FINANCE

Angel Investor Deal Flow & Portfolio Valuation Intelligence

Evaluate deal flow with institutional rigor instead of fragmented gut feel.

Angel investor syndicates and seed-stage venture funds review thousands of startup pitch decks, cap tables, and founder financial projections annually, making deal evaluation highly fragmented. Steeped AI transforms these sources into a searchable investment intelligence layer. Investors can upload deck PDFs, financial model spreadsheets, founder communication logs, and historical portfolio metrics into a secure private environment, where the platform normalizes inconsistent financial metrics across industries and extracts revenue growth rates, burn multiples, and addressable market claims.

Automatically identify recurring business-model patterns, customer signals, market trends, competitive positioning, traction indicators, and potential risks across companies. By calculating relational metrics across past portfolio wins, angel groups can identify which pitch attributes and founder track records correlate with follow-on funding rounds, then generate research-grade deal memos with strict citations that sharpen thesis development and founder evaluation frameworks.

AI Report

Deal Pattern & Portfolio Drivers

This report analyzes 6 years of decks, cap tables, and outcomes, ranking what predicts a follow-on round.

Capital efficiency drives 44% of follow-on rounds,¹ rising to 53% when paired with strong retention² and outperforming raw growth rate by 1.9x.³

Unsupported market claims recur as a risk. They appear in 29% of passed deals,⁴ and 3 in 5 lack any bottom-up model.⁵

Enterprise RAG & Custom Search

Use Steeped AI's enterprise search engines to query years of decks, memos, and founder threads by meaning rather than keyword. Ask which traction signals preceded your best exits and get the exact deck pages back with citations, inside a secure private environment.

Data Preparation

Use Steeped AI's data preparation to standardize varying accounting formats, valuation metrics, and currency entries into a clean baseline for portfolio comparison. When every founder models ARR differently, Steeped AI reconciles them first, so cross-company comparison means something.

Models from 6 accounting formats were normalized

Currencies were converted to one reporting baseline

ARR, MRR, and bookings were mapped to one definition

Removed column "legacy_valuation" because 83% were blank

Duplicate deck versions for one company were merged

generating new dataset

NEW DATA

Relational Metrics

Steeped AI's automated metric breakouts calculate hidden connections between seed valuation multiples, capital efficiency ratios, and follow-on Series A success rates. Real deterministic math runs across every meaningful column pair before an investment committee ever opens the file.

Long Text or ID Examples

Trace any portfolio metric down to the deals behind it with long text or ID examples, with the exact lines from each deck or memo highlighted. A committee member reads the real evidence behind a thesis before the capital call, not a summary of it.

Examples

See Examples For

31% of "deal_memo" records cited capital efficiency over growth

"Seed round closed at 1.4M ARR with a lean team and no paid acquisition. Growth was steady rather than spectacular, which cost them two term sheets. Burn multiple hit 3.1x the quarter before the raise, flagged during diligence and corrected before the Series A."

select for memo

Column: deal_memoforfollow_on: Series A

The insights are already in your data.

Ask your data anything. Get real findings ranked by impact, with AI reports your team can present and share on the spot.