High performing agentic AI,  fine-tuned for enterprise workflows

We design, fine-tune, and evaluate agentic AI that works seamlessly for any use case

AI agents are only as intelligent as the data that shapes them.

To make reliable decisions, they need more than massive datasets—they need context, judgment, and domain expertise.

micro1's human data engine combines human expertise with advanced AI to train agents that think, decide, and perform with human-level judgment to deliver real-world value.

Challenges

Limited data capacity

Even when budget and intent are available, enterprises lack internal capacity - in both people and data readiness - to implement and sustain AI agents.

Performance and ROI

Models hallucinate, behave unpredictably, and do not offer a reliable method to demonstrate ROI for agents.

Trust and compliance remain a black box

Usage of AI systems are often opaque with unclear compliance risks, making it difficult to trust them and safely scale their use.

micro1's solution

End-to-end, white-glove development

We’ll adapt to your unique requirements and handle agent development end-to-end: from recruiting top domain experts for model fine-tuning and evals, to deploying production-ready systems that learn and improve over time.

Catch failures and pinpoint ROI

We set up real-world evaluation environments around your workflows where agents are stress-tested against live scenarios. Weak outputs, hallucinations, and risky behaviors are surfaced and fixed long before they reach customers.

Bulletproof, multi-layered QA

Every dataset goes through multiple layers of review, from expert validation to manager oversight and automated checks. Quality is reinforced at every stage to ensure outputs are complete, accurate, and aligned with client standards.

How it works

Define

Workflows, policies, and edge cases are translated into a structured blueprint so the agent understands not just what to do, but how your organization does it.

Evaluate

Agents are stress-tested with domain-expert evaluations, judgment-rich scenarios, and failure-mode checks to measure reasoning, reliability, and workflow execution.

Refine

Performance improves through targeted fine-tuning data, updated evaluations, and human-in-the-loop corrections, ensuring the agent stays aligned with your standards over time.