AI that works.
Not just impresses.
We build practical AI — LLM integrations, intelligent automation, and data pipelines that cut costs, save hours, and create real competitive advantages. No buzzwords. No demos that never ship.
AI solutions that ship to production
We don't build proofs of concept that gather dust. Every engagement ends with something live, measurable, and owned by your team.
Real applications across your sector
AI isn't one-size-fits-all. Here's how we apply it differently across the industries we know deeply.
FinTech
- Fraud detection & transaction anomaly alerts
- AI-powered KYC document verification
- Automated loan underwriting scoring
- Natural language expense categorisation
Healthcare
- Clinical note summarisation & auto-coding
- Patient triage chatbots with symptom assessment
- Medical document Q&A for staff portals
- Appointment no-show prediction
EdTech
- Personalised learning path recommendations
- AI tutors with subject-matter guardrails
- Automated essay grading & feedback
- Content generation for course creators
eCommerce & Logistics
- Product recommendation engines
- Demand forecasting & inventory optimisation
- AI-generated product descriptions at scale
- Route optimisation for delivery fleets
Tools we use in production
How we build AI that actually works
Most AI projects fail at handoff. We design for production from day one — with evaluation, guardrails, and observability built in.
Use Case Discovery
We map your operations to identify where AI creates the highest ROI — focusing on tasks that are repetitive, data-rich, and currently time-consuming. We rule out bad AI fits early so you don't waste budget.
1 weekStakeholder interviewsROI mappingData & Feasibility Assessment
We audit your existing data, assess quality and volume, and evaluate which AI approach — fine-tuning, RAG, prompt engineering, or classical ML — fits best. Honest feasibility before any build commitment.
Data auditModel selectionPrivacy reviewPrototype & Evaluate
A working prototype with real evaluation metrics — accuracy, latency, cost per call, hallucination rate. You see it working on your actual data before we write production code.
2–3 weeksEval frameworkBenchmark testingProduction Build
We build the full system — API layer, guardrails, fallback logic, logging, and observability. Integrated into your existing product or deployed as a standalone service.
3–8 weeksCI/CDMonitoringRate limitingLaunch, Monitor & Iterate
We track real-world performance, cost, and user behaviour post-launch. AI systems degrade without maintenance — we set up the feedback loops that keep yours improving.
OngoingA/B testingPrompt tuningWe build AI that ships, not just slides
Outcome-first thinking
We start with the business problem, not the technology. If AI isn't the right answer, we'll tell you — and suggest what is.
Privacy by design
Data privacy is baked into every AI system we build. Private endpoints, on-premise options, and GDPR-aware pipelines as standard.
Full-stack capability
We handle the entire stack — AI model, backend API, frontend UI, and infrastructure. No coordination between multiple vendors.
Evaluation-driven builds
Every AI system we ship has measurable benchmarks — accuracy, cost per query, latency, and fallback rates. You know exactly how it's performing.
Cost-aware architecture
LLM API costs can spiral without proper architecture. We design caching, batching, and model-routing strategies that keep your AI economics healthy.
Knowledge transfer
We document everything and train your team. You own the system fully — prompts, pipelines, infrastructure — and can maintain it independently after launch.
AI questions, answered honestly
Ready to add real AI to your product?
Tell us what you're trying to automate or build. We'll respond within 24 hours with a clear, practical plan — no jargon, no overselling.