How to track costs and optimize AI agent performance locally

How to track costs and optimize AI agent performance locally

This task can be performed using AgentLens

See your AI agent's future before it fails.

Best product for this task

AgentL

AgentLens

dev-tools

AgentLens is an open-source debugging toolkit for AI agents that enables offline recording, replay, failure analysis, and cost tracking. Built for developers who need efficient, local-first debugging without consuming API credits.

hero-img

What to expect from an ideal product

  1. Record all agent interactions and API calls locally so you can analyze costs without burning through credits during debugging sessions
  2. Track token usage and expenses across different models and providers in real-time while your agents run offline
  3. Replay failed agent runs to identify where costs spike or performance drops without making new API requests
  4. Set up cost monitoring dashboards that work entirely on your machine to catch expensive operations before they drain your budget
  5. Compare performance metrics between different agent configurations using historical data stored locally on your system

More topics related to AgentLens

Featured Today

seojuice
seojuice-logo

Scale globally with less complexity

With Paddle as your Merchant of Record

Compliance? Handled

New country? Done

Local pricing? One click

Payment methods? Tick

Weekly Product & Deals