Architecting the Deep‑Tech Private Market
Real-time coverage of capital raises, federal awards, patent grants, published research, regulation and liquidity events across deep tech, with profiles of the companies, researchers, institutions and investors involved.
Noair Lab exists to accelerate capital formation for the most promising deep tech companies.
Live market activity
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Seven Data Sources, One Dataset
Profiles of Companies, Researchers, Institutions and Investors
Each profile consolidates the filings, awards, patents and publications associated with an entity, linked to related entities across the dataset.
Financing history, federal awards, contracts, patents and exits on a single timeline, with peer benchmarks and leadership.
- SEC Form D raises and their dates
- Federal grants and contracts
- Patents, founders and investors
- Peer ranks within the sector
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Relationships Across the Deep Tech Ecosystem
Every filing, award, patent and publication is linked to the companies, researchers, institutions and investors it involves. These connections establish baselines for each sector and entity type, against which Noair Lab measures activity and identifies the patterns that inform its predictive models.
From Connections to Predictions
How the dataset supports the models- 01ConnectFilings, awards, patents and publications are linked to the entities they involve, with names reconciled across sources.
- 02Establish BaselinesNorms by sector, stage and entity type: time from first federal award to first financing, award cadence, patent velocity and co-investment frequency.
- 03Detect PatternsCurrent activity is measured against those baselines to identify acceleration, convergence of funding sources and shifts in investor behaviour.
- 04PredictModels trained and validated on these patterns estimate financing likelihood, technology readiness progression and regulatory catalysts.
The Model Signals above are examples of stage 4: each is a pattern measured against a baseline. The map below shows the connections behind them.
Dr. Mara Ellison
Principal investigator on two federal awards, first inventor on a granted patent, author of a 2025 paper, and named as an executive officer of Helix Bio in its SEC filing.
- Northfield UniversitySTTR partner
- Nature Biotechnologypublished in
- US 12,345,678inventor
- Helix Bioleads · Form D
- NIH SBIR Phase IIprincipal investigator
- —federal awards linking researchers to companies
- —researchers in company leadership
- —patents linked to their inventors
- —companies affiliated with — institutions
- —co-investor pairs
- —researchers matched to their papers
Accelerating Capital Formation in Deep‑Tech
Early-stage deep tech companies are private and technically complex, which limits their visibility to investors. Noair Lab makes their activity visible and maintains a focused ecosystem around it.
Identify Financings at Filing
- Form D filings as they are submitted
- Federal awards and patents that precede a financing
- Co-investment networks and portfolio exits
Present a Verified Company Profile
- Financings, awards, patents and leadership in one profile
- Claim, verify and annotate the profile
- Visibility to investors researching the sector
Connect Research to Commercial Outcomes
- Awards, patents and publications in one profile
- Company affiliations arising from research
- Industry partners on STTR awards
Measure Affiliated Company Formation
- Companies led by partner researchers
- STTR partnerships and industry collaboration
- Benchmarks against peer institutions
Platform Capabilities
Automated Data Collection
LiveEach source is collected on its own schedule, entity names are reconciled, and profiles are updated continuously.
Explore companies →Baselines and Analysis
In researchSector and entity baselines derived from connected data, and research on the indicators associated with company outcomes. Analysis One: acquired aerospace companies raised 11× more private capital than defunct ones.
News and analysis →Prediction
In developmentPredictive models built on these baselines and patterns, validated against historical outcomes, with accuracy published before release.
Follow the research →Request Platform Access
Available to investment firms, corporate development teams, universities and research institutions.