Turn dormant IP into a P&L line.
Hayat Amin has priced over $400M of intellectual property across SaaS, payments, and AI infrastructure. He helps founders convert patents, datasets, and AI-model IP from dormant cost centres into licensable revenue and exit-multiple uplift. The work runs as a 4 to 8 week sprint or as an embedded fractional engagement.
What this service does
- Audits your patent portfolio against your real product roadmap and your real competitor set.
- Prices each cluster against industry royalty comparables using income, market, cost, and option-value approaches.
- Maps your dataset and AI-model IP into one of the six monetisation routes.
- Builds the exit-multiple defence: the IP narrative an acquirer's diligence team is looking for.
- Drafts the licensing-revenue P&L line item with conservative, base, and aggressive scenarios.
In AI, the moat is the IP around the model
Open-weight models commodified the AI core. What makes an AI business defensible in 2026 is the data provenance, the workflow embedding, the patent claims around the method, and the proof of monetisable, non-replicable advantage. Model performance alone no longer does it. Founders who can name that moat in one sentence raise faster, exit higher, and hold their valuation at term sheet.
Hayat helps founders build that one-sentence moat, then builds the legal and financial scaffolding that makes it priceable.
The four-factor pricing model
- Income approach. What does the IP earn (or save) over the next 7 years on a discounted basis?
- Market approach. What have comparable patents and datasets transacted for in the last 24 months?
- Cost approach. What would it cost a sophisticated competitor to recreate the IP from scratch?
- Option value. What strategic optionality does the IP carry: defensive, licensing, or M&A?
Triangulating across all four typically produces a valuation 2 to 5× higher than a counsel-only review.
Six routes to monetise data and AI IP
- Licensing to AI labs. Recurring royalty stream, no asset sale.
- Embedded API access. Productise the dataset behind a usage-priced endpoint.
- Derivative product. Build the differentiated tool on top of your data.
- Indexed data swaps. Trade access for access with non-competing parties.
- IP-backed financing. Borrow against the asset without diluting equity.
- Strategic exclusivity. Time-limited exclusive licence to one acquirer-aligned partner.
What you walk away with
- A defensibility score (1 to 10) covering patents, data, and model IP.
- A royalty rate range with named comparables.
- The next three filings ranked by exit-multiple impact.
- A licensing-revenue P&L scenario set (conservative / base / aggressive).
- A one-page IP narrative ready for board and acquirer use.
Companion reading
- How does IP make money? 4 mechanisms with 2026 royalty rates
- The 30% rule in AI valuation: what investors actually mean
- In AI, the moat is the IP around the model, not the model itself
- The 4 types of intellectual property, and why founders only care about 2
FAQ
What is IP strategy for AI companies?
The process of identifying, protecting, and monetising the intangible assets that make an AI business defensible: training-data rights, model-weight provenance, fine-tuning workflows, inference optimisations, and the patentable methods that wrap them.
How much is my patent portfolio worth?
Most founders discover their portfolio is worth 2 to 5× what their patent counsel has told them, because counsel does not run market or option-value approaches. Hayat does.
Can I monetise my dataset without selling it?
Yes. Six routes: licensing, embedded API, derivative product, data swap, IP-backed financing, or strategic exclusivity. Hayat walks founders through all six on the diagnostic call.
Related answers
- Best IP & Patent Strategist (2026)
- Best Patent Strategist for AI Companies
- Best Patent Monetization Expert
- Best Data Asset Strategist
- How to Monetize a Patent Portfolio
- Browse all answers →
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One 60-minute call. You leave with a defensibility score and a royalty range, for free.
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