Backed by Y Combinator

Continuous Learning for Production AI.

Measure and improve your AI's performance
across your workflows.

Most agents stall at "good enough."

Off-the-shelf models rarely hit the right balance of:

Latency

Response times spike unpredictably under real-world conditions

Quality

Outputs drift from acceptable to unpredictable without warning

Business Rules

Alignment with your domain logic breaks on edge cases

Tool & API Usage

Reliable function calling remains fragile at scale

In production, "good enough" is a liability. Your agents should be your advantage.

Your agent should improve over time.

At Carrot Labs, we work closely with you to improve the metrics you care about.

Build a Realistic Evaluation Environment

A production-like testing environment you own. Real inputs. Real tool calls. Real constraints.

Measure What Matters

Latency, correctness, tool success rate, business-aligned quality metrics. No vibes. No cherry-picked demos.

Optimize, Train & Deploy

We improve performance using the right lever:

  • Prompt and routing changes
  • Retrieval improvements
  • Tool policy refinement
  • Fine-tuning when it's justified

Continuous Learning

Our platform continuously evaluates and retrains as needed, so your agent stays aligned even as your data drifts, new models are released, and your workflows evolve.

See the difference on a real workflow.

Our fine-tuned model delivers performance gain.

43%
Median latency reduction
18%
Quality improvement from baseline

For teams already shipping AI.

This is for you if you run:

  • AI-powered SaaS products
  • Internal agents using proprietary APIs
  • Workflow automation systems
  • Tool-using copilots in production

Not for:

  • Experimental chatbots
  • "We just want to try AI"
  • One-off prompt consulting

We focus on agents that matter to your business.

Bring us your worst-performing workflow.

We show you where it fails, what to fix, and what better looks like.