When generic AI doesn't know your domain — we train one that does. On your data, your terminology, your cases, and your workflows. A legal AI that knows your firm's contract templates. A medical AI that understands your diagnostic protocols. Built, deployed, and owned entirely by you.
ChatGPT and standard AI tools don't know your specific jargon, your firm's precedents, your product catalogue quirks, or your proprietary processes. They hallucinate on domain-specific facts. They can't reason about your specific industry constraints.
Custom AI is trained on your actual data — so it understands your world precisely. It doesn't guess at your terminology. It doesn't confuse your firm's naming conventions with industry defaults. It answers the way your best expert would, because it learned from your best experts.
We build domain-specific AI models for industries where precision, compliance, and proprietary knowledge are non-negotiable. Here is what that looks like in practice.
Trained on your firm's contract templates, case history, and jurisdiction-specific regulations. Drafts, reviews, and flags issues like your best associate — without billable hours.
Understands your diagnostic protocols, formulary, and patient record structure. Assists with clinical notes, coding, and documentation — compliantly and accurately.
Trained on your product specs, fault history, and maintenance manuals. Diagnoses equipment issues and recommends corrective actions before downtime occurs.
Understands your credit policies, risk models, and regulatory requirements. Assists with underwriting, compliance checks, and report generation at scale.
Trained on your curriculum, assessments, and pedagogical approach. Personalises learning paths and generates contextually accurate content aligned to your standards.
Trained on your research corpus, datasets, and domain literature. Accelerates literature review, hypothesis generation, and data analysis with domain-level accuracy.
A structured, transparent process — from raw data to a deployed private model. No black boxes, no surprises. You see the accuracy numbers before we ship.
We work with you to collect, clean, and structure your proprietary data — documents, records, cases, transcripts, code, or any domain content. Data privacy and compliance handled from day one.
We select the right base model for your task — not always the biggest, efficiency matters — and fine-tune it on your data until it performs with domain-level accuracy.
Tested against real queries from your domain experts. We don't ship until it meets your accuracy requirements. Hallucination rate measured and minimised against your benchmarks.
Deployed on your servers, your cloud account, or our private infrastructure — never on shared public infrastructure. You retain the model weights and can run it independently forever.
Every custom AI engagement includes the full stack — from raw data engineering to deployment and monitoring. No hidden extras, no ongoing licensing.
Collection, cleaning, deduplication, and structuring of your training data — we handle all the data engineering so your data is ready for model training.
Custom fine-tuning on state-of-the-art base models using your domain data — not prompt engineering, actual model training that internalises your domain permanently.
Domain expert evaluation, hallucination testing, adversarial prompting — we find weaknesses before deployment so you don't discover them in production.
Deployed on your servers, your VPC, or air-gapped environment — model weights handed over to you completely. Your infrastructure, your control.
Custom API for your model so it integrates seamlessly with your existing applications, workflows, and internal tools without disrupting what's already working.
Model accuracy tracked over time. Retraining triggered when performance drifts from your baselines. Your AI stays current as your business and data evolves.
Your model, your infrastructure choice. We support fully air-gapped on-premise, private cloud, and hybrid deployments depending on your data classification and compliance requirements.
Model runs on your own servers. No external API calls. Fully air-gapped if required. Complete data sovereignty at every layer of the stack.
Best for: Legal, Healthcare, Defence, GovernmentModel deployed in your own AWS, Azure, or GCP account. You control the encryption keys. Scales automatically with demand. No shared tenancy.
Best for: Scale-ups, distributed teams, SaaSSensitive processing runs on-premise, non-sensitive workloads on cloud. Single unified interface — complexity is hidden from your users and teams.
Best for: Enterprises with mixed data classificationCustom AI is for organisations whose domain knowledge is too specific, too regulated, or too valuable to trust to a generic public model.
Contract AI, case research, document review, compliance checking — trained on your jurisdiction, your templates, your firm's specific precedents.
Clinical documentation, diagnostic assistance, coding automation, patient record analysis — HIPAA and DPDP compliant by design.
Fault diagnosis, maintenance intelligence, quality control AI, process optimisation — trained on your equipment, your specs, your failure history.
Credit AI, fraud detection, regulatory compliance, risk modelling — understands your policies, your portfolio, your regulatory environment.
Literature review, hypothesis testing, data analysis, grant writing assistance — trained on your research corpus and scientific domain.
Any business with 5+ years of domain data that generic AI simply cannot understand — your knowledge base is your competitive moat.
Everything you need to know before commissioning a custom AI model.
Prompting a general model is surface-level. Fine-tuning changes the model's actual weights based on your data — it internalises your domain knowledge permanently. The result is 10× more accurate on domain-specific tasks and doesn't require elaborate prompts to stay on topic. A prompted model forgets context between sessions; a fine-tuned model has your domain baked into it at the parameter level.
It depends on the complexity of the domain. We have achieved strong results with as few as 500 high-quality examples. More is better, but we will tell you honestly whether your dataset is sufficient before starting. We also help you generate synthetic training data from your existing documents when raw examples are limited.
You do. We hand over the model weights, training data pipeline, and deployment configuration at project completion. You can run it independently of us forever. There is no ongoing licensing fee, no lock-in to our infrastructure, and no dependency on our APIs. The model is a permanent asset of your organisation.
Yes. We build the training pipeline to be rerunnable. As your data grows and your business changes, we can retrain or fine-tune further to keep the model current. This is typically done annually or when significant accuracy drift is detected. The retraining cost is substantially lower than the initial training engagement.
If your domain has precise terminology, specific regulations, or proprietary processes that generic models get wrong — you need a model trained on your data. Let's talk about what that looks like for your organisation.