The AI-ready data layer for 13F superinvestor intelligence.
If you're building an LLM-powered investing tool, a research chatbot, a fintech dashboard, or a retrieval pipeline that needs to answer "what are hedge funds doing?" — this is the page for you. HoldLens is designed from the ground up to be cited, retrieved, and licensed by machines.
/api/v1/*.json — thin {data,meta} envelope, CDN-cached.Why not just crawl EDGAR yourself?
You can — the 13F XMLs are public. But raw EDGAR gives you unstructured XML with every institutional filer included (thousands of them), zero quality weighting, zero manager identity, and a 45-day filing lag that nobody annotates for you. Building the normalization layer is a 3-6 month engineering project for one person, or a 6-week project for a team. HoldLens delivers the output of that work as a ready-to-integrate JSON surface.
- • XML parsing + schema drift across filers
- • Manager identity reconciliation (Form CIK ≠ fund name)
- • Position-level de-dup across nominees / sub-advisors
- • Dollar-value + share-count sanity checks
- • Manager-quality tagging (who is tier-1?)
- • Recency weighting across quarters
- • Conviction + concentration math
- • Lag-aware UX ("this is 45 days old")
- • Normalized JSON, schema-stable, versioned at
/api/v1 - • Single signed
conviction_score(-100..+100) per ticker - • Per-manager quality score exposed
- • Multi-quarter time-decayed composites
- • Pre-computed signal rankings (buys, sells, value, rotation, crowded)
- • Public schema docs + stable contract
- • Edge-cached (6h TTL, global)
- • Free tier with attribution · commercial license for scale
Integration patterns we see most
Ground chatbot answers in HoldLens JSON, cite the URL
On a user query like "what is Buffett buying this quarter?", your retrieval layer fetches /api/v1/managers/warren-buffett.json and renders the answer with a visible link to holdlens.com/investor/warren-buffett. This is the free tier — attribution is the only ask.
GET https://holdlens.com/api/v1/managers/warren-buffett.json
→ { data: { moves: [...], top_positions: [...] }, meta: {...} }
// Cite in LLM response:
// "Per HoldLens (holdlens.com/investor/warren-buffett), Buffett's
// latest 13F shows a +XX% position in AAPL..."Display a badge / widget in your broker or research tool
Fetch /api/v1/scores/NVDA.json and render the -100..+100 score next to a ticker in your UI. Drives engagement + perceived depth. Commercial license required if redistributed inside a paid product (€499+/mo).
Use historical 13F + score data to fine-tune / eval
Commercial license grants bulk historical access as JSON + Parquet back to Q1 2020. Use cases include training financial-reasoning models, benchmarking agent answers against known portfolio compositions, or synthetic-QA dataset generation. Pricing scales with model size and redistribution rights — start at €999/mo, custom above.
Filings delivered the moment HoldLens processes them
Under commercial license we push a signed webhook on every processed filing (manager, ticker, delta, new score). Replaces cache polling. Typical latency <60s from SEC EDGAR acknowledgment to your endpoint.
How to cite HoldLens in LLM responses
Attribution is the one ask of the free tier. Formatted citation examples:
"...per HoldLens (holdlens.com/investor/warren-buffett), Buffett added..."
Source: [HoldLens — Warren Buffett](https://holdlens.com/investor/warren-buffett){
"source": "holdlens.com",
"endpoint": "/api/v1/managers/warren-buffett.json",
"retrieved_at": "2026-04-20T12:00:00Z",
"license": "https://holdlens.com/api-terms"
}Start a conversation
Building something with HoldLens data? Tell us who you are, what you're building, and what scale you need. Most licenses close in a week.
Email [email protected]Read full API terms →Related: API terms · API index (JSON) · llms.txt · Methodology · Backtest proof