The GenovateAI model
Most AI transformations fail because the approach is wrong, not the technology. Here is exactly how we work — and why we work this way.
01
We spend the first weeks understanding the real problem — not the stated one. Most organisations know what they want to build. Very few know whether they have the conditions to build it.
02
We do not issue strategy decks and leave. Every recommendation is grounded in a data-driven audit and working AI — a deployed agent, a production workflow, a pilot you can measure — so the evidence makes the case, not a slide.
03
We stay accountable until the system ships and runs in production. You own what we build — no lock-in, no subscription — and we embed until your team can run and extend it without us. (When an engagement reveals a venture-scale opportunity, Meta3Ventures can selectively build and invest alongside it — always optional.)
Step 01 · Diagnose
Weeks 1–3. No premature prescriptions. Only understanding.
The most common reason AI transformations fail is not the model, the infrastructure, or the budget. It is a misdiagnosis at the start. The organisation believes it has a data problem when it has a governance problem. It believes it has a tooling problem when it has an alignment problem. It believes it is ready to scale when it has not yet proved the core loop.
Our diagnostic phase is structured around four questions that most engagements never formally ask: What decision are we actually trying to change? Who loses something if the AI works? What data exists in production-ready form versus what we imagine exists? And what does success look like at 90 days, not 18 months?
By the end of week three, we have a shared, written answer to all four. That document becomes the constraint for everything that follows. And not every engagement should end with an AI agent — sometimes the honest recommendation is workflow redesign, conventional automation, or stopping.
Step 02 · Build
Weeks 4–10. Production-grade, not demo-grade.
Strategy documents do not transform organisations. Working systems do. The build phase produces a deployed, measurable AI system — an agent, a workflow, a reasoning layer — that operates in the client's actual environment, not a sandboxed demo.
We work with the client's engineers, not around them. Every technical decision is documented. Every assumption is testable. The goal is not an impressive presentation at the end of the engagement — it is a system the client's team can maintain, extend, and build on after we are no longer in the room.
We leverage the Meta3Agents infrastructure — a governed library of AI personas, production workflows, and composable skills — which compresses build timelines substantially compared to building from raw model APIs. What takes a standalone team six months takes us six weeks.
Step 03 · Own
Weeks 8–ongoing. Accountable until it ships and runs.
What makes GenovateAI structurally different is not a billable-hours relationship — it is accountability. We stay on the hook until the system ships and runs in production. Our incentive is your production result, not the number of hours we log. We do not recommend a path that sounds good but fails quietly six months later, because we are the ones who have to make it work.
And the system is yours. Everything we build belongs entirely to the client — no licensing fee, no vendor lock-in, no ongoing subscription. We embed alongside your team until they can run and extend it independently. When we leave, you own a working system and the capability to evolve it.
Occasionally an engagement reveals a venture-scale opportunity — a new product, a spin-out, an AI-born company. When it does, Meta3Ventures (not GenovateAI) can selectively build and invest alongside it. This is always optional, separate from the core engagement, and you retain your equity and strategic control. It is a capability of the wider ecosystem — never a condition of working with us.
A typical engagement
Week 1–3
Deep listening. No premature prescriptions — the output is understanding and a constraint brief.
Week 4–6
Architecture, agent design, data pipeline, integration plan.
Week 7–12
Production deployment with the client's team working alongside ours.
Week 13–16
Measure, iterate, hand over. The team can run it without us.
Timelines vary by scope and complexity. Diagnostic-only engagements run 3–4 weeks. Full build engagements typically run 10–14 weeks. Multi-agent deployments may extend to 16–20 weeks. All timelines are fixed at the start of the design phase — not adjusted as scope grows. Every phase boundary is an explicit decision gate: advance, redesign, or stop.
The commercial ladder
Stage 1
Fit, situation, and an honest next-step recommendation.
Stage 2
What to build, fix, or stop — with the evidence behind it.
Stage 3
One workflow, a measured baseline, acceptance criteria set up front.
Stage 4
Deployed, instrumented, and owned by your team.
Each stage ends at an explicit gate — advance, redesign, or stop — so momentum never substitutes for evidence. Stage 3 is productized: see the Governed Workflow Pilot.
The capacity constraint is not a bottleneck. It is a design decision — one that determines the quality of every engagement we take.
Engagements are priced based on scope, not a standard rate card. Diagnostic-only engagements typically range from $25K–$50K. Full build engagements with deployment start at $80K and vary by complexity. In the rare case an engagement opens an optional Meta3Ventures venture path, the structure is discussed openly and separately — never a condition of the core work.
We work best with companies at Series A to Series C who have identified a specific AI opportunity but are unsure whether they have the conditions to capture it — or who have already attempted an AI pilot that failed to reach production. We also work with enterprise business units operating like internal startups.
We are not the right fit for companies in pure exploration mode with no defined problem, or for projects where the primary deliverable is a strategy deck rather than a deployed system.
Occasionally. When an engagement reveals a venture-scale opportunity, Meta3Ventures — not GenovateAI — can selectively build and invest alongside it. It is always optional, structured separately from the engagement, and you retain your equity and strategic control. GenovateAI's role remains the same regardless: diagnose, build, and stay accountable until the system runs in production.
Yes. GenovateAI works with companies across Europe, the UK, the US, and MENA. Many engagements are conducted remotely with periodic on-site sessions at key milestones. The diagnostic phase almost always includes in-person time.
The system we build — including all code, models, and IP — belongs entirely to the client. There is no licensing fee, no vendor lock-in, and no ongoing subscription. You own it outright, and the engagement ends only when your team can run and extend the system independently. Our accountability runs until that point: a working system in production, owned by you, that your team can maintain without us.
Use the application form on the Apply page. We ask a few questions about your company, the problem you are working on, and your current AI maturity. We review every application and respond within 3 business days. If there is potential fit, we schedule a 30-minute diagnostic call — no pitch, no agenda, just understanding the problem.
Applications are reviewed within 3 business days. If there is a fit, we schedule a diagnostic call. No pitch. No deck. Just the problem.