Turn AI ambition into systems that run your business
AI roadmaps, LLM architecture, RAG systems and agent workflows wired into your core operations.
What you get
- AI opportunity assessment and 12-month roadmap
- Reference architecture and data readiness report
- Production pilot with evaluation harness
- Governance, security and responsible-AI playbook
From first conversation to running system
- 01AssessData, workflows and risk audit
- 02DesignUse cases, architecture, guardrails
- 03PilotProduction pilot with evals
- 04ScaleRollout, monitoring, enablement
Overview
Most AI initiatives stall between a promising demo and a dependable production system. We close that gap with an engineering-led approach: we start from your data, your workflows and your risk profile, then design AI capabilities that fit the way your organisation actually operates.
Our teams have shipped LLM applications, retrieval systems and autonomous agents into regulated environments. We bring the evaluation harnesses, guardrails and observability that make those systems safe to depend on.
Outcomes you can expect
- Working AI capability in production within one quarter
- Measurable cost or revenue impact tied to each use case
- Internal team enabled to own and extend the platform
Industries served
AI Consulting & Transformation on a real engagement
Senior engineers, production-grade from the first sprint, with the outcome instrumented so you can see it move.
What we do under AI Consulting & Transformation
AI strategy & opportunity mapping
Prioritised use-case portfolio with ROI, feasibility and risk scoring.
LLM application architecture
Model selection, prompt and context design, cost and latency budgets.
Retrieval-augmented generation
Document pipelines, embeddings, vector search and grounded answers with citations.
Agentic workflows
Tool-using agents with human-in-the-loop checkpoints for high-stakes actions.
Evaluation & guardrails
Golden datasets, automated evals, red-teaming and policy enforcement.
MLOps & LLMOps
Versioning, monitoring, drift detection and cost governance in production.
Related case studies
Questions we hear most
No. Data readiness is part of discovery. We identify the minimum data foundation required for the first use case and build from there.
We are model-agnostic and routinely deploy OpenAI, Anthropic and open-weight models. Selection is driven by accuracy, cost, latency and data residency requirements.
We design for least-privilege access, private deployments where required, redaction pipelines and audit logging from day one.
Other services
Ready to talk about ai consulting & transformation?
Book a free 45-minute session with a senior architect. We will map your situation to a delivery shape and an honest estimate.