Technology Intelligence
The scientific edge in
emerging technology investment
Innovation Lens provides technology intelligence to VCs and institutional investors on the emerging technologies that will define the next decade, grounded in the latest research from leading labs worldwide.
33.8%
Annual return, 2010–2026 (S&P 500: 13.3%)
+5 pts
Added per year to Gary Anderson’s real trades, walk-forward
21 mo
Ahead of the NSF on 2D electronics
3,700+
Technology predictions tracked
Backtested and walk-forward results, both hypothetical. The trades re-weighted above are real; the re-weighting of them is a simulation, not a live account. Past performance does not guarantee future results.
What We Do
Intelligence before consensus
We translate the frontier of scientific research into technology intelligence years before it reaches mainstream market awareness.
Deep Scientific Monitoring
We continuously track published and unpublished research in computer science, physics, and biomedicine — identifying breakthroughs before they surface in earnings calls or analyst reports.
Quantified Predictions
Each research signal is assigned a confidence score that measures alignment with commercial applications. In backtested simulations, high-confidence predictions have outperformed market benchmarks over the period studied.
Research for Investors
We partner with venture capital firms, family offices, and institutional investors to identify which emerging technologies merit attention before the crowd arrives.
How It Works
We map the scientific landscape and predict what rises
Our system embeds millions of papers into a unified research landscape, grouping them by semantic proximity across disciplines. We then identify clusters of papers our model believes will drive future commercial breakthroughs and mark them as predictions. The maps below show what happens when we overlay predictions made in 2018-2021 with articles published in 2022-2026. On the left, all published articles. On the right, all articles that received at least 300 citations. The same clusters remain, showing our model reliably points to work that goes on to matter most.
Every topic our model predicted as significant during 2018-2021, overlaid on the published research landscape of 2022-2026. Orange dots show our predictions.
Filtering to show only those papers that received 300 or more citations, the clusters hold. Our predictions disproportionately capture the research that becomes most impactful.
Each hexagonal cell represents a distinct research topic cluster. Orange dots are topics and papers flagged by our prediction model prior to citation accumulation.
Scientific Rigor
Research-grounded conviction
Our predictions are not based on market sentiment or analyst reports. They are derived from systematic analysis of primary scientific literature, including papers from the world's leading research institutions that have not yet reached commercial awareness.
Literature Ingestion at Scale
We process tens of millions of preprints and peer-reviewed papers across disciplines, identifying technology-commercialization signals before they enter the mainstream narrative.
Multi-Domain Synthesis
Breakthroughs rarely emerge from a single discipline. We connect dots across computer science, physics, and biomedicine to identify convergence opportunities.
Verified Prediction History
Every prediction is dated, recorded, and scored, creating an auditable track record that speaks for itself.
Case Studies
Dated, recorded, and ahead of the news
When our predictions keep landing in the same region of the research landscape, the signal is one worth acting on. Two clusters that formed well before the market noticed.
2D Quantum Materials
We flagged 2D electronics before the NSF did
One prediction landed on low-dimensional electronics in Dec 2024. Over the next nine months seven more landed in the same region of the map — the same neighbours, the same cluster, tightening. In Sep 2026 the NSF opened its $150M ELEGANT program in exactly that area.
21 months
from first prediction to NSF funding
Each hexagon is a research topic; yellow marks a prediction, and the pale halo is the region it covers. The same frame, nine months apart — what changes is how much of it we had called.
AI Code Generation
8 months
ahead of Cursor's Series A
We flagged AI coding before the round that repriced it
Our predictions clustered around AI-augmented software development through 2024 — one in Dec 2023, five more by that July. Cursor raised at a $400M valuation the following month, and was later bought by SpaceX at $60B, roughly 150× that mark.
Backtest · Apr 2010 – May 2026
What the scores alone would have returned
We matched predictions to US-listed companies, bought only the top scorers — 30 holdings at most — and held each for three years, longer if a new prediction confirmed it. No market signals, no discretion.
$1,000 invested in 2010 → $105,954
vs $7,399 in the S&P 500 over the same period
33.8%
Annual return · S&P 500 13.3%
1.01
Sharpe ratio · S&P 500 0.81
−49.9%
Max drawdown · S&P 500 −33.7%
Hypothetical backtest, not a live account. The same scores that produced the return above also produced a 49.9% peak-to-trough drawdown — deeper than the S&P 500's over the period. Past performance is no guarantee of future results.
The Janus Factor Challenge
An award-winning manager asked us to beat his own portfolio
Gary Anderson — author of The Janus Factor (Bloomberg Press) and winner of the Charles H. Dow Award — picks stocks on market signals: momentum and relative strength. He challenged us to improve on his selection using scientific signals alone, scored independently of anything his own method looks at.
Same stocks, same days, same prices — only the weights change
We tilt each holding toward its Innovation Lens score, with the threshold chosen walk-forward rather than in hindsight
29.3%
Re-weighted, a year
24.2%
His portfolio, untouched
+5.1 pts
Added per year, Jun 2018 – Aug 2026
Hypothetical walk-forward backtest, before tax, not a live account. His trades are real; the re-weighting of them is a simulation. Choosing the threshold without hindsight does not make this a live record — the scoring method, the weighting rule and the structure of the account were all fixed with the whole record in view, and the edge arrives in three of the eight years rather than evenly. Past performance is no guarantee of future results.
Private Markets
Our edge multiplies in private markets
If our predictions generate alpha in liquid public markets — where prices reflect millions of participants — imagine the advantage in pre-IPO companies where information asymmetry is far greater and pricing is far less efficient.
Earlier Signal Capture
We identify technology themes 3–7 years before they reach public market consensus, precisely the window where private equity returns are made.
Unpriced Scientific Moats
Private companies often have deep ties to academic research. We identify which scientific relationships translate into durable competitive advantages.
Portfolio Construction Clarity
We help VCs answer: “Is this technical thesis actually grounded in the state of science?” — a question that separates category leaders from also-rans.
Work With Us
Ready to invest at the frontier?
We work with a small number of investment partners. If you are a VC, family office, or institutional investor seeking a durable scientific edge, we would like to speak with you.