We design the whole system around the model, not just the model.
Most AI projects fail between the notebook and production: the model works, but the data contracts, evaluation loop, cost controls and fallbacks were never designed. AI architecture is the discipline of designing those parts first.
Our founder is a practising AI architect. Engagements start with your business decision, map the data and latency realities around it, and produce a blueprint your team (or ours) can build against: components, interfaces, evaluation gates, cost envelopes and failure modes.
How this differs from System Design & Architecture: System Design & Architecture covers the software platform; AI Architecture adds the model, data, evaluation and cost layers that make AI features reliable.
You have a product idea that depends on LLMs or ML and need the system designed before hiring or building.
A proof of concept worked in demos; it now needs reliability, cost control and observability.
Several teams want AI features; you need shared retrieval, prompt management and evaluation infrastructure.
An independent assessment of an AI system that is already built, with prioritised remediation.
Chosen per project. We are vendor-neutral and will recommend what fits your constraints.
Business objective, decision points, data inventory, latency and compliance constraints.
Two or three candidate architectures compared on cost, risk, time-to-value and team fit.
Detailed design, interface contracts, evaluation plan and roadmap, reviewed with your stakeholders.
Optional: our architect stays on to guide implementation and sign off milestones.
A two- to four-week architecture engagement producing a target design, model strategy, evaluation plan, cost model and roadmap.
Twenty questions we ask before designing any AI system. If you can answer most of them, you are ready to build…
Both. Many clients start with a design engagement and then have our engineering team implement it; others take the blueprint to their in-house team.
It depends on the task, data-residency requirements and cost profile. We are vendor-neutral and have shipped on Claude, OpenAI and Gemini.
Typically two to six weeks depending on system scope and how many stakeholders need to be involved.
RAG assistants, copilots, summarisation and content pipelines.
Agentic workflows and cross-system automation, with and without code.
Neural networks for sequences, perception and control.
Document OCR, image evaluation and visual inspection pipelines.
Send a three-line brief. We reply within one business day.
A two- to four-week architecture engagement producing a target design, model strategy, evaluation plan, cost model and roadmap.
