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ValueinValuein
For sell-side & buy-side analysts

Spread any 10-K in seconds — not hours.

Spreading a single filing by hand eats hours and the copy-paste tax never ends. Get standardized, point-in-time financials that drop straight into your model — every number cited back to the filing it came from.

  • Standardized line items across 19,000+ companies — one canonical Revenue, EBIT, FCF.
  • Point-in-time accurate: see exactly what was reported, before any restatement.
  • Variance tables ready the moment a print drops — actual vs. estimate vs. prior.
  • AI co-analyst drafts your first-take note with citations, not guesses.

Built for

Financial Analysts

  • Point-in-time accurate
  • Survivorship-bias-free
  • Every number cited to its filing

Works where you do

WorkspaceMCP ServerPython SDK
Recommended plan
Pro

Point-in-time accurate · Survivorship-bias-free · Every number cited to its filing

Hours → seconds
to spread a filing
30-min
earnings clock, beaten
~286
canonical concepts from raw XBRL

The pain points we remove

Analysts spend 25-75% of their week in Excel — and far too much of it re-keying numbers a machine should hand them. These are the recurring frustrations Valuein removes.

1

The copy-paste tax

Pulling line items out of a 10-K and 10-Q into a model is manual, slow, and error-prone — hours to days per name, every quarter, forever.

2

The 30-minute earnings scramble

When the print lands you have ~30 minutes to publish a first-take with a variance table. There's no time to re-key the numbers by hand.

3

Restatements break comparability

Companies restate and line items move. Reconciling side-by-side quarterly history out of EDGAR is tedious and easy to get silently wrong.

4

Inconsistent XBRL tagging

The same disclosure is tagged differently across filers, so raw SEC data needs heavy processing before it's usable in a comparison.

5

Siloed tools, manual refreshes

Switching between PDFs, CSVs, and a half-dozen apps — with no self-service refresh — costs thousands of hours a year you'd rather spend on the thesis.

Built around your actual cadence

From the daily grind to the month-end crunch — Valuein fits the rhythm of the work, not the other way around.

Every day
  • Read 8-Ks and news on covered names
  • Tweak model assumptions and answer PM/client questions
  • Pull a quick fundamental or ratio to settle a debate
Every week
  • Refresh comps tables with consistent definitions
  • Track consensus and estimate revisions
  • Draft and refine thesis notes
Month / quarter-end
  • Spread every covered name's new 10-Q/10-K
  • Publish first-take notes within minutes of the print
  • Re-rate price targets and refresh the model suite

What you can do with Valuein

Each job you need done, mapped to the exact capability that delivers it.

Spread a company's financials instantly

Standardized, point-in-time facts ready to drop into a model — no scraping, no copy-paste.

Python SDK · Bulk Data API

Build a variance table the second a print lands

compare_periods + get_earnings_signals surface actual vs. prior in one call.

MCP · Workspace

One-click comps across a peer set

get_peer_comparables + generate_comps_xlsx export a branded comps workbook.

MCP · Document generation

Draft the first-take note from the data

Your BYO-LLM agent writes the note with every figure cited to its filing via verify_fact_lineage.

Workspace · MCP

Catch restatements automatically

Point-in-time history exposes original-vs-amended values so nothing changes under you.

Datasets · verify_fact_lineage

Spread any 10-K in seconds, not hours — standardized, point-in-time, cited to the filing.

When the print drops, your variance table is already built.

Stop paying the copy-paste tax. 105M+ standardized facts, straight into your model.

Frequently asked

How is this different from copying numbers out of a 10-K myself?

Valuein delivers the line items already standardized to canonical concepts across all filers, point-in-time accurate, and traceable to the source filing — so you skip the spreading entirely and drop them straight into your model via the SDK, MCP, or Workspace.

Can I generate a comps table or research brief automatically?

Yes. The MCP server's get_peer_comparables builds a peer set on demand, and generate_comps_xlsx / generate_research_brief_docx export branded Excel and Word documents (Pro tier and up).

Will my numbers reconcile to the actual SEC filing?

Every fact carries its source. verify_fact_lineage returns the exact filing, accession, and context for any number, so your note is auditable line by line.

Do I need to write code?

No. The Workspace gives you an AI chat and a report editor in the browser. The Python SDK and Bulk Data API are there when you want to wire data into Excel or a model pipeline.

Spread any 10-K in seconds, not hours — standardized, point-in-time, cited to the filing.

105M+ standardized SEC facts across 19,000+ companies, 1993–present. Free to start — no credit card.