Building Better AI Agents
Starts With Better Data
We specialize in training and benchmark data for LLMs and VLMs. We build tools for human and agentic annotation and develop methods to assess, synthesize, calibrate, and repair datasets.
The Problem
BEHAVIOUR
AI behaviour is inherited from data
Even a small share of defective examples in training data can measurably change a model’s behaviour.
COST
Dataset defects are cheap when caught early, but very expensive when caught late
Finding a defect in a dataset can cost orders of magnitude less than diagnosing the same defect in a trained model.
COMPLIANCE
Regulations are catching up to data problems
Article 10 of the EU AI Act now requires training, validation, and testing data to be relevant, representative, and free of errors.
The Solution
DETECT
Detect defects before any training
Bias, anomalies, incoherence, and more, caught in the dataset before a model can learn them. We attack the problem from several sides at once: statistical analysis over the distribution, deep learning models built for bias detection, and a panel of LLMs that reads the examples.
FIX
Fix what is broken, fill what is missing
Fine-tuned agents, kept inside guardrails, repair defective examples and generate the ones a dataset lacks. A panel of LLMs validates what they produce before any of it goes back in.
DOCUMENT
Logs and reports that satisfy compliance
Every check and every repair is logged. The reports say what the data holds, what changed, and why — the record Article 10 asks you to keep.
Curate fine-tuning data from your own experts in a workflow-optimized, research-driven annotation tool built for LLM and VLM data. Go to the annotation platform →
Built on Years of Research & Applied AI Work
Calibrion is developed by PhDs in NLP and computer vision, with decades of combined experience in applied AI and research: training pipelines, data curation, and evaluation systems built for AI labs and enterprises.
Need help building with the data? We design and deploy post-training pipelines, agentic systems, RAG, and custom evaluators. See AI engineering services →