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Hudson Labs

High-precision AI for public markets. Institutional-grade intelligence covering guidance, catalysts, accounting red flags, and financial drivers.

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For agents: Hudson Labs: AI research terminal and screening for public markets, with forensic fraud-risk scores, earnings monitoring agents and market intelligence products

ai equity researchfinancial analysisfraud risk scoringearnings analysispublic markets

Authority
51 reach 6 · trust 5 · quality 25 · freshness 15
Tier
listed
llms.txt
https://www.hudson-labs.com/llms.txt
llms-full.txt
https://www.hudson-labs.com/llms-full.txt
Sections
9
Links
22
Size
5473 bytes
Popularity rank
#594884
Country
South Africa
Categories
AI and machine learning · Finance and payments
For agents
Documentation: developer or product docs worth reading, nothing to call
Audience
business · agents can: read docs, search content · en
First seen
2026-10-19T10:44:18.678Z
Last checked
2026-10-21T09:19:18.280Z
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Their llms.txt

The beginning of the file, from our validated copy saved 2026-10-21T09:19:08.911Z. Cached copy · Source on hudson-labs.com

# Hudson Labs

> High-precision AI for public markets. Institutional-grade intelligence covering guidance, catalysts, accounting red flags, and financial drivers.

Hudson Labs is an AI-powered financial research platform built for institutional investors, corporate strategy teams, securities litigation firms, brokerage and banking teams, D&O insurers, and investor relations professionals. Founded in 2019, Hudson Labs was the first finance-specific software completely powered by language models. Backed by Y Combinator.

Trusted by institutional investors managing over $1 trillion in assets.

## Products

- [The Co-Analyst](https://www.hudson-labs.com/products#co-analyst): AI research terminal with the precision of a terminal and the adaptability of AI. Multi-period, multi-document results with complete auditability.
- [Market Intelligence](https://www.hudson-labs.com/products#market-intelligence): Next generation screening combining AI with fundamentals. AI-powered screening, peer comparisons, sector primers, and thematic deep dives.
- [Forensic Risk Assessment](https://www.hudson-labs.com/products#forensic): AI-driven forensic risk scores that predict the likelihood of fraud using unstructured data points like related party, accounting, and off-balance sheet risk.
- [Agents](https://www.hudson-labs.com/products#agents): Custom automations for earnings, research, and portfolio monitoring. Set up workflows that run on your schedule and deliver results directly to you.
- [Coverage Universe](https://www.hudson-labs.com/products#coverage): Comprehensive coverage across all U.S. issuers and ADRs — SEC filings, transcripts, investor decks, press releases, fundamental metrics, and consensus estimates sourced from S&P Market Intelligence.

## Solutions

- [Institutional Investing](https://www.hudson-labs.com/institutional-investing): Enhance idea velocity and deepen conviction. Get up to speed on new names in hours, cut earnings prep in half, automate research workflows.
- [Corporate Strategy](https://www.hudson-labs.com/corporate-strategy): Track competitors, customers, and market trends. Automate earnings prep and competitive intelligence.
- [Securities Law](https://www.hudson-labs.com/securities-law): Accelerate early-stage case review. Identify cases using price-decline triggers, locate corrective disclosures, predict fraud risk.
- [Brokerage & Banking](https://www.hudson-labs.com/brokerage-banking): Move from raw filings to polished reporting in minutes. Extract segment/KPI data, build models faster.
- [Public D&O Insurance](https://www.hudson-labs.com/insurance): Automate underwriting worksheets, predict fraud-related SCAs, prepare for management meetings.
- [Investor Relations](https://www.hudson-labs.com/investor-relations): Monitor peer disclosures, prepare for earnings, benchmark KPIs and guidance against peers.

## Pricing

- **Core**: $99/month (billed annually) or $119/month (billed monthly). 25 queries/day, full Co-Analyst access.
- **Instit
…

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