIX | SCM |
+-----------------------------------------------------------------------+
| Three directions, one engine |
| AI Governance Trust & Safety Risk & Compliance |
+-----------------------------------------------------------------------+
| Swiftward engine |
| versioning | replay | shadow | A/B | rollback | HITL | DLQ | evidence |
+-----------------------------------------------------------------------+
| Enterprise foundation |
| on-prem | SSO | RBAC / ABAC / field-level | audit | multi-tenant |
+-----------------------------------------------------------------------+
You are not buying a point tool. You are buying the engine every team shares.
- AI Governance - control what your AI agents do: which tools they call, what data they touch, what actions they take. Prompt-injection defense, source-code and PII leak prevention, a human in the loop for the calls that matter.
- Risk & Compliance - enforce limits, approvals, velocity, and pre-trade checks on the decisions your AI makes, and replay any one of them for an examiner.
- Trust & Safety - moderate content with versioned policy, change it without a deploy, and replay any disputed takedown on the version that was live.
- Deterministic and replayable - every decision is recorded and provable, and a decision built from deterministic rules replays exactly, not approximately (where a rule defers to a model or a human, the trace records exactly what happened).
- On-prem - it runs in your environment; nothing leaves it.
- Policy as versioned code - a draft, candidate, frozen, archived lifecycle; deploy a set of policies and roll the deployment back in one click.
- Shadow mode and A/B - test a change against live traffic with no effect applied, and backtest it against your recorded traffic before you enforce.
- Enterprise foundation, day one - SSO, layered access control, multi-tenancy, secrets, a tamper-evident audit trail. Built in, not bolted on.
See a policy, end to end for one real rule that reads and writes state in a single pass.
| Section | What's inside |
|---|---|
| Overview | What Swiftward is, the three pillars, the one-engine story |
| Platform | The engine, evidence & audit, the enterprise foundation, human-in-the-loop, gateways |
| Solutions | AI governance, risk & compliance, trust & safety, and the use cases under each |
| Standards | EU AI Act, NIST AI RMF, SR 26-2, the PMI AI standard - how Swiftward maps to each |
| Resources | The AI Control Maturity Model, the Decision System Map, the prompt-injection guide, agent architectures |
| Compare | Build-vs-buy against OPA, LiteLLM, NVIDIA NeMo Guardrails, and others |
Early stage, working with the first design partners, and looking for 1-2 more: direct founder access, real use cases, honest feedback. The engine works today; production hardening is ongoing. We are honest on the site about what is shipped versus what we stand up fast for a pilot.
Book a 30-minute call - we will figure out if there is a fit.
This is the public documentation for Swiftward. Swiftward is a self-hosted product under a commercial license; the engine source is not public. For the full picture, the screens, and a working demo on your own use case, book a call.
Built by Konstantin Trunin, who ran this same declarative architecture - a high-load logistics platform - in production for years, and is building it a second time, for policy. Konstantin on LinkedIn.