Drop-in OpenAI-compatible gateway that prunes and shapes prompts, routes smarter with confidence fallback, and enforces per-tenant budgets—backed by request-level diffs and reason codes. No hidden LLM calls.
Built for AI-native CX vendors running high-volume traffic: measurable savings, audit-ready governance, and safe rollouts.
Remove low-value turns and payload bloat. Emit a prompt diff + input token delta.
Cap over-generation and enforce formats (JSON/schema). Track output token delta with reason codes.
Shadow mode first. Enforce only when quality proxies hold. Roll back instantly if regressions appear.
We're building the MVP with design partners. If you run high-volume CX AI traffic and care about cost-per-conversation + governance, reach out.
[ PROOF ]
Every claim outputs an artifact: diffs, deltas, eval status, fallback events, and weekly savings reports.
Metric: pass / block / rollback
Metric: complexity → model step + fallback
Repeatable intents + structured outputs = fast wins without risking customer experience.
Aggressive context pruning + output shaping for speed. Fallback if uncertainty spikes.
Semantic cache + difficulty routing. Strong models reserved for hard queries.
Route classification to cheap/fast models; enforce strict JSON outputs.
Shadow → eval gate → staged rollout with versioned policies and audit logs.
Per-tenant caps and “budget prevented” events when usage spikes.
Rate-limit detection + provider failover with explicit controls.
OpenAI-compatible. Base URL swap. No hidden LLM calls. Reason codes on every request.
We measure cost-per-conversation, p95 latency impact, and quality proxy stability before enforcing anything.
Request logs, cost + tokens + latency
Prune + shape + routing policies
Private deployment options