Covenant analysis project
Lay out every debt basket with verbatim text and plain-language interpretation in parallel columns.
Hire teams of AI research analysts. Answer questions at scale.
“Genuinely feel like Village solves key AGI problems—continual learning and long-term memory—right in the research workflow.”
PM at leading endowment
“99% of funds would find this transformative. We ran this across 1,200 filings. The analyst time reduction was immediate and obvious.”
Trader at $50B+ AUM fund
“Check out what it’s doing in the latest legal analysis. Marvelous! So cool—definitely the best tool for research.”
Associate at top distressed-credit fund
Assistants live in a shared workspace, read documents, update tables, and use tools—like browsing EDGAR and the web—exactly as you do.
Assistants run until the job is done — whether it’s 10 minutes or 10 hours
Scores highest in accuracy for public-company research (Vals AI)
Accuracy based on benchmark questions over SEC EDGAR and web (Vals AI, 2025)
Use cases
Extract hard-to-find KPIs with context across an entire industry.
Comprehensively track the evolution of management’s thinking.
Monitor every press release and news site for developments that are material to your coverage.
Lay out every debt basket with verbatim text and plain-language interpretation in parallel columns.
Track how leaders discuss growth drivers across 8 quarters; flag shifts in sentiment and guidance.
Attendance, ATP, F&B per patron, U.S. box office revenue — by chain and quarter.
Pull commentary across 12 quarters of filings and earnings materials; extract relevant passages.
Assistants create dozens of research documents and bubble up the most important information to the user.
Have confidence that every document was read—and zoom in on the details whenever you need more information.
Quick status: Core pages are ready for review with disclosure-only citations.
Decision: For Uber, if Ads % of GB/GOV isn’t explicitly disclosed, should I compute implied % via Interpreter with step-by-step math and citations?
Task Log
Goal: Extract verbatim disclosures from Uber for the last 12 quarters (Q3'2022-Q2'2025) across filings (10-Ks, 10-Qs, 8-K earnings press releases via EDGAR) and IR materials (earnings call transcripts, investor presentations via IR Materials). Organize by topic and chronologically. Topics: (1) Uber Eats Food Delivery profitability, (2) Uber Eats Grocery profitability, (3) Uber Advertising incl. % of GB/GOV and profitability, (4) Definitions and metrics. Deliver a Page titled "Uber — Disclosures (Last 12 Quarters)" with Summary and topic sections.
Uber — Disclosures (Last 12 Quarters)
Task Log
Extract verbatim disclosures for Instacart/Maplebear (CART) over the last 12 quarters (Q3'2022-Q2'2025) across: Profitability, Ads (% of GTV/GOV and profitability), Grocery Delivery profitability, and Definitions. Sources: EDGAR (10-K, 10-Q, 8-K earnings PR; S-1/S-1/A for pre-IPO) and IR materials (shareholder letters, presentations, call transcripts). Strictly follow citation protocol with text fragments and page_number.
Instacart (CART) — Disclosures (Last 12 Quarters)
Verbatim disclosures listed chronologically (Q3'2022 → Q2'2025). Annotate each with period and source (e.g., "Q1'2024 Shareholder Letter").
Task Log
Extract verbatim definitions and metric methodologies from DoorDash (DASH) filings over the last 12 quarters (Q3'2022-Q2'2025) for comparative analysis. Focus areas: (1) GOV/GTV definitions and inclusions/exclusions, (2) Take rate and monetization metrics, (3) Revenue recognition methodology, (4) Advertising revenue definitions and measurement basis. Sources: EDGAR filings (10-K, 10-Q, 8-K) and investor materials. Ensure strict citation protocol with exact text fragments and source attribution for cross-platform metric comparison with Uber and Instacart.
DoorDash (DASH) — Definitions and Metrics
Follow passage-level citations for every excerpt, sort and filter the output table by company or commentary type, and remix the assistant’s research.
50+ assistants working together
10 hours of research in under an hour
Gain confidence that you've covered every base
Village | ChatGPT | Claude Finance | Perplexity for Finance | AlphaSense Grid | |
---|---|---|---|---|---|
Chat with the assistant | |||||
Dedicated EDGAR integration | |||||
Earnings calls | |||||
Build on prior work | Limited | Limited | |||
Granular citations | |||||
Ability to work at scale | Limited | ||||
Transparent reasoning | |||||
Give feedback at scale | |||||
Collaborate with users on artifacts | |||||
Vals AI performance | 96% | 82% | — | 56% | — |
Context window | Functionally unlimited | 128K | 200K | 32K | — |