Continue with AI
Bring governance to live AI traffic.
Add AI to existing systems, support flows, and internal operations without exposing the records, secrets, and context that make production environments harder to trust.
Live telemetry
policy decisions
24,819
sensitive fields redacted
1,482
runtime latency overhead
0.02s
Provider stream
[ingest] request captured from support workflow
[policy] live-production profile applied
[redact] email and case reference tokenized
[route] approved provider lane selected
[trace] governance record stored
Runtime path
Put governance in the live request path, not in a slide deck.
This page should feel like interception and control. The point is to make the runtime path visible enough that engineering, platform, and security can all trust it.
Live system call
Support tools, internal software, and customer operations keep their current integration path.
Inline governance
Spendplane applies redaction, routing policy, provider choice, and budget rules before egress.
Traced model execution
Approved traffic reaches the model with a reviewable trail of what changed and why.
Incident timeline
Make a live request look inspectable, not mysterious.
Spendplane turns production AI calls into an inspectable pipeline. Requests move through redaction, policy decisions, and routing constraints before they ever cross the boundary.
Request intercepted
Spendplane identifies a live support workflow and assigns the correct policy profile.
Sensitive fields tokenized
Email, case references, and internal identifiers are replaced before the provider sees them.
Route selected
The request is sent to the approved model lane with budget and provider constraints enforced.
Trace stored
Security and platform teams get a usable record of the request path, not just a success message.
Before vs after the boundary
customer_email: stefan.kilo@gbc.com
case_id: GOV-4421
request: summarize this complaint and draft a response
api_key: sk-proj-live-...
customer_email: [EMAIL_1]
case_id: [CASE_REF_1]
request: summarize this complaint and draft a response
api_key: [SECRET_1]
Common protected categories
- Dates of birth, contact details, and regulated personal records
- Internal project codes, employee references, and client case information
- API keys, tokens, and secrets copied into support or engineering workflows
Governance signals
- Detection and redaction events per request
- Shared policy decisions for every provider call
- Governance traces that support audits and change reviews
Developers and ops
- Add AI to existing services without rewriting everything around provider-specific logic.
- Keep one runtime path for live requests, fallback behavior, and redaction decisions.
Platform teams
- Centralize routing, provider policy, and spend attribution across software that is already in production.
- Make AI traffic visible to engineering instead of hiding it inside each application team.
Security and compliance
- Turn live AI traffic into something reviewable, enforceable, and auditable before data leaves the environment.
- Reduce the risk of secrets, identifiers, or case records crossing the wrong boundary.
Enterprise readiness
Add AI to live systems without giving up the audit and control story.
Mature buyers want more than a protected request. They want evidence that policies, routing, and provider boundaries can survive security review, compliance review, and rollout across teams.