Pricing for production OpenAI teams
CachePilot is the governed execution layer for BYOK teams running production OpenAI workflows. It sits between application logic and the OpenAI Responses API to control cost, latency, output budgets, tool access, cache hygiene, policy receipts, and hash-first telemetry.
Governed-vs-passthrough comparison
In a governed-vs-passthrough comparison, prefix accuracy improved from 7.4% to 82.6%, p95 latency dropped from 16,210 ms to 8,872 ms, and estimated cost dropped from $0.2368 to $0.1820.
Comparison data, not a customer guarantee. Pilot results depend on request structure, model, traffic mix, and policy choices.
Start with one workflow
The goal is a clear technical decision: whether CachePilot can reduce execution risk across cost, latency, policy, and auditability for one real workflow.
Diagnostic
A technical teardown of one production OpenAI workflow to identify cost, latency, cache hygiene, policy, and auditability risks.
Pilot
Run baseline traffic against a governed path and measure what changes before committing production routes.
Production
Route production OpenAI workflows through CachePilot with deployment guidance, policy controls, telemetry, and founder support.
Engagement path
Map cost, latency, cache hygiene, retry, tool, and policy risks in one workflow.
Compare baseline behavior against a governed gateway path with receipts and telemetry.
Route approved workflows through CachePilot with support, policy controls, and rollout guidance.
Extend governance into broader AI execution control across teams and workflows.
Developer evaluation
A low-volume developer evaluation can help confirm routing, receipts, and basic telemetry. Production buyers should start with the teardown or pilot so governance, security, and rollout constraints are scoped correctly.
Request a technical review
Share enough context to qualify the teardown, pilot, or production deployment conversation. The first call should focus on your current OpenAI path, routing constraints, and what a governed comparison would need to measure.
FAQ
No prompt or output storage by default. CachePilot is designed around hash-first telemetry: policy hashes, request fingerprints, token usage, latency, status, and receipts. Custom retention requirements are scoped during pilot planning.
No. CachePilot sits between your application logic and the OpenAI Responses API. The pilot usually starts with one workflow so your team can compare baseline behavior against a governed gateway path before routing more traffic.
Yes. CachePilot supports BYOK flows where your application supplies the OpenAI key while CachePilot applies project policy, receipts, and telemetry around the request.
The pilot measures baseline versus governed behavior for cost, latency, output budgets, cache hygiene, tool access, policy receipts, and drift visibility. The goal is to prove whether governance reduces waste and operational ambiguity for a real workflow.
Most pilots start with one workflow and a narrow routing change. Timing depends on your OpenAI path, security review, BYOK requirements, and the workflow selected for comparison.
No. Cache hygiene is one part of the system. CachePilot is the governed execution layer for production OpenAI workflows: output budgets, tool controls, policy receipts, drift detection, latency and cost telemetry, and auditable request structure all matter.
Next step