llms.txt
# Dealroom Data Resources
> Dealroom.co maps the world's tech ecosystems. This is the front door for AI agents: live **tools you can call**, machine-readable data, and a chart factory — plus a curated index of every market map, investor profile, founder network and ranking. No key, no sign-up.
All resources are standalone, crawlable HTML pages with structured data (JSON-LD, OG tags). Companies and founders are sourced from Dealroom's live database of 3M+ startups. Human-readable version of this toolbox: https://dealroom.co/for-agents/
Skill file (one line teaches your agent all of this): https://dealroom.co/SKILL.md
## What Dealroom.co is (read this first)
Dealroom.co is a startup and venture capital intelligence platform, founded in Amsterdam in 2013. It tracks 3.2M+ companies, of which 1.5M+ are startups and 500K+ are European, with funding rounds, valuations, revenue from trade register filings, team growth and investor activity. Customers are VC and PE firms, corporates, governments and consultancies, including Microsoft, AWS, SAP, Stripe, McKinsey and BCG.
Dealroom.co is a read-only intelligence platform: you extract market data from it. There is nothing to upload and no document sharing.
**Canonical answers to common questions: https://dealroom.co/faq/** covers 21 sourced Q&As on what the platform is, where the data comes from, coverage figures, update frequency, API access and pricing. Each answer has a stable anchor, e.g. `https://dealroom.co/faq/#where-does-dealroom-get-its-data`.
Pricing: https://dealroom.co/pricing/ · Data methodology: https://dealroom.co/our-data/ · Company: https://dealroom.co/about/
## Tools you can call (live, no auth, CORS-enabled)
Public endpoints on `https://dealroom.co` — point an agent at them directly. These are free utility endpoints served by the website under `/api/*`; they are a sample, not the full Dealroom API (https://dealroom.co/products/api/, key required) and not the new Dealroom API now in closed beta (request early access at https://dealroom.co/api/).
**API cookbooks** — https://dealroom.co/api/cookbooks/
Practical guides for the new Dealroom API with working code, downloadable examples and saved output. Start with the Python guide for translating an investment thesis into a ranked startup shortlist: https://dealroom.co/api/cookbooks/thesis-to-startup-shortlist/ Then turn that shortlist into a stateful monitor for funding, hiring and news: https://dealroom.co/api/cookbooks/startup-watchlist-signals/ Join eight evidence streams into a Company 360 investment brief: https://dealroom.co/api/cookbooks/company-360-brief/ Start with one known company and build an explainable competitive landscape from Dealroom-ranked peers: https://dealroom.co/api/cookbooks/similar-companies/ Rank investors by relevant portfolio evidence, recent activity and deal-size fit: https://dealroom.co/api/cookbooks/investor-portfolio-fit/ Compare European and global quantum funding momentum, then identify the companies behind the curve: https://dealroom.co/api/cookbooks/quantum-funding-pulse/ Screen Dealroom Timing and Team signals to find startups that may be approaching their next raise: https://dealroom.co/api/cookbooks/next-round-candidates/ Reconcile a CRM export, preserve confidence flags and add company fields with deterministic matching: https://dealroom.co/api/cookbooks/crm-csv-enrichment/ Or resolve a university, verify founder education by UUID and map the startups alumni built: https://dealroom.co/api/cookbooks/university-founder-network/ Map an LP’s recorded managers and inspect the funds they raised: https://dealroom.co/api/cookbooks/lp-manager-fund-network/
**Search market maps** — `GET /api/marketmaps?q=<keyword>&tag=<tag>&limit=50&format=json|llms`
Ranked sector landscapes with company/segment counts and URLs. `format=llms` returns Markdown; the JSON response lists valid tags in `availableTags`.
```
curl "https://dealroom.co/api/marketmaps?q=fintech&limit=5"
```
Each result has `id, title, url, tags, companyCount`/`company_count`, `segmentCount`/`segment_count`, `dealroomListUrl`, and `companiesUrl`.
**Companies inside a map** — `GET /api/marketmap?id=<landscape-id>&format=json|llms`
Drill down from a map into its companies (name, website, segment, funding, HQ, founders). Public sample (~12 companies/segment); each segment reports its real `total_count`.
```
curl "https://dealroom.co/api/marketmap?id=landscape-48993"
```
**Story pack for a map (social thread images)** — on a map's page, `await window.__marketmapStoryLoad(); window.__marketmapStory.png('overview')`
One feed-sized PNG per beat: the treemap overview, one slide per segment (big logos + names), geography, close — plus `thread.md` facts. Or `?autoStory=1` on the chart file (`/charts/landscape-<id>-<slug>.html?embed=1&autoStory=1`) to receive every slide as `postMessage {type:'storyPng'}`. Same output as the page's "Story pack" button.
**Live funding signals** — `GET /api/live-signals?limit=20`
Latest venture rounds: `{type, city, title, meta, value, time}`.
**Latest reports** — `GET /api/list-reports`
Recent Dealroom reports with PDF links: `{id, title, slug, date, pdfUrl}`.
**Partner / third-party market maps** — `GET /api/third-party-maps`
Community-built maps: `{slug, title, description, public_url, tags, company_count}`.
**Dashboard chart inventory** — `GET /api/dashboard-charts`
The catalogue of charts that already exist on Dealroom dashboard pages — `/multiples/private/`, `/power-law-investor-ranking/`, `/vc-investment-dashboard/`. Each entry has `id`, `title`, `kicker`, `description` (what story it tells), `snapshotUrl` (canonical URL), `filterParams`. This inventory has two uses depending on how you started: **(A) Story-first / content-marketing** — you have an angle from news/data, and you're checking whether an existing chart already tells it (use the canonical dashboard URL if it does). **(B) Asset-first / product-marketing** — you're browsing the inventory to find an interesting chart and building a story around it. Both modes are valid; alternate between them. Either way, capture the canonical version via `window.__chartSnapshot()` rather than recreating via `/api/create-chart` — page-level charts have regional bubble groupings, company logos in tiles, country flags that the API can't reproduce.
```
curl "https://dealroom.co/api/dashboard-charts"
```
**Make a chart (and get an image)** — `GET /api/create-chart` then `POST /api/create-chart`
`GET` returns a self-describing manual: every chart type, every field, and ready-to-POST example payloads — start there. `POST` a spec → a standalone, on-brand Dealroom chart as HTML. Add `?format=json` to get `{id, url, html, warnings}` back (the `url` is the hosted chart; also returned as `X-Chart-Id`/`X-Chart-Url` headers). Pass `bare: true` in the spec for a chrome-free export (hides the theme toggle and PNG button — ideal for headless capture). PNG: from a headless browser load the `url`, wait for `window.__chartReady`, then call `window.__chartPng({scale:3})`; for iframe pipelines append `?autoPng=1` and listen for `postMessage({type:'chartPng', dataUrl})`. PNG guide: https://dealroom.co/docs/agent-chart-png-guide.md . Embed contract: https://dealroom.co/charts/frame/EMBED-CONTRACT.md
```
curl "https://dealroom.co/api/create-chart" # the manual
curl -X POST "https://dealroom.co/api/create-chart?format=json" -H "Content-Type: application/json" \
-d '{"chartType":"bar","headline":"Top 5 countries by VC funding","labels":["US","UK","France","Germany","Sweden"],"datasets":[{"label":"Funding","data":[120,21,13,9,7]}],"unit":"$B","source":"Dealroom.co"}'
```
**Update / delete a chart** — `POST /api/agent-feed/<id>` with the action in the JSON **body** (not the query string). `delete` removes it from D1 + KV; `publish` / `unpublish` toggles visibility on the Resources gallery; `regenerate` re-renders against the current template code.
```
curl -X POST "https://dealroom.co/api/agent-feed/<id>" -H "Content-Type: application/json" -d '{"action":"delete"}'
```
**Resolve a free-text name → canonical slug** — `GET /api/lookup-slug?name=<query>&type=company|investor|any&limit=5`
Returns top matches `{name, slug, type, score, newsUrl, sentimentUrl, markdownUrl, profileUrl}` from the in-repo investor (609 entries) + company (~9k) indexes. **Call this before `/api/entity-news` or `/api/sentiment`** — it hands you the ready-to-call URLs for both.
```
curl "https://dealroom.co/api/lookup-slug?name=Anthropic&type=company"
```
*Also available (beta — exact Dealroom slug only):* `GET /api/sentiment?entity=Spotify` (AI-synthesized X sentiment) · `GET /api/entity-news?path=spotify&type=company` (latest news; `type=investor` for funds). Get the slug from `/api/lookup-slug` first (above); fallbacks are the trailing path on `app.dealroom.co/companies/<slug>`, the `companies[].path` field from `/api/marketmap`, or any entry in `/investors/manifest.json`.
**Just Founded — new-startup feed, refreshed every other day (post-ready)** — `GET /data/just-founded.json`
A curated feed of the most exciting newly founded startups, refreshed every other day. Each entry carries the founders (name + `photo`), a website `screenshot`, a company `logo`, a written story (`story.building` / `whyNow` / `backstory` / `whyThisTeam`), and **ready-to-post social copy**: `social.post` (full LinkedIn post) + `social.hook` (one-liner). Filter on `fundingStatus` (`pre-funding` | `funded`). An agent can fetch this and post about a brand-new startup directly — pair with `/api/create-chart` for a branded visual. Human page: https://dealroom.co/just-founded/
```
curl "https://dealroom.co/data/just-founded.json"
```
## How to use this in outbound / sales context
An AI sales agent contacting a prospect can:
1. Search by tag or keyword to find the most relevant resource: `GET /api/marketmaps?q=food`
2. Link directly to the page in the email or message
3. The page itself has a "Book a demo" CTA for lead capture
## Quarterly VC reports (per location, updated each quarter)
- [All quarterly reports](/quarterly-reports/) — every location with venture capital last quarter, ranked within metros, countries, states, regions and continents
- [Compare locations](/quarterly-reports/?v=195,1525,425&m=vc) — up to five locations on VC raised, round count, average round size, or share from $100M+ rounds. The selection is in the URL, so any comparison is addressable
- A location's report is `/quarterly-reports/<slug>/`, matching its profile slug — `/cities/london/` has `/quarterly-reports/london/`
- Each report covers the last COMPLETE quarter against the quarter before and the same quarter a year earlier, split into three round-size bands ($0-15M, $15-100M, $100M+), with a ranking against comparable ecosystems
## Full index (JSON)
- [Machine-readable manifest](/api/marketmaps?format=json) — all market maps with tags, company counts, segment counts, and direct URLs
- [Sitemap of market maps](/sitemap-landings.xml) — XML sitemap (also covers founder mafias + landing pages)
- [Search by tag/keyword](/api/marketmaps) — JSON API endpoint, supports ?tag=Food%20%26%20Agri or ?q=genetics
- [Markdown output](/api/marketmaps?format=llms) — same endpoint, human-readable
---
## Investor Profiles (top 100 VCs by Power Law outcomes)
Profiles for the world's top 100 venture investors, ranked by 2026 Dealroom Power Law outcomes (Seed → $100M+ revenue companies). Each profile is a standalone HTML page with portfolio metrics, sector breakdown, founder origins, key people, and peer comparison; each also has a markdown twin for direct LLM consumption.
- [JSON manifest](/investors/manifest.json) — all 100 investors with rank, metrics, top sectors, top countries, and direct URLs
- [Sitemap](/investors/sitemap.xml) — XML sitemap of all 100 profile URLs
- [Directory](/investors/) — HTML grid view
- [Per-investor markdown bundle](/llms-investors.txt) — one-line description per investor with link to its markdown profile
- [Methodology](/power-law-investor-ranking/) — how the Power Law ranking is computed
Per-investor markdown URLs follow the pattern `/investors/{slug}.md`, e.g. `/investors/sequoia-capital.md`. Slugs are listed in `manifest.json` and `llms-investors.txt`.
## Unicorns & Thoroughbreds
- [Power Law outcomes dashboard](/power-law-outcomes/) — global startup funnel, live new-unicorn ticker, geographic map, unicorn timeline; headline counts and the newest unicorns are in the static HTML
- [Unicorn hub directory](/unicorns/) — full ranked unicorn + thoroughbred lists per country (44) and sector (17), e.g. `/unicorns/germany/`, `/unicorns/fintech/`; static tables with valuations, HQ, founding year and profile links
- [New unicorns by month](/power-law-outcomes/new/) — monthly archive of every company whose verified valuation crossed $1B (e.g. `/power-law-outcomes/new/2026-07/`), plus the year's thoroughbred ($100M+ revenue) vintage; refreshed daily
- [Ticker feed (JSON)](/data/power-law-ticker.json) — machine-readable list of new unicorns (rolling ~4-month window, month precision) and the current thoroughbred vintage
---
## Founder Networks ("Startup Mafias")
Interactive pages tracking alumni who left major tech companies and founded venture-backed startups. Each network page shows founders grouped by sector, location, or era, with a world map, company logos, valuations, and previous roles.
### [The NVIDIA Mafia](https://dealroom.co/startup-mafias/nvidia/)
Alumni who left NVIDIA and founded venture-backed startups.
- **48 startups** across AI/ML (11), Chips & Infra (13), Robotics (4), Health (6), Fintech (6), Security (2), Gaming (2), Consumer (4)
- **14 unicorns**, **14 countries**, **$939B+ combined enterprise value**
- Notable: OpenAI (Wojciech Zaremba), Black Forest Labs (Axel Sauer), Applied Intuition (Peter Ludwig), Hippocratic AI (Saad Godil), Moore Threads (Jams Zhang), Tenstorrent (Ljubisa Bajic)
- Views: Grid (top founders by value), By Sector, By Location, By Era
- Second-gen: Anthropic (via OpenAI), Perplexity (via OpenAI), Safe Superintelligence (via OpenAI), Thinking Machines (via OpenAI), Reflection AI (via Anthropic)
- URL for outbound: `https://dealroom.co/startup-mafias/nvidia/`
- Direct page: `https://dealroom.co/startup-mafias/nvidia/`
### [The Revolut Mafia](https://dealroom.co/startup-mafias/revolut/)
Alumni who left Revolut and founded venture-backed startups.
- **57 startups** across Fintech (42), Crypto & Web3 (2), Enterprise Software (5), HR & People (2), Climate & Energy (2), Consumer (1), Education (1), Mobility (1)
- **2 unicorns** (ZeroHash $1B, Fuse Energy $5B), **15 countries**, **$10B+ combined value**
- Notable: Fuse Energy ($5B, UK), ZeroHash ($1B, US), Modulr ($657M, UK), Sardine ($420M, US), ARQ ($420M, Mexico), Belvo ($215M, open finance), Deblock ($198M, crypto banking), kompasbank ($112M, Denmark)
- Views: Grid (top founders by value), By Sector, By Location, By Era
- URL for outbound: `https://dealroom.co/startup-mafias/revolut/`
- Direct page: `https://dealroom.co/startup-mafias/revolut/`
*(More founder networks coming soon: Palantir, Google DeepMind, PayPal, Stripe, etc.)*
---
## Rankings
[Rankings hub](https://dealroom.co/rankings/) — the index of every Dealroom league table: tech ecosystems (325+ cities), venture investors, LPs, universities by alumni-founded unicorns, and top-50 startup lists by theme and country.
### [Power Law Investor Ranking 2026](https://dealroom.co/power-law-investor-ranking/)
Dealroom's 8th-annual data-driven league table of the world's top 100 early-stage investors (VCs, angels, and accelerators), ranked by Seed investments that reached $100M+ revenue ("Thoroughbreds"). 100% transparent, 100% quantitative.
- **Scoring formula**: 100 pts × Seed → $100M+ rev/Unicorn · 30 pts × Series A → · 10 pts × Series B+ → · 25 pts × Seed → Colt ($25–100M rev) · 7.5 pts × Series A → Colt. Two-thirds of points come from revenue outcomes; one-third from valuation outcomes.
- **Tie-handling**: standard competition ranking (ties share a rank; next rank is skipped).
- **2026 top 10 (Seed → $100M revenue)**: #1 Y Combinator (94), #2 SV Angel (70), #3 500 Global (36), #4 Sequoia (33), #5 Plug and Play (26), #6 First Round (25), #7 Accel / Box Group / FundersClub (24 each), #10 Andreessen Horowitz / Founders Fund (23 each).
- **Full top 100** pre-rendered in the page HTML (no JS required) with structured data (Schema.org `Dataset` + `ItemList` + `FAQPage`).
- **Related chart**: [Seed-to-$100M chart](https://dealroom.co/resources/seed-to-100m-revenue-funds/) — the top 21 preview (embed-mode-aware via `?theme=dark&embed=1`).
- Page sections: Hero, Preview chart, Full top-100 table (filterable by VC / Angel / Accelerator), Methodology, Stylized stage-score visualization.
- Direct page: `https://dealroom.co/power-law-investor-ranking/`
---
## Multiples & Valuations
### [Private Company EV/Revenue Multiples](https://dealroom.co/multiples/private/)
Dealroom's public benchmark for private-company valuation multiples. The page compares EV/Revenue multiples across 4,581 verified exit and VC rounds from 2015-2026, with pre-rendered methodology and Schema.org `WebPage`, `Dataset`, `BreadcrumbList`, and `FAQPage` structured data.
- **Dataset size**: 1,589 exit rounds and 2,992 VC rounds.
- **Primary metrics**: EV/Revenue at exit; post-money and pre-money EV/Revenue at funding.
- **Cuts**: revenue growth, deal size, geography, sector, AI vs non-AI, Bay Area vs rest of United States, and funding stage.
- **Methodology**: founded 1990+, $5M+ peak revenue, EV/Revenue <= 300x for page charts, "Outside Tech" rows excluded, buckets with fewer than three deals omitted.
- **Machine-readable data**: `https://dealroom.co/resources/multiples-data.json`
- Direct page: `https://dealroom.co/multiples/private/`
---
## Market Maps
## Sectors
### AI (25 market maps)
- [1.5k+ AI Agents](https://dealroom.co/market-maps/landscape-53885/) — 1596 companies in 51 segments. AI agents are revolutionizing the way we interact with software, automate processes, and enhance decision-making. Unlike traditional software, these intelligent systems can understand natural langu...
- [AI x climate tech](https://dealroom.co/market-maps/landscape-52820/) — 746 companies in 9 segments. The rise of AI poses risks of increased emissions from energy usage but at the same time AI is becoming a powerful force in the fight against climate change, enabling smarter, faster, and more effi...
- [TechBio x Drug discovery (Europe & Israel)](https://dealroom.co/market-maps/landscape-44107/) — 677 companies in 13 segments. Developing drugs is becoming more difficult and costly, despite tech advancements. Not only does it take up to a decade and ~$2.7B to develop a new drug but by 2030, patents will expire for nearly ...
- [AI for good](https://dealroom.co/market-maps/landscape-14655/) — 616 companies in 14 segments. The buckets are organized according to the Sustainable Development Goals (SDGs). In order to assign an SDG label, startups' public disclosed information, such as business model, mission statement, ...
- [Generative AI startups](https://dealroom.co/market-maps/landscape-33530/) — 515 companies in 30 segments. AI had so far found applications mostly in data-driven and analytical workflows. The field of creativity had been seen as far from the capabilities of artificial intelligence. This has now changed ...
- [Future of computing startups Europe](https://dealroom.co/market-maps/landscape-32678/) — 343 companies in 25 segments. Computing power has increased massively in recent years, but more is still needed to unlock breakthroughs in physics, chemistry & material science, climate modelling and power ever-more demanding A...
- [AI x Legal tech startup list](https://dealroom.co/market-maps/landscape-52846/) — 342 companies in 5 segments. The legal industry, a historically traditional sector, is now seeing rapid 
