Proprietary Data Is Now the Most Valuable AI Asset Your Portfolio Company Owns.
The investment race is no longer about which AI tools you subscribe to. It's about which companies have built intelligence on their own data — intelligence that cannot be purchased off the shelf, cannot be replicated by a competitor, and compounds in value the longer it runs.
I build those systems. For investors and board members who understand what that's worth.
Market Reality
The Market Has Already Moved. Most Portfolio Companies Haven't.
In late January 2026, software indexes fell sharply while broader equity indexes held flat. The repricing reflected one conclusion: agentic AI can automate the knowledge work that per-seat SaaS models were built to support. Companies whose competitive moats rested on legacy software or non-proprietary data were hardest hit.
The companies that came through that repricing unaffected had one thing in common: they owned their intelligence. They didn't rent it.
I've been building those systems for three years. Here is what your portfolio company is most likely sitting on — and what it's currently worth.
The Sovereign AI Stack
Generic AI Creates No Moat
If your portfolio company is using ChatGPT, Copilot, or any off-the-shelf AI tool, so is every one of its competitors. That's parity, not advantage. McKinsey (2025): 'Proprietary data and knowledge bases will become a moat for enterprises, making their competitive advantages more difficult to replicate.' The window to build that moat first is open. It won't be indefinitely.
The SaaS Stack Is a Liability at Exit
At due diligence, a portfolio company dependent on six to twelve SaaS subscriptions for its core operations is a risk, not a feature. Bain's 2026 AI Enterprise report named companies with 'legacy software and non-proprietary data assets' as the most exposed to value erosion. Acquirers see this. I help you fix it before the process starts.
PE Firms Are Moving Fast. Portfolio Companies Are Not.
EY's 2026 PE Pulse data shows that by 2026, two-thirds of PE firms expect to invest over a quarter of their total budget in AI — up from nearly zero three years ago. 84% have appointed a Chief AI Officer. The firms are ready. The portfolio companies they own are often still running on Excel and disconnected SaaS tools. That gap is the opportunity.
Data Readiness Determines AI ROI
Blackstone's CTO stated plainly: 'Data quality — not flashy tools — determines AI success.' Only 10% of large companies report significant ROI from generative AI investments. The difference between the 10% and the 90% is almost always the same: the 10% built on their own structured, proprietary data. I assess data readiness as the first step of every engagement.
No Technical Accountability at Board Level
FTI Consulting's 2024 AI Radar for PE found that 40% of PE firms are managing AI investments at the portfolio company level with no centralised oversight — a model FTI described as likely insufficient. Portfolio companies need board-level technical architecture, not another IT manager. I provide that — without the full-time CTO overhead.
Live Systems
Two systems live. One in development.
Not case studies. Not prototypes. Production intelligence systems interrogating real proprietary datasets — built and deployed in weeks.
Doctorate-Level Knowledge Base
A PhD-level cybersecurity thesis — years of clinical research, frameworks, and methodology — restructured as a Sovereign AI coaching system. Users interrogate it through an iPhone app. The expertise scales without the expert needing to be in the room.
IndiFind — European Industrial Property Intelligence
A pan-European database of industrial property assets, overlaid with an AI that lets investors, developers, and brokers ask complex questions in plain English. What took an analyst two hours now takes two minutes. The data advantage stays inside the platform.
In Development
Global Minerals Intelligence System
A living database of global mineral deposits, supply chains, and asset valuations — built for investors who need to move fast in a market where data advantage is everything. The AI doesn't just surface data. It reasons over it.
Engagement
How I Work With Investors and Boards.
Assessment, architecture, and build — each engagement is scoped to a defined outcome. The portfolio company owns what is built.
Data and AI Readiness Assessment
Before any system is built, I assess whether the data assets are worth building on. This is not a generic technology audit. It is a structured evaluation of whether your portfolio company's proprietary data can support a sovereign AI system — and what that system would be commercially worth if built. Most assessments complete within five business days. Some engagements end here, with a written report that pays for itself.
Sovereign AI System Architecture
For companies with the right data, I design a proprietary intelligence system built specifically on their unique information. Not a configuration of someone else's platform. Not a SaaS integration. A private AI system — owned outright, operated internally, impossible to replicate by purchasing the same subscription. Architecture is fixed-scope and delivered with a clear commercial outcome defined before build begins.
Build and Deployment — Architected by One. Delivered by a Specialist Team.
I architect every system personally. A specialist delivery team executes the build. Full IP transfer on completion. No ongoing vendor contracts. No subscription dependency. The portfolio company owns what is built — including the data structures, the intelligence layer, and the competitive advantage it creates. Typical delivery: 8–12 weeks.
What I Deliver
What I Build — and What I Don't Accept.
I work with a small number of investors and portfolio companies at any time. Every project is accepted based on three criteria: the quality and uniqueness of the underlying data, the commercial potential of the AI system, and whether the board has the appetite to act on what is built. I do not take on projects to fill capacity. I take on projects to create assets worth owning.
Sovereign AI System Build
A proprietary AI intelligence platform built entirely on the portfolio company's own data. Full-stack delivery: data architecture, intelligence layer, user interface, deployment. Full IP transfer. No ongoing licence fees. Priced on commercial outcome, not day rate.
Submit an EnquiryData and AI Readiness Assessment
A structured five-day evaluation of the portfolio company's data assets and AI readiness. Output: a written report covering data quality, sovereign AI potential, build complexity, and estimated commercial return. Commissioned pre-acquisition or at 100-day plan stage. Findings are yours regardless of next steps.
Submit an EnquiryTechnical Due Diligence
Independent pre-acquisition technology assessment for investors evaluating data-rich targets. Covers: proprietary data quality, AI value potential, architecture risk, licensing exposure, and integration complexity. Delivered in 5–10 business days. Used to sharpen valuation, identify value creation levers, and surface technical risk before commitment.
Submit an EnquiryFractional CTO — Board Level
Ongoing technical leadership for portfolio companies that need CTO-level thinking without the full-time overhead. I attend board meetings, own the technology strategy, and hold accountability for execution. Engagements are structured around defined value creation milestones — not open-ended retainers.
Submit an EnquiryMarket Evidence
What the Market Is Telling Investors Right Now.
“Nearly half of the larger AI deals recorded by Bain & Company involved AI-native companies or cited AI benefits.”
Source: Bain & Company / Akin Gump, 2026 PE Perspectives
The investment thesis has shifted. AI-native positioning is now a valuation driver — not a feature.
“95% of PE firms plan to multiply their AI investments in the next 18 months.”
Source: World Economic Forum, 2025
Capital is moving toward AI. Portfolio companies that cannot demonstrate proprietary AI capability will face questions at the next board meeting.
“Firms that use AI to drive growth report 1.7× higher revenue growth and 3.6× greater total shareholder return.”
Source: BCG, cited in WWT AI Advantage Report, January 2026
The gap between AI leaders and AI laggards is already measurable in the P&L. It compounds. The time to act is before exit — not during the process.
“I'm shocked that CEOs haven't done a good job preserving sovereignty and dominion. They were on an ARR race, chasing growth in a way that they've leaked intellectual property.”
Source: Robert F. Smith, Vista Equity Partners, 2025
This is the problem I was built to solve.
Credibility
19 Years Building Inside the Systems That Enterprise Companies Depend On.
I've worked inside Thomson Reuters, Woolworths, the Australian Government, and SUEZ — implementing and optimising the enterprise platforms that established businesses run on. That experience is not incidental. It is why I can assess a portfolio company's technical estate in days, not weeks — and why the systems I build are designed for the operational reality of mid-market businesses, not the theory of a consulting deck.
Case Studies
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From CFOs, Heads of Technology, and Group Operations leaders at the organisations I have worked inside:
What decision-makers say.
Exceptional professional — expertise in enterprise architecture, Salesforce, PMO leadership. Remarkable ability to simplify complex projects. Transformed our PMO.
Exemplary platform knowledge with dynamic, thought-provoking approaches. Exactly what large enterprises need early in their Salesforce journey.
Highly professional architect — strong in technical and business engagement. Breaks down complexity, builds relationships.
Knowledgeable and well-connected professional — scoped and addressed company needs accurately and timeously.
Tight-knit team delivered on tight timelines under pressure. Focused on getting right things done right — project shipped, users happy.
I replaced a £140k/year Salesforce stack in 6 weeks. Strategic, precise, and completely focused on what actually ships — not what sounds impressive in a proposal.
Selective Enquiry
If the Data Exists, the Competitive Advantage Can Be Built.
Most portfolio companies are sitting on proprietary data that has never been put to work. Operational records, transaction histories, sector-specific knowledge bases, unique workflows — data that a competitor cannot purchase or replicate. I assess whether that data can support a sovereign AI system, what that system would be worth commercially, and whether the build is the right move.
Enquiries are reviewed within 48 hours. Not every project is accepted.
Projects are accepted based on data quality, commercial potential, and strategic fit.
A written response is provided for every enquiry received.