We embed in your organization, diagnose where AI creates real advantage, and stay accountable through execution — until the system ships and runs.
Listen. Understand your business, pressures, and constraints — before forming any view
This is not a trend to monitor or a pilot to run. AI is reshaping competitive advantage, capital allocation, and talent models at the same time — and the window to position correctly is measured in quarters, not years. The enterprises that get the decision architecture right now will set the terms in their market. The ones that don't will spend the next cycle catching up.
How we define our metrics: every third-party figure on this page is labeled with its source. Internally measured figures appear only with their full methodology disclosed. Sources & definitions →
Pilot-heavy, little in production. Strategy decks pile up, spend climbs past $3–5M, and board confidence slips.
Leadership gains clarity on which AI bets to make. ROI-weighted priorities. Production systems begin shipping. Board alignment achieved.
Proprietary models. Agent workforces. AI-born ventures. Competitors react to moves you made 18 months earlier.
The question is no longer whether to transform. It's whether you have the decision architecture to do it right.
That's the gap we exist to close — between ambition and production, between strategy and value capture.
Enterprise AI requires simultaneous mastery of strategy, architecture, engineering, and value capture. Most enterprises have none of them connected.
Leadership lacks decision architecture. Pilots multiply without alignment. The board pushes harder. The team moves in circles.
AI spend treated as expense, not capital allocation. No ROI framework. No portfolio view. Every initiative competing for the same budget.
Strategy, architecture, engineering, and ownership sit in different hands — decks get handed off, systems get built to spec, and no one is accountable end to end. The pilot ends, the system never ships.
The paid AI Decision diagnostic produces board-ready artifacts your leadership can act on immediately — each one tied to a real decision, ROI case, or execution path.
Different stages of the AI journey require different interventions. Identify your situation — we'll tell you exactly what comes next.
You have AI ambitions and a board asking hard questions. Multiple pilots are running. Nothing is in production. The consultants have delivered decks. The ROI case doesn't exist yet.
You're about to write a check into an AI company — or acquire one. The founder says the moat is the model. You need code-level truth before the term sheet, not after.
Your hardest AI problem keeps coming up in every leadership meeting. It's too big for an internal team and too strategic to outsource. It might be a company.
You know where the analyst hours are going. Market intel, reporting, sourcing, monitoring — repetitive, high-volume, decision-critical work that AI agents could run 24/7.
Not sure which situation fits?
30 minutes with Liron. We'll diagnose where you are, which path makes sense, and whether we're the right fit — before any engagement begins.
From decision architecture to production engineering to venture building — one operating model that executes across all of them.
4–6 weeks. Board-ready ROI clarity and live agent workflows on your data.
See full detailsEmbed as your fractional CAIO from week one. No 6-month ramp.
See full detailsSenior AI engineers embedded with your team. 14-week sprints. Accountable to production, not a slide deck.
See full detailsManaged AI agents running 24/7 on your workflows. Always-on intelligence.
See full detailsCode-level technical truth before a significant investment, acquisition, or strategic commitment.
See full detailsTurn your hardest AI challenge into a funded, independent company.
See full detailsThe work is the same across every engagement — only the problem changes. We listen first, prove with data before we present, and — when a venture-scale opportunity emerges — Meta3Ventures can build and selectively invest alongside it. Always optional.
Weeks 1–3. No premature prescriptions. Stakeholder interviews, data audit, readiness assessment, weekly decision notes, and a one-page constraint document signed by leadership — before any recommendations.
Weeks 4–10. A data-driven audit and a working system on your data — not a sandboxed demo or a slide. The evidence makes the case, and your team can inspect, extend, and run it.
Weeks 8+. You own what we build — no lock-in, no subscription — and we stay accountable until it ships and runs in production. (When the work surfaces a venture-scale opportunity, Meta3Ventures can build alongside it. Always optional.)
15 questions across 5 dimensions. Honest scoring. A tier interpretation that tells you whether your next move is a pilot, a diagnose engagement, or a full build — and what to fix first if it's any of the first two.
30 minutes. We'll map where your AI decisions are bottlenecked and tell you honestly whether we're the right fit. No pitch, no deck, no commitment.
"The initial conversation alone was worth more than most paid engagements."
— CTO, Series B SaaS · private client feedback, shared with permission