New Provisioned capacity routing. Reserved throughput routing across multiple providers.

AI inference
tailored to
your use case.

Run AI at the quality, speed and cost your product needs. EVO optimizes your inference setup and manages the capacity behind it.

Backed by

Make your AI work better

Find the right model

Compare models against your own quality, latency and cost targets.

Improve every request

Test prompts, context, tools and cascades to get more from each model call.

Prove what works

Evaluate changes on your own workloads before moving production traffic.

Get competitive pricing

We source competing bids for your workload. You get one offer from EVO.

Secure your capacity

Arrange throughput around your traffic, concurrency and latency needs.

Keep delivery in check

EVO checks performance against your agreement and arranges backup supply.

How EVO
Works

A loop that re-checks as models and prices change.

  1. 1

    Measure your workload

    EVO reads your prompts, traces and traffic to learn each model call's token mix, latency needs and peak demand.

  2. 2

    Set the bar from your traffic

    Evals come from your own production outputs.

  3. 3

    Test setups and source capacity

    Models, prompts and cascades are scored against your baseline. Providers bid on the throughput you need.

  4. 4

    Route to reserved capacity

    Traffic runs on committed throughput across providers, on one contract.

  5. 5

    Keep delivery in check

    Delivery is tracked against the agreement, with redundancy for failures.

Without EVO

  • The model was picked once and never revisited
  • Capacity is bought from one provider at list price
  • Peak traffic runs into rate limits
  • One provider outage takes your product down

With EVO

  • Every workload is re-checked as new models ship
  • Providers compete for your throughput, on one contract
  • Reserved capacity is sized to your peaks
  • Backup supply takes over when a provider falls short

Plugs into your whole stack

EVO slots in next to your gateway. It does not replace it and does not do load balancing.

Reads from

  • GitHub
  • Langfuse
  • Maxim
  • Datadog
  • Braintrust

+ traces, logs, observability

Runs through

  • Bifrost
  • LiteLLM
  • Portkey
  • Helicone
  • OpenRouter

+ any OpenAI- or Anthropic-compatible gateway

Routes to

  • Anthropic
  • OpenAI
  • Google
  • DeepSeek
  • Qwen
  • Together
  • Baseten
  • Modal
  • AWS
  • Azure

+ your own endpoints and on-prem

Request capacity →

What does your AI
need to do better?

Bring one use case. Let’s work through quality, cost and capacity together.

Discuss your use case