Innovation Lens provides a data‑driven platform that analyzes millions of scientific articles, patents, and grant records to identify emerging research topics with a statistically validated likelihood of high impact. Its patent‑pending algorithm scores novelty and proximity to existing work, delivering ranked lists, visual dashboards, and API‑enabled reports that help deep‑tech investors, grantmakers, and research institutions prioritize funding and investment decisions.
Funding
Funding not disclosed
Founders
Product
Problem
Deeptech investors, grantmakers, and research institutions face an overwhelming volume of scientific literature, making it difficult to identify emerging, high-impact research topics that are both novel and sufficiently supported by existing work. This information gap leads to inefficient allocation of capital and missed opportunities for breakthrough innovations.
Solution
Innovation Lens offers a data-driven platform that analyzes millions of articles, patents, and grant records to surface research topics with a statistically validated likelihood of becoming high‑impact breakthroughs. Its patent‑pending algorithm quantifies both novelty and proximity to existing work, delivering ranked lists of promising areas. Users receive automated reports and visualizations that highlight emerging gaps, citation potential, and strategic relevance, enabling faster, evidence‑based decision‑making for investment and funding strategies. The service is delivered via a web interface with optional API access for integration into internal workflows.
Target Audience
Primary customers are deeptech venture capital firms, grantmaking agencies, and research institutions that need to prioritize funding and investment in emerging scientific domains.
Features
- Predictive analytics engine trained on >40 million publications and patents, delivering topic scores that are ~300 % more accurate than baseline for PubMed and ~100 % for physics and computer science
- Automated identification of “innovation gaps” that are novel yet well‑supported by recent literature
- Interactive dashboards with trend graphs, citation forecasts, and heat‑maps of research clusters
- Exportable reports and API endpoints for seamless integration with internal analytics pipelines
- Tiered subscription plans providing access to historical data ranges, multiple repositories, and real‑time monitoring