TKM-AI helps teams optimize and deploy LLM-based agents — cutting latency and cost while keeping quality high. From prototype to production.
Illustrative estimate based on typical workloads — your numbers will vary.
Support all agents
Claude Code
Codex
Cursor
Antigravity
DeepSeek
Gemini CLI
OpenClaw
Copilot
Claude Code
Codex
Cursor
Antigravity
DeepSeek
Gemini CLI
OpenClaw
CopilotOne platform to optimize, deploy, and observe LLM-based agents — so your team ships quality without burning budget.
Compress prompts, cache aggressively, and trim wasted tokens automatically — without touching your agent logic.
Push an agent and we autoscale it across regions with sub-second cold starts. No infra to babysit.
Trace every step, score quality with custom evals, and catch regressions before they reach a user.
Route each request to the right model by cost, latency, and capability — and fail over automatically.
Bring the agent you already have. We handle the rest of the path to scale.
Wrap your existing LLM calls with our SDK, or import from LangChain and LlamaIndex in a few lines.
TKM-AI profiles every run, then compresses, caches, and routes to keep quality up and cost down.
Ship to autoscaling infra with one command and watch traces, costs, and evals in real time.
TKM-AI exists to make LLM-based agents cheaper, faster, and more reliable to run — so teams can move from prototype to production with confidence. We focus on the unglamorous parts: latency, cost, and reliability under real traffic.
Every optimization is measured against quality, not just price — so you never trade accuracy for a lower bill.
Tracing, evaluations, and automatic failover are built in from day one, not bolted on later.
Route across providers and models. You're never locked into a single vendor.
A drop-in SDK and clean APIs that fit the stack and workflow you already have.
Tell us about your agents and we'll show you where the wins are.