Most AI budgets are spent before anyone knows what will work. We help you find the use cases worth building, pressure-test feasibility, and leave with a costed, ROI-ranked roadmap — vendor-neutral, senior-led, and grounded in your data.
Independent AI consulting — we advise on the right path, then can build it end-to-end.
It is rarely the technology. Projects stall because the wrong use case was chosen, the data was not ready, or nobody agreed on what success looked like — and that only becomes visible after the budget is spent. RAND's 2024 study found more than 80% of AI projects fail to meet their goals, most often for reasons that have nothing to do with the model itself.
AI consulting fixes the expensive part first: the thinking. Before any build, we assess where AI can realistically move a number for your business, whether your data and systems can support it, and what it will take to run in production. We rank the opportunities by return and effort, recommend build-vs-buy for each, and give you a plan your leadership can actually sign off on.
The cost of getting this wrong is rarely the build itself — it is the months spent on the wrong problem, the platform bought that nobody adopts, and the credibility lost when the first AI project underdelivers. An independent assessment is a small investment that protects a much larger one, and it puts every stakeholder in front of the same clear picture before commitments are made.
Because we also build AI systems — from generative AI to custom software and automation — our advice is grounded in what ships, not slideware. And because we are vendor- and model-neutral, our recommendation is the one that is right for you, not the one that suits a platform partnership.
A snapshot of where you stand before you invest
From the first opportunity workshop to a plan your team can execute — engagements sized to where you are today.
We map where AI can create value across your business, score feasibility and data readiness, and rank use cases by return and effort. You leave knowing exactly which ideas deserve budget and which to shelve.
Where large language models, RAG and agents genuinely fit — and where they don't — with a costed path from pilot to production. We help you avoid expensive experiments that were never going to scale.
Whether a chatbot or copilot is the right answer, which channels and journeys to target, and how to measure success before you build. We size the opportunity against the cost to serve.
An honest read on when to buy off-the-shelf, when to build custom, and the architecture and models that fit your stack and budget. We weigh total cost, control and data privacy for each option.
How to add AI features to an existing web or mobile product without disrupting users — scoped, sequenced and de-risked. We plan the rollout so each release earns its place before the next.
Upskill your team, set standards for evaluation and governance, and — when you want — we deliver the build alongside you. Your people stay in control and grow capable of running it without us.
Every engagement ends with concrete, reusable artifacts your team and leadership can act on straight away — not a slide deck that gathers dust.
Good consulting is measured in decisions made and money not wasted. Here's what teams typically gain from a focused engagement — long before any large build begins.
We work directly with the leaders accountable for making AI pay off — not a layer removed from the decision.
Deciding where to place an AI bet without betting the company on it. We help you back the few moves that matter and time them right.
Choosing architecture, models and build-vs-buy with a partner who has shipped it. We pressure-test your options against real delivery experience.
Turning “add AI” into a sequenced, fundable roadmap users will value. We keep the focus on outcomes customers actually feel.
Scaling AI across teams with governance, security and measurable ROI. We help you standardize what works and retire what doesn't.
A SaaS leadership team knew AI mattered but had a dozen competing ideas, no agreement on priorities, and pressure to show something fast. Every idea sounded plausible, none had a business case, and the debate had been circling for months.
We ran a structured assessment — stakeholder interviews, a data review and a prioritization workshop — then scored each idea on impact and effort. We mapped them onto a priority matrix, recommended a first pilot, and outlined the architecture, models and cost to get there.
The team left with a clear, ranked roadmap and a funded first pilot instead of a stalled debate. Two low-value ideas were dropped before a rupee was spent on them, the highest-ROI use case moved into build, and leadership finally had a plan they could all stand behind.
Weeks, not quarters — a focused path from questions to a plan you can fund.
Interviews with stakeholders to understand goals, constraints and where the pain is.
Review your data, systems and skills to judge what is realistically feasible.
Score every use case on impact and effort, then agree the shortlist together.
A costed, sequenced plan with architecture, models and a clear first pilot.
Hand over, upskill your team, and build alongside you when you want us to.
Most AI consultancies stop at the recommendation, then hand you off to someone else to make it real. We're a product-engineering team that has shipped 500+ products over 12+ years, so our advice is shaped by what actually ships in production — not by what sounds good in a strategy deck. And when you're ready to move, the same senior team can deliver it, so nothing is lost in translation between the plan and the build.
Bring your questions and your goals. In one call we'll point to where AI can realistically pay off for your business — and what the first step should be.
Tell us about your project and our team replies within 24 hours with a clear scope and estimate — no obligation.
