Generative AI excellence,
unlocking limitless possibilities.

It includes a use-case assessment scoring candidate ideas against feasibility and business value, an architecture recommendation, a governance and risk framework, and a phased roadmap with a business case. Most engagements run 4-8 weeks depending on how many stakeholders and systems need reviewing.

Consulting is the strategy and architecture advisory work: deciding what to build, which approach fits your data, and how to govern it. Development is the hands-on engineering that follows. We offer both, and most clients move from consulting straight into a development build with the same team.

It depends on scope. A focused use-case assessment and architecture recommendation is a smaller, fixed-fee engagement, while an ongoing advisory retainer through implementation costs more but spreads over a longer period. We size this after a discovery call rather than quoting a number blind, since stakeholder count and technical depth change the work meaningfully.

The number of stakeholders who need interviewing, how many candidate use cases you want scored, and whether we are also reviewing an in-flight technical build all add time. A single-team readiness assessment moves faster than an enterprise-wide roadmap covering multiple departments.

We run a structured opportunity assessment, scoring candidate use cases against feasibility, data readiness, business value, and risk, so you prioritise the initiatives most likely to succeed instead of chasing every idea at once.

It comes down to your data and how the answer needs to be produced. If your knowledge base changes often and answers need to cite it accurately, retrieval-augmented generation (RAG) usually wins. If you need a model that consistently reasons in your domain's own terminology, fine-tuning a base model tends to fit better. A fully custom model is reserved for cases where neither approach solves the problem.

Yes. We regularly provide architecture reviews and performance audits for in-flight generative AI projects, identifying risks, cost drivers, and optimisation opportunities before launch rather than starting from a blank slate.

We advise grounding generative output in verified data through RAG architecture, setting confidence thresholds that route lower-confidence answers to human review, and building an evaluation framework before any system reaches production.

An existing tool is usually faster and cheaper when your use case is common and a vendor's model already fits your data. Custom development earns its cost once you need the system to reason over proprietary data or match a workflow no packaged product covers. Part of our advisory work is giving you an honest build-versus-buy recommendation.

Ask what they have actually shipped into production, not just advised on. A firm that only produces reports and hands them off will leave you to figure out the hard part yourself. Look for consultants who can speak to real technical tradeoffs and who will tell you when an existing tool already solves your problem.

We start with discovery and stakeholder interviews, then a use-case scoring exercise, then a technology and architecture assessment, then the roadmap and business case, and finally a governance and transition plan. Each stage is a real deliverable you review before we move to the next one.

We sign NDAs before any strategic detail is shared, and our assessment includes how data will move between systems, who can access model inputs and outputs, and where an architecture choice would create a new risk.

Yes. If you would rather embed our people into your own team than run a fixed-scope project, you can hire dedicated AI developers who work under your direction on your existing roadmap.

You do. Everything we produce, including assessments, roadmap documents, architecture recommendations, and any proof-of-concept work, belongs to you outright once the engagement is complete.

We offer transition support, implementation oversight, and ongoing advisory retainers. Many clients bring us in to build the roadmap we defined together, so there is real continuity from strategy through delivery rather than a handoff to a separate team.

We work with clients across United States, United Kingdom, Australia, United Arab Emirates, Canada, and India, from early-stage startups through enterprise teams. Engagement scope is shaped by the project itself, not by location.