Ensure your fine-tuned models perform accurately and reliably by evaluating them against your own ground truth data. Gain deep insights, compare results, and optimize for real-world applications—seamlessly and at scale.
Empower subject matter experts to easily contribute insights, define ground truth, and give structured feedback—all in one place
Smart Data Labeling
Accelerate annotation by labeling documents in minutes. Capture SME feedback and apply them at scale for consistent, high-quality data.
Enhance LLM Accuracy
Identify errors in training data using built-in analysis tools. Rapidly iterate to enhance the accuracy and reliability of your LLM.
Why enterprises need robust LLM Evalutions
Enterprises rely on LLMs to drive critical decisions, but without robust evaluations, model performance can be unpredictable and misaligned with business goals. A strong evaluation framework ensures accuracy, fairness, and relevance by measuring models against real-world tasks and ground truth data. By continuously refining LLM evaluations, enterprises can mitigate risks, improve efficiency, and confidently deploy AI-driven solutions at scale.
Build smarter, accurate and more aligned models with LLM evaluations
advanced evaluation
Create Your Own Ground Truth Data
Label and create your own ground truth data to evaluate LLMs for multiple tasks such as RAG, Named Entity Recognition, Relation Extraction, Classification and more
Measure what truly matters by customizing evaluation metrics and benchmarks for your business. Ensure your models excel in specialized use cases with relevant, high-quality assessments.
Automate and streamline LLM evaluations to get faster, more precise, and reproducible results. Minimize errors, reduce manual effort, and make data-driven decisions with confidence.
Shorten the development cycle with rapid evaluation and feedback loops. Improve model performance with each iteration and deploy production-ready LLMs that meet your exact requirements.