We turn your prototypes into production-grade systems
We build AI applications that handle lease abstraction, COI verification, and document processing—with source citations and human-in-the-loop review.
Our Evaluation Framework
Every AI application passes through three layers of validation before reaching production
Systematic Quality Measurement
Quantitative scores and structured reports track performance across your pipeline
Application-specific evaluations
Application-specific assessments measure what actually matters for your use case
Error Analysis and Continuous Monitoring
Automated guardrails catch drift and block bad outputs before they reach users
All Our Applications Pass Rigorous Evaluations
Evaluations are the foundation of reliable AI systems—measuring quality, catching errors, and enabling continuous improvement
Systematic Quality Measurements
Systematic measurements of quality in an LLM pipeline—producing quantitative scores or structured reports that help teams understand how well their AI application is performing.
Error Detection & Improvement
Tools for catching errors and enabling improvement—used as background monitors to detect drift, as guardrails to block bad outputs, or to label data for fine-tuning and identify failure cases.
Application-Specific Assessments
Application-specific assessments that measure what actually matters for your use case (like helpfulness or format adherence), rather than relying on generic benchmarks that may not reflect your requirements.
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