The First AI Impact Audit Platform

Prismatique helps investors price AI’s impact on company value and gives business leaders a quantified roadmap to create it. Our proprietary frameworks and platform connect the evidence, the action plan and the results over time.

Request a demoOnboarding in 2026

What does AI change for this business?

A synthesis of the investment case: readiness, competitive advantages, financial impact, priority decisions and the uncertainties that matter.

How much of the AI strategy is real?

Separate what is declared, tested, deployed and used across operations and products. Examine measurable results, team capabilities and constraints in data, systems and governance.

See how demonstrated maturity is distributed across departments and workflows.

Compare each workflow’s current level and target state. Use the gap to shape the roadmap.

Review workflow volumes, friction, demonstrated maturity and the evidence behind each assessment.

What can AI erode, replace or strengthen?

Identify exposed revenues, margins and competitive advantages. Test what competitors can replicate or bypass, what remains defensible, and who captures the benefit over time.

What does this mean for company value?

Bridge current EBITDA to AI-normalised EBITDA. See how productivity, new revenue, pricing pressure and recurring costs change earnings, and how that impact builds over time.

What should we do first, and why?

A company-specific plan to create and protect value. Compare expected benefit, investment, timing, dependencies, ownership and review criteria, starting with the first 100 days.

First 100 days, then the next milestones.

Establish the baseline, assign accountable owners and sequence the priority initiatives. Track delivered outcomes separately from expected or extrapolated gains.

Is the plan delivering the expected value?

Track implementation milestones, committed investment and measured gains over time. Compare actual outcomes with the investment case and identify where action is needed.

Why prismatique

We do not measure the presence of AI. We measure the work it actually performs, with complete independence. We then translate that reality into EBITDA and valuation.

Expertise

Four founding profiles combining financial, operational and technological insight into the same organisation.

  • Two small- and mid-cap M&A specialists with 20 years of combined experience and more than 80 completed transactions.
  • Two builders of software and agentic systems with 20 years of combined technology development experience.
  • A 100% AI-native company that understands AI maturity because it builds and deploys these systems.

Methodology

A function-by-function reading of operational reality, grounded in evidence rather than narrative.

  • Verify real usage: who uses AI, where, how often and for which tasks.
  • Assess what systems actually execute, from individual assistance to supervised work.
  • Establish every position through interviews, processes, tools, documents, usage data and architecture.
  • Measure opportunities, dependencies and the possible path towards a sequenced and quantified action plan.

Independence

An objective assessment because our economic interest never depends on the initiatives we recommend.

  • We do not implement the initiatives we recommend.
  • Every level is backed by evidence: a score without proof remains an opinion.
  • Every initiative states its access tier and confidence level; nothing is oversold.

How it works.

Inputs

Human

Tailored interviews to uncover real workflows and organisation.

Business

Documented workflows, wikis, procedures, internal charts, financial statements, latest audit reports, …

Tech

Technology stack, usage logs, telemetry, …

Request a demo

Assess AI maturity objectively.

Let us discuss your context, the scope to assess and the decisions the audit should inform. We will get back to you within 48 hours.

Or directly: contact@prismatique.ai

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prismatique

Manifesto

AI impact belongs in every valuation.

AI marks a structural break in how businesses create and capture value. It can obliterate competitive advantages, destroy pricing power and create new profit pools before financial results reflect the shift.

Financial, legal and strategic due diligence must now establish what AI puts at risk and where it can create value. A company can become more productive and still be worth less.

Our proprietary frameworks measure operational AI maturity, expose business model vulnerabilities and quantify the potential for value creation. We translate the evidence into earnings and valuation scenarios, with transformation costs and execution risk built in.

Investors get the evidence to price risk and upside. Business leaders get a quantified roadmap for creating value. Our platform tracks progress and tests expected gains against measured results.

Founded by M&A and AI practitioners with 40 years of combined experience, Prismatique brings transaction discipline to AI impact assessment. We protect our independence by keeping implementation outside our business: we do not sell the projects we recommend.

Our vision

Give the market a universal benchmark for AI proficiency across every investment process and M&A transaction.

Provide genuinely useful tools to audited companies.

The questions our platform answers

  1. What is this company really worth in the AI era, and can it defend and grow that value?

  2. What is the company’s real moat, and can AI replicate or bypass it?

  3. Which revenue streams and margins are exposed to AI disruption, and over what time horizon?

  4. If competitors gain access to the same AI capabilities, what keeps customers paying this company?

  5. What is the company’s actual level of AI maturity across its core operations and products?

  6. How much of its AI strategy is already operational, and what measurable results can we verify?

  7. Are its AI capabilities embedded in the organisation, or dependent on a few individuals and isolated tools?

  8. Is the company building capabilities that will remain valuable as AI improves, or investing in advantages that AI will commoditise?

  9. Is management’s AI strategy backed by a credible operating plan, capable teams and committed resources?

  10. Can the company adapt before AI puts material pressure on its revenues and margins?

  11. What must change in its data, systems, organisation and commercial model to deliver that plan?

  12. What additional value can AI create, net of implementation, operating and oversight costs?

  13. Will productivity gains expand margins, or will customers and competitors capture the benefit?

  14. Where could AI support new revenue, better retention or stronger pricing power?

  15. How much of the asking price is supported by demonstrated AI performance, and how much depends on future execution?

  16. How does AI change the earnings outlook and the valuation we can justify today?

  17. How would the valuation change under downside, base and upside scenarios?

  18. What additional capital must we commit after closing, and how should that affect the price we are prepared to pay?

  19. What should happen in the first 100 days, and which initiatives should follow?

  20. What evidence will demonstrate that the AI strategy is delivering the expected results?

  21. Where are actual outcomes diverging from the investment case, and what needs to change?

Existing shareholders

  1. Which portfolio companies are most exposed to AI, and where should we prioritise investment?

  2. What must change before exit to strengthen the valuation case?

  3. What evidence can we show the next buyer that AI has improved earnings quality or made the company’s competitive advantages more durable?

Strategic acquirers

  1. Do the target’s AI capabilities strengthen our business, or duplicate capabilities we already have?

  2. Which AI-related synergies can we realistically realise, at what cost and over what timeframe?

Business leaders

  1. Where is AI putting our business at risk, and where can we build an advantage?

  2. What should we change first, what will it cost and what measurable benefit should we expect?

  3. Which activities should remain human, and which are ready to be redesigned around AI?

  4. How do we demonstrate progress to our board, investors or a future buyer?