The Brief
A deep-tech diagnostics startup needed its AI/ML patent estate to do double duty — defending its diagnostic moat while actively shaping which features and hardware tiers the roadmap should prioritise next.
Approach
- Drove product differentiation using IP landscape analysis and competitive intelligence to guide AI feature prioritisation and hardware-optimised model deployment across device tiers.
- Oversaw prosecution and portfolio management of 12+ US and 25+ international granted patents across AI/ML, neural network architectures, and microfluidics.
- Generated IP valuation analyses modelling royalty-revenue streams, and structured patent claim strategy that led competitors to take commercialisation licenses.
- Applied a four-lens framework — feasibility, viability, desirability, strategy — to guide roadmap tradeoffs, and developed phased go-to-market plans aligned to release backlogs.
- Conducted inventor interviews and patentable subject-matter identification at the intersection of AI algorithms and medical imaging, ensuring regulatory and IP compliance to minimise product risk.
Outcome & Business KPIs
- Built and defended a 12+ US / 25+ international patent estate underpinning the platform's diagnostic moat.
- Structured claim strategy that resulted in competitors seeking commercialisation licenses — monetising the IP position directly.
- Accelerated time-to-revenue for new diagnostic modules through phased GTM plans tied to the release backlog.
Tools & Frameworks
USPTO / Indian Patent Office prosecutionIP landscape analysisRoyalty & valuation modellingFour-lens product frameworkDeep learning / digital pathology