Five industries. One platform. Your data never leaves your infrastructure.
Every one of these started as a generic model that hallucinated on domain questions. Fine-tuning on your own data is what closed the gap.
Deflect 60% of tickets. Resolve the rest in seconds.
Fine-tune an open-weights LLM on your product docs, past tickets, and FAQs. Deploy a support agent that understands your brand voice, handles complex queries, and escalates intelligently — all without sending customer data to third-party APIs.
A code assistant that knows your codebase, not just Python.
Train a coding LLM on your internal repositories, architecture docs, coding standards, and proprietary SDKs. Get an assistant that suggests code following your conventions, understands your domain models, and never leaks trade secrets to external APIs.
Clinical-grade AI. Runs inside your own environment.
Deploy fine-tuned medical LLMs for clinical documentation, diagnostic support, patient communication, and EHR data extraction — with full HIPAA compliance and zero PHI sent to external APIs.
Compliant AI for regulated financial workflows.
Fine-tune LLMs on your financial data — earnings reports, regulatory filings, risk models, and customer communications — with full data residency control, PII guardrails, and audit-ready logging.
AI that reads contracts so your lawyers don't have to.
Fine-tune models on your specific contract types, legal jurisdiction, and firm's clause library. Build AI that extracts obligations, flags risks, and answers questions about legal documents — with citations, not hallucinations.
Product discovery that understands intent, not keywords.
Fine-tune on your catalogue, past search sessions, and return reasons to build search, recommendations, and product copy that speak your customers' language. Runs on your own infrastructure, so basket data and margins stay yours.
Tutors that teach your curriculum, not the open internet.
Fine-tune on your syllabus, marking rubrics and past student work to build tutors, graders and study tools that stay inside the material you actually teach — with student records kept on infrastructure you control.
Decades of maintenance logs, finally searchable.
Fine-tune on equipment manuals, maintenance history, SOPs and shift handover notes to build assistants that answer plant-floor questions in your own terminology — deployable air-gapped, with no dependency on an external API.
Reproducible experiments, not a folder of notebooks.
Fine-tune and evaluate open-weights models against your own benchmarks with every run versioned, every hyperparameter recorded and every checkpoint exportable. Built for teams that have to defend a result, not just demo one.
The platform is domain-agnostic — these are just the patterns we see most. Tell us what you're building and we'll map it out with you.