AI strategy
Don’t guess your way into AI. Engineer it. The reason that 95% of AI projects are failing is lack of clear strategy on how to get AI systems built.
Technology Stack & Architecture Decisions
We map your existing infrastructure, data systems, and team capabilities to recommend the right LLM providers, frameworks, and deployment patterns.
You need answers to:
- Cloud vs. self-hosted models?
- Which LLM APIs for which use cases?
- RAG architecture or fine-tuning?
- Cost projections at scale?
We make the technical calls based on your industry, budget, and engineering reality with a full risk assessment on all projects we work with.
Compliance, Security & Risk Management
AI that violates regulations isn’t innovation it’s a liability.
We build compliance guardrails into your strategy from day one: data handling policies, model governance frameworks, audit trails, and risk mitigation for your specific industry standards (GDPR, HIPAA, SOC2, whatever applies).
You get frameworks that satisfy both legal and engineering requirements. Clear policies that mean people to do the right things by default.
Adoption Roadmap & Change Management
Technology is easy. Getting your organization to actually use it isn’t.
We sequence your AI initiatives to build momentum: quick wins first, then complex deployments. We identify which teams need training, which processes need redesign, and where resistance will come from.
Your roadmap includes:
- Phased rollout timeline
- Team enablement plans
- Success metrics that move the organisation forward
- Change management strategy
Implementation plans that account for humans, not just systems.
