# doany.ai — Investor One-Pager
**Confidential | April 2026**

---

## Company

**doany.ai** turns expert workflows into testable, reusable AI agents and distributes them through a marketplace where teams subscribe to domain-specific capabilities instead of hiring consultants.

Founded March 2024 | San Francisco, CA | 14 FTE

---

## Problem

Enterprises spend $340B/yr on professional services for repeatable knowledge work. Today's AI tools are horizontal copilots — they lack the domain specificity, quality benchmarking, and accountability that enterprises require.

## Solution

doany.ai discovers, packages, and benchmarks expert workflows ("skills") into plug-and-play AI agents. Each skill is version-controlled, content-addressed (SHA-256), and tested before listing. Teams buy what they need from a curated marketplace; skill authors earn 80% net revenue share.

---

## Traction (as of December 2025)

| Metric | Value |
|--------|-------|
| ARR | **$1.4M** |
| MoM revenue growth | **18%** |
| Paying teams | **220** |
| Enterprise contracts (>$50K ACV) | **16** |
| Avg enterprise ACV | **$54K** (expanding to $72K at renewal) |
| Skills published | **3,800** |
| Net revenue retention | **138%** |
| Gross margin | **81%** |
| CAC payback | **4.2 months** |

Customer logos: Ramp, Vercel, Anduril, Scale AI (pilots)

---

## Business Model

| Stream | Mechanism | Mix |
|--------|-----------|-----|
| Marketplace | 20% take rate on skill transactions | ~60% of revenue |
| Enterprise subscription | $299/seat/mo (unlimited runs, private catalog, SSO, audit log) | ~40% of revenue |

---

## Market

- **TAM**: $340B global professional services
- **SAM**: $48B developer tools + knowledge automation
- **SOM (Year 3)**: ~$620M — mid-market teams replacing 2-3 consulting engagements/yr with skills

---

## Team

| Name | Role | Background |
|------|------|------------|
| **Alex Chen** | CEO & Co-founder | Ex-Stripe PM lead (Billing & Revenue Recognition), Stanford CS '18 |
| **Priya Sharma** | CTO & Co-founder | Ex-Google DeepMind senior staff engineer, MIT EECS '16 |
| **Jordan Reeves** | Head of Growth | Built Notion's enterprise sales motion $2M to $18M ARR |
| **Maria Torres** | Head of Engineering | Ex-Databricks staff engineer, led MLflow team |

---

## The Ask

| Parameter | Value |
|-----------|-------|
| Round | **$3.0M Seed** |
| Instrument | Post-money SAFE |
| Valuation cap | **$28M** |
| Target close | **Q1 2026** |
| Committed | $800K in soft commits (operators at Stripe, Vercel, Databricks) |

---

## Use of Funds (18-month runway)

| Category | Amount | % |
|----------|--------|---|
| Engineering (5 hires) | $1.50M | 50% |
| Sales & go-to-market | $750K | 25% |
| Skill supply & partnerships | $450K | 15% |
| G&A / operations | $300K | 10% |

Post-hire team: 19 FTE | Monthly burn (post-hire): ~$195K

---

## Milestones to Series A (Target: Q3 2027)

- **$5M ARR**
- **500+ paying teams**
- **40+ enterprise customers**
- **Net revenue retention >130%**
- 10,000 published skills
- SOC 2 Type II certification
- Launch vertical catalogs: legal, finance, DevOps

---

## Why doany.ai Wins

| | doany.ai | Copilots | Zapier AI | Consulting |
|---|---|---|---|---|
| Domain-specific | Yes | No | Partial | Yes |
| Benchmarked quality | Yes | No | No | Varies |
| Scalable | Yes | Yes | Yes | No |
| Repeatable | Yes | Partial | Yes | No |