AI & Automation Engineering.
We integrate AI into existing systems, from LLM-powered features to full workflow automation, with production-grade reliability and guardrails.
Quick Facts
AI demos are easy. Production AI systems are not.
The gap between a working prototype and a reliable production system is where most AI projects fail. We bridge that gap with engineering discipline.
Integration Complexity
Connecting LLMs to your existing data, APIs, and workflows requires careful orchestration and error handling.
Data Quality Issues
AI is only as good as its data. Most teams underestimate the work needed to clean, structure, and maintain training data.
Hallucination Risks
Uncontrolled AI outputs can damage trust and create liability. Production systems need validation, guardrails, and fallbacks.
Privacy & Security
Sending sensitive business data to third-party APIs requires careful architecture around data handling and compliance.
AI & automation capabilities.
From simple workflow automation to complex LLM integrations, we build AI systems that actually work in production.
Workflow Automation
Replace manual, repetitive processes with intelligent automation that adapts to edge cases and scales with your operations.
LLM Integration
Production-ready integrations with GPT-4, Claude, and open-source models, with proper prompt engineering, caching, and cost controls.
Predictive Analytics
Turn your historical data into actionable forecasts with custom ML models built for your specific business domain.
AI systems in production.
Real results from AI and automation systems we've built and deployed.
Built an LLM-powered document extraction system that processes invoices, contracts, and compliance forms with 97% accuracy, replacing 3 full-time data entry roles.
Read full case study →Deployed a RAG-powered support agent that handles L1 tickets using company knowledge base, escalating complex issues to human agents with full context.
Read full case study →Implemented an anomaly detection system that identifies production defects before they reach QA, using sensor data and historical defect patterns.
Read full case study →Technology Stack
We combine proven ML frameworks with modern LLM tooling, always prioritising reliability and cost efficiency over hype.
Transparent pricing.
AI development scoped to your automation goals and data readiness.
Every engagement is scoped individually after understanding your requirements. These ranges reflect typical projects we deliver.
Discovery & Assessment
$2K – $4KData audit, feasibility analysis, and a concrete proposal for what AI can (and can't) do for your specific use case.
AI Development
$8K – $20KEnd-to-end AI feature or automation system, from data pipeline to production deployment, with monitoring and guardrails.
Scale & Optimise
$20K – $50K+Multi-model orchestration, fine-tuning, advanced analytics, and ongoing AI system maintenance and improvement.
From data audit to
production AI.
Four phases. Clear deliverables at each stage.
Data & Feasibility Audit
Assess your data quality, identify automation opportunities, and determine what's achievable with current AI capabilities.
Prototype & Validate
Build a working prototype with real data to validate accuracy, latency, and cost before committing to full development.
Production Build
Engineer the full system with proper error handling, monitoring, caching, rate limiting, and fallback strategies.
Monitor & Improve
Track accuracy metrics, optimise costs, handle model updates, and continuously improve based on production feedback.
Let's add intelligence
to your systems.
30 minutes with a senior AI engineer to discuss feasibility, data readiness, and practical automation opportunities.