Built for teams turning LLM usage into measurable savings. Read the API docs

LLM optimization gateway

KillToken™

The optimization control plane for LLM traffic.

Put one governed layer between your app and the model providers. KillToken™ measures waste, reduces safe repetition, accelerates repeat work with Redis-ready response reuse, and turns every request into tenant-level savings intelligence.

Open the dashboard Explore the funnel Developer docs

Savings Funnel

AI requests go in. Waste comes out.

KillToken™ watches the flow, applies conservative controls, reuses safe repeats, and turns request data into proof teams can act on.

App traffic Prompt load Repeat work Spend signals KillToken control plane Lower provider spend Faster repeat calls Savings proof

Savings Simulator

Estimate your token waste

A quick, directional estimate of monthly token spend and what KillToken could reclaim with exact-cache reuse and safe prompt optimization. It runs against public pricing — no signup, no provider calls, nothing stored. These are projections; verified savings come only from real gateway traffic.

Cost intelligence

Separate projected savings from verified savings.

KillToken™ reports baseline cost, actual cost, estimated savings, verified savings, and pricing source separately so finance and engineering are not reading one blended number.

  • Baseline vs. actual spend by request
  • Pricing profile source and model attribution
  • Null-safe verified savings when usage or pricing is unknown
Savings over time tenant view
estimated verified actual cost

Token efficiency

Track prompt weight before and after optimization.

The dashboard surfaces raw input estimate, optimized input estimate, provider input, provider output, and skipped-optimization reasons so teams can see where prompt weight lives.

  • Raw vs. optimized input token estimates
  • Provider-reported usage when available
  • Quality-risk visibility for safe mode
Token stack raw -> optimized
support summary agent run report raw input optimized input

Cache performance

Show speed and savings from repeat-safe traffic.

Cache status, exact-cache savings, and latency are tracked on the request timeline so teams can see where repeat work is actually saving money and time.

  • Hit, miss, skipped, and not-configured status
  • Latency trend by hour or day
  • Exact-cache savings kept distinct from other savings
Hit rate / latency last 7 buckets
cache hit volume latency trend

ROI proof

Turn usage traces into boardroom language.

ROI reports keep estimated, verified, potential, and cache savings distinct, so technical operators and business owners can discuss the same data without hand-waving.

  • CSV request exports for audit trails
  • Analytics JSON for finance dashboards
  • Tenant pricing profiles for contract-specific math
MetricSourcePeriodUse
Verified savingsprovider usagedailyactual ROI Potential savingssafe estimatedailynext action Exact-cache savingsrepeat workhourlylatency + cost Template opportunitytemplate matchweeklyprompt governance

Credibility signals

Proof that turns LLM usage into action.

Measure

See request volume, token load, spend, and latency by tenant.

Reduce

Find low-risk prompt waste and focus optimization where it is safe.

Reuse

Let repeat-safe workloads benefit from Redis-ready response reuse.

Prove

Export traces and ROI reports finance and engineering can share.

Platform

One control layer for AI traffic.

KillToken™ brings savings, speed, governance, and proof into one product surface for teams running LLM features in production.

Savings analytics

Cards, charts, request traces, and exports that make LLM spend visible by tenant.

Redis-speed repeat work

A production-ready path for repeat-safe responses without exposing cache internals on the public page.

Tenant access controls

Dashboard-minted keys, revocation, session auth, and tenant-scoped views.

Provider passthrough

Model generation stays with your own provider — OpenAI, Anthropic, Gemini, Mistral, DeepSeek, OpenRouter, Together AI, Perplexity, or xAI — while KillToken™ measures the traffic around it.

Developers

Ship with a straightforward gateway API.

Start in measurement mode, route server-side traffic through KillToken™, then turn on safe optimization and response reuse where it fits the workload.

API docs Quickstart
Minimal backend call
curl http://localhost:3000/v1/chat \
  -H "Authorization: Bearer kt_..." \
  -H "Content-Type: application/json" \
  -d '{ "provider":"openai",
       "model":"gpt-4.1",
       "optimizationMode":"measure_only",
       "messages":[...] }'

Trust posture

Built for tenant-safe operations.

KillToken™ keeps prompt content private by default, scopes controls by tenant, and preserves provider output so teams can route production traffic with confidence.

No raw prompt storage by default

Metrics and traces are useful without making prompt content public.

Tenant-scoped controls

Keys, dashboard data, exports, and analytics stay scoped to the logged-in tenant.

Provider output stays intact

KillToken™ measures and optimizes around the call; it does not rewrite the model response.

Ready to see the savings surface?

Open the dashboard, mint a key, and watch requests become measurable.

Open Dashboard System status