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 4–8 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.
The thesis: in AI, the moat is not the model
Open-weight models commodified the AI core. What makes an AI business defensible in 2026 is no longer model performance — it is the data provenance, the workflow embedding, the patent claims around the method, and the proof of monetisable, non-replicable advantage. Founders who can name that moat in one sentence raise faster, exit higher, and do not get squeezed 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 unlock — defensive, licensing, or M&A?
Triangulating across all four typically produces a valuation 2–5× 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 (1–10) 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 not just the model — it is the IP around it
- 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 2–5× 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.
Book the diagnostic
One 60-minute call. You leave with a defensibility score and a royalty range — for free.
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