Pnyx provides an OpenAI‑compatible routing layer that automatically selects the most cost‑effective and performant large language model for each request across multiple providers. By continuously evaluating prompts against models, it offers real‑time cost attribution, policy‑based routing, and audit trails without requiring code changes, monetizing through usage‑based fees for the routing service.
Funding
Funding not disclosed
Founders
Product
Problem
Enterprise AI applications often route every LLM inference request to a single provider’s model, leading to unnecessary spend, limited performance insight, and difficulty enforcing compliance or cost‑control policies. Teams must manually manage multiple vendor APIs, handle rate‑limit failures, and lack a unified audit trail for model usage. This fragmented approach hampers scalability and obscures budgeting for production workloads.
Solution
Pnyx delivers an autonomous decision layer that intercepts LLM inference calls and dynamically selects the optimal model across major providers (OpenAI, Anthropic, Google, AWS, Microsoft, Mistral, Meta, Cohere) based on real‑time performance metrics, cost, and configurable policy rules. The platform exposes a single OpenAI‑compatible endpoint, so existing codebases and orchestration tools (LangChain, LlamaIndex, Semantic Kernel) require no changes. Continuous evaluation of each model’s quality, latency, and price informs routing decisions, while built‑in cost attribution, budget caps, and allow‑list controls enforce financial and compliance governance. Automatic failover and rate‑limit handling ensure high availability, and audit logs provide traceability for every request. Users can upload production prompts to benchmark models, run A/B tests, and activate routing policies without redeploying services.
Target Audience
The primary customers are enterprise AI platform teams, engineering leaders, and DevOps groups that deploy production LLM workloads and need centralized cost control, compliance, and high‑availability routing.
Features
- OpenAI‑compatible API gateway that aggregates access to all supported LLM providers.
- Real‑time cross‑provider routing engine powered by continuous model evaluation (quality, speed, cost).
- Policy engine with budget caps, model allow‑lists, and compliance rule enforcement per team or use case.
- Full cost attribution and per‑agent usage tracking, enabling granular spend reporting and chargeback.
- Automatic failover and provider‑level rate‑limit management to maintain service continuity.
- Integration adapters for LangChain, LlamaIndex, Semantic Kernel, and any standard HTTP client.
- Live leaderboard visualizing model performance metrics updated every minute from production data.
- Audit‑trail logging for every inference request, supporting security and regulatory audits.