Financial statement analysis, traced to the filing.
L3i Data turns SEC EDGAR filings for roughly 8,300 public issuers into structured financials, ratios, and comparables — and lets you query all of it in plain language, with every answer cited back to the source filing.
Apple's operating margin — operating income ÷ revenue — expanded steadily over the last three years, from 29.8% to 32.0%:
Coverage is stated precisely, not rounded up. Structured financials begin with XBRL tagging in 2009, with full-text keyword search across the filing archive. Filing types include 10-K, 10-Q, 8-K, proxies, Form 4, 13F, 13D/G, and S-1 — enriched with FRED macro series and Census business-formation data so a company reads against its market.
Ingest once. Analyze every way.
The filings are normalized a single time, then reused across every view — so a ratio, a trend, a peer set, and an AI answer all resolve to the same audited source. No re-keying, no drift.
Read the statements, build the comparables, ask the question.
The financial-statement layer is normalized once and reused everywhere — so a ratio, a peer set, and an AI answer all resolve to the same audited source.
Structured financials & ratios
Normalized income statement, balance sheet, and cash flow for ~8,300 issuers, with derived ratios computed consistently across companies and periods — no re-keying from PDFs.
Comparable-company screening
Build peer sets from disclosed financials and generate interquartile ranges on the margins and returns that matter, with each comparable tied to the filing it came from.
Ask in plain language
Pose a question the way you’d ask a colleague. L3i returns a direct answer grounded in the filings, with citations to the exact passage — not a general-purpose guess.
Filing browser & full-text search
Move from a screen to the underlying document in one step: 10-K, 10-Q, 8-K, proxy, Form 4, 13F, 13D/G, and S-1, all full-text searchable.
From one company to a whole industry.
Roll a peer set into a single size-weighted industry markup — the pricing-power lens behind the De Loecker / Roosevelt Institute studies — and track it across years, so one firm’s cost shock doesn’t distort the read.
Why size-weight?
Weighting each firm by its share of industry sales reflects real pricing power — a few dominant firms move the aggregate. The same five-firm set reads very differently three ways:
Tracked over years
Illustrative peer set on the COGS + SG&A basis; each markup traces to the firm’s 10-K. Apple’s 60.3% is computed from its FY2023 filing.
A defensible range, with outliers flagged.
The interquartile range is the standard way to set an arm’s-length band — it keeps the central distribution and drops the extremes. L3i builds the range from your comparables and flags anything beyond the Tukey fence, so a single outlier can’t quietly stretch your position.
Illustrative comparable set on the COGS + SG&A basis. The same range can be built on asset-adjusted bases — operating ROA or the Berry ratio — for cross-industry comparability.
Same data foundation, whichever way you work.
Browse & screen
A company and filing browser with screens and comparable sets, built for analysts who want to move fast without writing code.
Pull it into your stack
Query normalized financials and citations programmatically and drop them straight into your models and pipelines.
Query in plain language
A natural-language layer over the same corpus that answers with source-traced citations — so the reasoning is auditable, not opaque.
The answer is only useful if you can stand behind it.
Every figure is traced to the filing it came from and carries a reliability verdict — so the reasoning is auditable, not a black box.
Source-traced by design
See your own coverage, on your own tickers.
Walk through L3i Data with your companies loaded, and see the citations resolve to the filings you already know.