Company Profile
AI Due Diligence for Venture Capital
See What You're
Actually
Investing In.
The AI workspace where VC teams run structured due diligence — configured around how each fund actually invests.
"Every capital allocation decision in early-stage investing is made with complete, unbiased information about the people and markets behind it — not just what a well-networked analyst happened to surface."
The Problem
Early-stage VC diligence
is structurally broken.
Analysts get 2–10 hours per deal. Funds see 200+ inbound startups a month. Reference checks are curated by founders. Competitive pressure to move fast creates systematic under-diligence — and two costly failure modes that no existing tool is built to prevent simultaneously.
200+
Inbound startups per month at a typical early-stage fund
2–10h
Hours an analyst gets per deal for first-pass diligence
0
Tools purpose-built for claim verification and cross-source conflict detection
Failure Mode 1 — False Positives
Funding the wrong people
Early-stage traction is easy to manufacture. Vanity metrics, curated reference lists, inflated prior exit narratives — a motivated founder can construct a compelling signal picture without the underlying substance. Investors evaluating at speed, without structured verification, are routinely misled. Not because they're credulous, but because the signals are designed to deceive and the tools to verify them don't exist in one place.
Failure Mode 2 — False Negatives
Missing the right people
Genuinely exceptional founders who are first-timers, outside the network, or from underrepresented geographies produce weak online signals. Pattern-matching on surface signals — pedigree, prior exits, familiar schools — systematically screens out the best deals a fund never saw coming. The best deal a fund ever passed on is often invisible in their post-mortems.
Existing tools automate the shallow layer — CRM enrichment, news alerts, data lookup. Nothing is built around claim verification, cross-source conflict detection, and thesis-aware synthesis. Nothing is designed to reduce both failure modes at once.
The Solution
Meet NEO —
your AI diligence analyst.
One Agentic is an AI workspace where VC teams — partners and analysts together — run structured due diligence on startups. The product combines automated enrichment, a thesis-aware evaluation engine, and a human-directed AI agent to produce a sourced, structured picture of every opportunity — specific to how each fund actually invests.
Pillar 1
Thesis Capture
Each fund encodes its investment thesis — stage, target markets, team profiles, the signals they weight, and what they've decided not to invest in. Every deal is evaluated against that lens, not a generic checklist. The output is never "this is a good startup." It's "this fits or doesn't fit your thesis, and here's why."
Pillar 2
Automated Enrichment
NEO enriches every deal automatically — founder background signals, company context, market references, public records, court filings, regulatory databases, and IP records. Synthesized into a structured, sourced output in minutes, not hours.
Pillar 3
Signal Verification
When independent sources tell different stories about the same fact, the product flags it explicitly, with sources. A claimed exit that doesn't match public filings. A role that appears in one source and disappears in another. NEO surfaces conflicts; the investor decides what to do with them.
Not a decision engine. The investment call is always the investor's. NEO does the hours of research in minutes — the VC directs every step.
What it is not: a replacement for human judgment · a general AI research assistant · a portfolio monitoring tool · a tool for founders · a data vendor
For the Analyst
Eliminates 40–60% of repetitive research time. Produces sharper, sourced output for partner meetings — without the last-minute scramble.
For the Partner
Trusted, structured output that can be relied on without configuring anything, reviewing raw research, or asking an analyst to start over.
How It Works
Inbox to decision-ready
in 20 minutes.
A deal enters through any path. NEO runs the research, surfaces conflicting signals, and the VC reviews and directs next steps — in plain language. The loop continues until the team has enough to decide. Every external action NEO takes is at the VC's direction.
1
Deal enters through any path
A pitch deck, a company URL, a founder name, or a structured intake form. The product extracts what it needs from whatever it receives — no reformatting required.
2
NEO enriches automatically
Founder background signals, company context, market references, public records, court filings, regulatory databases, intellectual property history, and commercial signal data — all synthesized against the fund's thesis in one structured output.
3
Conflicting signals surface
When independent sources disagree on the same fact, the product flags it explicitly, with sources. Each flag is specific and attributed — not a generic warning that something seems off.
4
The VC reviews and directs
Partners and analysts review the structured output together and decide what to explore next — in plain language. NEO drafts any outreach; the VC sends. The fund stays in control of every external action.
5
Loop continues until decision-ready
NEO executes, returns with results, the VC reviews again. The loop continues until the team has enough to make a call — or pass with confidence. Every deal gets a complete first look.
For the Fund
Consistent diligence depth across every deal — not dependent on who ran the check or how busy the week was.
Workflow Design
Funds configure their own diligence workflow conversationally through NEO. Pre-built templates available as starting points.
Human-Directed
NEO runs enrichment automatically. Every subsequent action — outreach, deep dives, follow-up — requires explicit VC direction.
The Difference
Four things that are
actually defensible.
Verification Depth
The differentiation is not in aggregating data — any analyst can aggregate. It's in detecting what's been manufactured, omitted, or contradicted across independent sources. That's a judgment problem we can encode, and it compounds with every deal run through the platform.
Genuine Simplicity
A partner with no technical background reaches a trusted output without configuration or help. Every layer of setup, every prompt they have to write, every integration they have to maintain, is a reason to stop using a product. Simplicity is a real moat in this market.
Trust as the Product
Usefulness is the floor. Trust is the ceiling. The product only creates value when a partner puts the output in front of a Monday meeting and stands behind it. That requires consistency and a clear audit trail — not just accuracy on easy cases.
Distilled VC Knowledge
A general model can research a founder. It cannot do it through the lens of a seed-stage investor running a thesis-driven fund. Our framing reflects how VCs actually think, what signals matter at pre-seed, and what a well-prepared deck was specifically designed to avoid.
How We Position
| Tool |
What it does well |
The gap we fill |
| One Agentic |
Thesis-aware evaluation · claim verification · cross-source conflict detection |
— |
| Harmonic |
Best-in-class sourcing & top-of-funnel discovery |
Not built for deal evaluation. No structured risk assessment or thesis fit. |
| Affinity |
Dominant CRM; deep relationship & network intelligence |
Pre-investment evaluation is not a supported workflow. Knows who you've talked to; not what you're investing in. |
| Clay |
Flexible enrichment, cheap to start, wide data source coverage |
No VC-specific structure, no thesis awareness, no output a partner trusts without manual assembly. |
| Generic AI |
Fast, free, capable for basic research tasks |
No VC framing, no persistent deal context, no proprietary data, inconsistent output. |
Business Model
Built for VC teams
of every size.
Tiered subscription with a shared monthly credit pool per organization. Credits are consumed as workflows run — a standard diligence pass draws less, a deep research session draws more. Shared at the org level, not locked to individual seats.
Seed
Solo investors and small emerging funds. 2 seats, shared credit pool sized for low deal volume. Self-serve.
Series
The standard early-stage fund in active deployment. 5 seats, credit pool for typical deal flow. Self-serve.
Max
High-volume funds. Unlimited seats, large pool for sprint periods, priority support. Self-serve.
Enterprise
Custom contracts, SSO, CRM integrations, dedicated CSM, API access. Annual contract, custom pricing.
~$2,100
Estimated avg annual spend — typical 5-person fund
4K–8K
Actively deploying early-stage funds globally
+66K
Active angel investors running the same core diligence workflow
Get Started
Run your first deal with an AI analyst at your side.
We're onboarding pilot customers now — VC teams running One Agentic on real deals before opening billing. We'll map the platform against your last few completed deals to show what it would have surfaced. A proof point, not a demo.
Contact
Mohamed Baddar
baddar@oneagentic.us
Stage
Pre-Seed · Core workflow functional end-to-end
Target: 3 pilot customers on real deals before opening billing
Focus
Pre-Seed through Series A funds
1–15 person teams · 50–200+ inbound deals/month