Fine-tuned models, retrieval-augmented pipelines, and purpose-built AI that understands your terminology, your edge cases, and your data — not just the internet.
Off-the-shelf LLMs are general. Your business isn't. We build the layer that makes AI specific to you.
Train base models on your proprietary data — internal docs, historical decisions, product knowledge — so the model behaves the way your experts do.
Retrieval-Augmented Generation pipelines that ground every LLM response in your source-of-truth documents — reducing hallucination and enabling citation.
Systematic eval frameworks that measure what actually matters: accuracy on your task, regression from model updates, and edge-case failure rates.
Structured, searchable AI knowledge systems built from your unstructured content — manuals, case notes, emails — queryable by AI and humans alike.
Custom KYC model that extracted and validated investor data from complex fund documents at scale.
Domain-specific model trained on carrier policy language to classify and route claims without human review.
RAG pipeline that locates and categorises contract clauses across thousands of documents per hour.
General models are impressive. But when the task is specific — your terminology, your formats, your risk tolerance — a purpose-built model pays for itself immediately.
Discuss your use caseContracts, briefs, and discovery documents — extracted and flagged with attorney-level precision.
ICD codes, SOAP notes, and clinical documentation — processed accurately without provider bottlenecks.
Fund summaries, earnings analysis, and compliance reports — generated from structured data at volume.
Spec sheets, datasheets, and product descriptions — accurate, on-brand, and generated at catalogue scale.
Tell us what the off-the-shelf model gets wrong. We'll scope a custom solution — fine-tune, RAG, or hybrid — and show you what accuracy looks like on your actual task.