High-performing agentic AI for enterprise workflows

We provide custom contextual evaluations, fine-tuning, and monitoring for agentic AI to work seamlessly in 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 combines human expertise with advanced AI to evaluate and train agents that deliver real-world value

Challenges

Performance and ROI

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

Evaluation Gaps

Agents are rarely tested against real procedures, edge cases, or compliance requirements and once deployed, they are left without ongoing evaluation.

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

Contextual evaluations built on real workflows

We design evaluations that reflect how AI agents are actually used in production, grounded in real tasks, decisions, and success criteria instead of generic benchmarks.

Expert-level human influence

Domain experts evaluate agent outputs in realistic scenarios to surface reasoning gaps, edge-case failures, and risky behavior that automated tests do not catch.

Data-driven improvement loops

Evaluation results feed directly into targeted data generation, fine-tuning, and ongoing monitoring so agent performance improves and stays reliable over time.

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.