Product build ยท Financial services

An AI equity research platform that cites every claim

Enter the ticker of a US-listed company and the platform reads five years of filings, earnings call transcripts and market data, then writes a cited memo with growth signals.

Client
Built for boutique funds, family offices and registered advisers
Engagement
Platform build, data pipeline through research interface
Our role
Architecture, backend, ingestion, agent design, front end
Status
Full application delivered and reviewed end to end
Document types per company: 10-K, 10-Q, proxy statements and earnings call transcripts

4

Years of financial history analyzed per ticker

5

Every memo claim linked to its filing, transcript line or stored figure

Cited

For an analyst to check a memo, instead of redoing the research

Minutes

In brief

Analysts at smaller institutions covering US-listed companies need the depth of a large research desk on a fraction of the budget, which means reading every filing, transcript and data series for every name, every quarter. Involabs built a research platform that starts from a ticker, pulls five years of 10-K and 10-Q filings, proxy statements, earnings call transcripts and market data, and has an agent write investment memos against one fixed analytical framework. Every claim in a memo traces back to a filing, a transcript line or a stored figure, so an analyst can check a memo in minutes instead of redoing it.

Architecture

How it works

  1. Ingest

    Sources per ticker

    • 10-K, 10-Q, proxy
    • Earnings call transcripts
    • Yahoo Finance prices and ratios
  2. Process

    Normalize and index

    • Vector index per document class
    • Five years of financials in Postgres
  3. Reason

    Research agent

    • Cross-source synthesis
    • Historical trends and growth signals
    • Memo against a fixed framework
  4. Deliver

    Research interface

    • Watchlists per analyst
    • Cited, exportable memos
    • Universe dashboard
Every generated claim resolves back to a filing, a transcript line or a stored financial.

The situation

Analysts at smaller institutions covering US-listed companies need the depth of a large research desk on a fraction of the budget. The raw material is public: 10-K and 10-Q filings, proxy statements, earnings call transcripts and market data. The work is reading all of it, consistently, across several years of history, on every name in the universe, every quarter.

What we built

  • Start from a ticker. An analyst enters the ticker of a US-listed company. The platform pulls its 10-K and 10-Q filings from SEC EDGAR, proxy statements and earnings call transcripts, and stores them behind an abstraction that swaps local storage for cloud object storage without touching calling code.
  • A financial layer. Five years of prices, statements and ratios from Yahoo Finance, normalized into Postgres, so the research agent reasons over stored numbers rather than re-fetching under load.
  • Synthesis across sources. The agent reads the filings, the earnings call transcripts and the market data together, so a memo weighs what management said alongside what the reported numbers show.
  • Insights and growth signals. Five-year trends in revenue, margins, cash flow and balance sheet strength, turned into forward-looking signals on growth, risk and capital allocation, each tied back to the source that supports it.
  • A memo engine. Investment memos generated against one fixed analytical framework, so two names written up a month apart are comparable.
  • A research dashboard. Watchlists, a top-100 universe with benchmark, market overview, a filings browser and rendered memos in one interface.
  • Session security. Signed tokens in HTTP-only cookies; every dashboard route is refused without a valid session.

How it is engineered

A single application with one API process, one Celery background worker, one Postgres database and one Redis cache. Long-running ingestion and generation run as queued tasks rather than inside a request, which is what lets a heavy research job survive a page refresh.

Why it matters

Auditable output is the difference between a research tool and a plausible paragraph. Because every claim traces back to a filing, a transcript line or a stored financial, an analyst can check a memo in minutes instead of redoing it.

Have a similar problem?

Send us the problem and the constraints. We will tell you what it would actually take, starting with a fixed-scope assessment.