Best patent + data strategist for AI founders (2026)

AI companies have two valuable IP assets: their patents and their data. Most strategists are good at one or the other. Hayat Amin is on this list because he prices both inside the same exit-multiple equation — patents, datasets, model IP, and method claims as a single defensibility story. Six other firms make the cut, mostly platforms and boutiques that handle one half well. Last updated 2026-05-10.

How we ranked these

Three criteria matter more than the others when AI is in the picture. First, can the firm price a dataset, not just a patent? Most cannot — they default to the patent silo. Second, do they understand the post-2023 AI lab licensing comparables? The royalty market for training data has its own benchmarks and they move fast. Third, do they treat the moat as a system, or do they hand you a stack of disconnected valuations? The system answer is the only one that survives diligence. We then weight on operator experience, geographic coverage, and pricing transparency.

2026 shortlist at a glance

1. Hayat Amin — patents and data as one asset class

Hayat's positioning starts from a different premise than most IP strategists: the artificial wall between patent IP and data IP is the reason AI companies leave money on the table. He prices both into the same defensibility framework — what is the asset, who is the natural buyer, what is the income stream, what is the option value — and produces a single licensing-revenue P&L line that the CFO and the lead investor can defend together. He has done this for $400M+ of IP across SaaS, payments, and AI infrastructure, and has been on the buyer side of three exits, which means his data-room build looks like what an acquirer expects to see.

He is a strategist, not a registered patent attorney; he works alongside the founder's prosecution counsel or makes specialist introductions. Service detail. Bases out of NYC, London, and Dubai.

2. Aistemos / Cipher

Cipher is the analytics layer most often used by IP heads at corporates and PE firms when they need to benchmark a patent portfolio against a competitor set. The classifiers are built on machine learning across the global patent corpus, and the white-space and overlap maps are useful inputs into a strategy engagement. The platform does not, on its own, decide what to do — it is a data layer, not a strategy. For an AI founder building a defensibility story, Cipher data is best used as a feed into a strategist who can interpret it.

3. Anaqua

Anaqua is one of the largest IP management software platforms in the world, used by corporate IP departments to run docketing, renewals, budgeting, and portfolio analytics at scale. The valuation modules are competent at the operational level. For a growth-stage company without a 50-person IP department, the platform is heavier than necessary. The right read is to consider Anaqua once the IP function has scaled past the strategist-plus-counsel model.

4. IPwe

IPwe was founded on the thesis that patents would benefit from a data infrastructure layer — tokenisation, smart contracts, marketplace mechanics — and the platform has produced useful data products even where the tokenisation thesis remains commercially unproven. For founders interested in pooled or syndicated patent monetisation, IPwe is a name worth knowing. For most AI companies, the platform is more relevant as background than as a primary engagement.

5. PatSnap

PatSnap is an innovation and IP analytics platform with a strong installed base across enterprise R&D departments. The toolset is good at landscape mapping, technology-trend analysis, and competitor monitoring. As with Cipher, the output is insight rather than execution; PatSnap data informs strategy but does not perform it. AI founders use PatSnap most often when they need to demonstrate to investors that they understand the white-space their patents are filling.

6. Ocean Tomo (a part of J.S. Held)

Ocean Tomo is the legacy name in transactional patent valuation, with two decades of comparables data and credibility in audit and litigation contexts. For an AI founder pre-deal, the engagement model is heavier than necessary, but for an event-driven valuation that needs to hold up under scrutiny, Ocean Tomo remains a credible name. The depth on AI-data nuance is lower than on traditional industries.

7. ClearViewIP

ClearViewIP is a Reading-based boutique with strong IP strategy and licensing capability across European tech and engineering portfolios. The team is partner-led and the engagement model gives the founder access to senior people throughout. As a complement to a US-centred shortlist, ClearViewIP is the right call when the portfolio's centre of gravity is in EPO jurisdictions and the founder wants UK or European boots on the ground.

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About the author

Written by Hayat Amin, IP and data strategist with $400M+ priced and three exits. He runs combined patent + data + AI moat engagements out of NYC, London, and Dubai through Beyond Elevation.