Partners read the top 15%. The other 85% still get fair analysis.
A mid-stage fund sees 200-500 inbound decks a month. Most get a four-second partner skim on a Sunday afternoon before the Monday pipeline call. The signal that could have turned into the next flagship investment usually dies somewhere between "too early," "wrong stage," and "I'll look at it tonight" — which means never.
Your AI deal flow triage agent reads every inbound the minute it lands. It extracts 20+ structured fields from the deck, scores each deal against your thesis, and routes Tier 1 to the right partner within 30 minutes. The other tiers don't get ignored — they get archived with full data so you can query the pattern later.
Your partners stop skimming. They start analyzing the deals that deserve an hour.
At 400 inbound decks a month, "skim everything" stops being a strategy.
A partner at a mid-stage fund typically gets 400-600 inbound decks a quarter across their sector focus. Even at a brutal four-second skim per deck, that's five to seven hours of pure pitch-scrolling per partner per quarter — and the scroll happens on Sunday afternoon before the Monday pipeline meeting, with a tired brain, on a phone. The decision of what to take seriously is effectively random by hour three.
The deals that actually deserve attention get lost in the 85% that didn't. And the 85% that didn't deserve this week's attention still contain signal you'd want to query a year later — "any devtools company we saw in Q1 that hit $500K ARR by Q3?" — except nobody saved structured data when they hit "archive." All that pattern-recognition gold compounds into nothing.
20+ structured fields pulled from every deck. Even the messy ones.
The agent reads PDF decks, Notion pages, DocSend viewers (where you have access), Figma files, and plain-text email pitches. For each one it extracts 20+ structured fields: stage, ARR, team headcount split (engineering, GTM, ops), customer count, sector and sub-sector, ask amount, round structure, key hires and their pedigree, and the traction metrics founders are leading with.
Decks that don't follow a standard template — the ones with ARR buried on slide 17 or team size in a footnote — get the same treatment as the clean ones. Nothing escapes extraction because the deck was ugly.
Tier routing is rubric-driven, not black-box. You see the score components.
During deployment we translate your thesis into a scoring rubric: stage fit, sector match, traction thresholds, team signal markers, ask-size alignment. Every deal gets a 0-100 score plus the component scores that built it — so when a partner disagrees with a tier assignment, they can see exactly which signal the agent over-weighted and mark it wrong. The agent learns from every correction.
Tier 1 (top ~15%) routes to a partner's Notion queue for a same-day look with a Slack DM. Tier 2 (next ~25-30%) batches into the weekly pipeline review deck. Tier 3 (remaining 55-60%) archives with full extracted data — searchable, pattern-analyzable, never in anyone's way.
The partner who needs to see it, sees it — within 30 minutes of inbound.
Tier 1 deals hit the matched partner's Slack DM within 30 minutes of the deck landing in your inbox — with a one-paragraph summary, the thesis fit score, the component breakdown, and a one-click Notion link. Partners read on the commute, reply on the commute, decide on the commute. No more "I'll check the deck inbox tonight" that slides into next week.
For warm-intro deals, the SLA drops to 10 minutes — because a portfolio founder who makes an intro deserves faster-than-cold response speed. The agent knows the difference.
Three questions every GP raises first.
Won't this screen out unconventional founders?
Every deal gets a one-paragraph summary and full structured data extracted — even Tier 3 archives. Partners can search the archive at any time ("any healthtech at $3M ARR we saw in Q1?") and surface deals the initial routing may have missed. The agent's job is prioritizing attention, not gatekeeping your pipeline.
How do we prevent bias in the scoring rubric?
The rubric is trained on your firm's actual last 12 months of decisions — investments AND passes — not on industry defaults. Partners review and adjust the rubric weights during deployment, and every tier assignment shows the component scores so disagreements surface immediately. The agent learns from corrections, not from a black-box model.
What if we want two partners to see the same deal?
Partners can be tagged on any Notion card and the agent routes to primary + secondary matches for cross-sector deals. Any partner can claim or redirect with one click. Your internal process stays intact — the agent just eliminates the "who saw this?" Slack thread that usually follows every ambiguous deal.
AI deal flow triage — answered.
What formats can the AI deal flow triage agent read?+
PDF pitch decks, Notion-linked decks, DocSend viewers (where you have access), Figma files, and plain-text email pitches. For DocSend specifically, the agent uses your firm's existing viewer access — it doesn't try to bypass access controls. If a founder shares a deck you can't open, the agent flags it for manual access rather than guessing.
How does the agent know our investment thesis?+
During deployment we ingest your written thesis document (if you have one), your last 12 months of investment decisions (both passes and investments), and a short conversation with each partner about what they personally weight. The agent builds a scoring rubric from those signals — stage, sector, traction thresholds, team signal patterns — and calibrates as partners mark its tier assignments right or wrong over the first 30 days.
Won't the agent miss unconventional deals that don't fit the thesis?+
Every deal gets a written summary regardless of tier. Even Tier 3 archives include a one-paragraph summary and the extracted data, so a partner can search later ("any healthtech with $3M ARR from the last six months?") and surface anything the initial tier-routing missed. The agent's job is to prioritize attention, not to gatekeep the pipeline.
How does the agent handle warm-intro deals differently from cold inbound?+
Warm intros get a bump: any deal from a source your firm has previously co-invested with, or where a portfolio founder made the intro, gets pre-routed to the partner closest to the intro source. The signal of warm-vs-cold is surfaced on every deal so partners can factor it into review weight — not applied as a hard override.
Can multiple partners see the same deal in their queue?+
Yes. For deals that cross multiple partners' sectors, the agent routes to the primary match and tags secondary partners on the Notion card. Partners can claim or redirect with one click. The routing respects your internal process — no deal ever sits in a "nobody's" queue by accident.
What happens to the 85% of deals that don't make Tier 1?+
They archive with full structured data — ARR at time of pitch, team size, stage, sector, the deck itself, and the agent's score rationale. This builds a searchable history your partners can query later: "what healthtech at Series A did we pass on in Q1?" Many firms use that archive for pattern analysis on thesis drift and missed opportunities.
How much does AI deal flow triage cost?+
Included in every beeeowl deployment tier, starting at $2,000 for Hosted Setup. One-time payment — no per-deck fee, no per-partner charge, no per-deal cost. See the pricing page for the full breakdown.