- Security / compliance — did governance controls actually run on this request?
- Finance — what did it cost, and is the number trustworthy?
- Effectiveness — did this governed spend produce accepted work?
The core problem
Most teams deploying AI at scale stitch together a gateway + observability tool + guardrail service + FinOps tool + productivity tool to get four separate, after-the-fact views of the same request. Each sits outside the request path, producing dashboards that lag reality and logs that only describe what allegedly happened — none of them enforces anything, and none of them can prove it. Wardin sits in the request path. That means:- Budgets are enforced before a token is spent, not discovered in a report
- PII is redacted before it leaves your network
- Policies (model allowlist, injection detection) block non-compliant calls at the source
- Every enforcement decision, cost, and actor is signed into one hash-chained receipt — not logged separately and reconciled later
- Every request is attributed to a team, user, and session, so governed spend can be tied to accepted work
How it works
You point your existing SDK athttps://gw.wardin.ai instead of
https://api.anthropic.com. No client code changes. Signing and chaining happen in an
asynchronous writer, off the response path — a receipt adds zero latency to your
request. See Signed Receipts for how the chain works.
Wardin produces audit-grade, Art-12-style runtime records for gateway-routed
traffic — not a compliance certification. No software makes an organization
“compliant,” and Wardin doesn’t hold (or confer) SOC 2, ISO 27001, or HIPAA. Receipts
today are verifiable over the hot analytics window (7–30 days). Framework-mapped
control citations, the one-click Evidence Bundle export, and the offline verifier
(spec published; reference CLI, public release in preparation) are shipped today;
long-term WORM retention beyond the hot window is still in development — see
The Evidence Layer for what’s shipped versus roadmap.
Key concepts
The Evidence Layer
The organizing idea: enforce, meter, sign, and attribute converge into one receipt, read by three audiences.
The Request Path
The six-stage rail — the mechanism that produces the evidence layer on every request.
Virtual Keys
Scoped API keys that proxy to your real provider credentials — with per-key budgets, rate limits, and policies.
Budgets
Hard spending limits enforced via Redis atomic counters before a request is forwarded.
Policies
Model allowlists, prompt injection detection, PII redaction — enforced in-path.
Caching
L1 exact-match and L2 semantic caching reduce spend without changing your prompts.
Sessions
Requests grouped into sessions so cost-per-task is a real metric — built for agentic clients.
Signed Receipts
Every model-inference request emits an ED25519-signed, hash-chained receipt — tamper-evident audit evidence.