Finetuning

Fine-Tuned Evaluations for Smarter AI Decisions

Design flexible, multi-step pipelines using LLMs and Python scripts to measure performance with data-backed insights, not just intuition.

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Features

Calibrate with Confidence

Harness the best of human intuition and advanced algorithms to fine-tune models faster and smarter.

Enhance LLM evaluations by incorporating real-time human feedback to refine accuracy, trust, and transparency.

Collect granular scores and critiques to fine-tune metrics like hallucination detection.

Use minimal, targeted examples with LLM-as-a-judge to boost fidelity and relevance.

Combine human intuition with model intelligence for transparent, trustworthy evaluations.

Accelerate fine-tuning with fewer samples by converting user-driven scoring into powerful calibration signals.

Transform human assessments into robust signals that enhance LLM performance.

Reduce development cycles and costs while maintaining high evaluation quality.

Enable faster rollouts with continuous improvement backed by domain-specific insights.

Synthetic Data Generation

Custom Metrics