AI Engineering
AI engineering is our core discipline. We build the models, pipelines, and infrastructure that power intelligent products. Custom training and fine-tuning for your domain. Evaluation frameworks that catch problems before users do. Production infrastructure with monitoring, drift detection, and automatic retraining. This isn’t AI that works in a demo — it’s AI that works at 3am on a Tuesday when nobody’s watching.
What you get
Real examples
Document classification
Fine-tuned classification models for domain-specific document triage — legal, financial, or operational — replacing manual sorting with consistent, auditable AI.
Predictive maintenance
ML pipelines over sensor data that predict equipment issues before they happen, enabling proactive maintenance and reducing unplanned downtime.
Common questions
When should we fine-tune vs use prompting?
Start with prompting and RAG — it’s cheaper and faster. Fine-tune when you need consistent domain-specific behaviour, lower latency, or cost reduction at scale. We’ll advise which approach fits your use case.
What’s your approach to AI evaluation?
Automated eval suites that test accuracy, latency, cost, and safety across hundreds of test cases. Every model change runs through evaluation before deployment. No ‘looks good to me’ releases.
How do you handle AI safety?
Guardrails from day one — content filtering, output validation, PII detection, bias testing, and human-in-the-loop for high-stakes decisions. Responsible AI isn’t optional in our practice.
Can you work with our existing data?
Yes. We work with structured databases, document stores, API data, sensor feeds, and unstructured text. Our assessment identifies what’s usable, what needs cleaning, and what gaps exist.
Do we own the models?
Yes. Custom models, fine-tunes, evaluation suites, and infrastructure code — you own everything. No platform fees, no vendor lock-in.
Ready to get started?
Tell us about your project and we'll tell you honestly how we can help.
Get in Touch