We build AI employees for businesses ready to scale.
Fully managed, custom-built AI agents — deployed in weeks, run by us, measured by your outcomes.
Ben Valentin, CEO · ben@madewell.ai
Team
Built by operators who build AND sell.
Ben Valentin
CEO / CTO
Army veteran turned technical founder. Built Madewell from $0 to ~$40K/mo revenue in 9 months while writing production code, architecting AI systems, and closing deals. Fills both CEO and CTO roles — saving the company a $150-180K senior technical hire.
Christian Damico
Head of Sales
Founding GTM at HappyRobot, a well-funded AI startup where he built the enterprise sales motion from scratch. Experienced enterprise AE with a track record of closing complex, multi-stakeholder deals. Launching Madewell's cold calling program April 2026.
Chris Damico
CSO / CMO
Serial entrepreneur with multiple successful exits. Leads GTM strategy, investor relationships, and brand positioning. Brings operator experience from scaling early-stage companies through the messy middle — the exact stage Madewell is in now.
Chad Burwick — Product Manager
Owns the discovery-to-deployment pipeline for every client
Doug — Head of GTM
20-25 raw appointments/mo with 50-60% qualification rate
Problem
AI adoption is broken.
Businesses are drowning in tools but starving for outcomes.
Manual work is compounding
Mid-market businesses ($5M-$50M) are buried in operational work that doesn't scale with headcount. They hear about AI but can't translate hype into business value.
Hiring cannot keep pace
Talent is scarce and expensive. Every new FTE adds management load and slows execution. 6M US businesses with 10-500 employees face this exact constraint.
Generic AI fails in the wild
Self-serve AI tools stall without technical ownership, integration work, and ongoing tuning. 85% of AI projects fail to reach production.
6M
US businesses with 10-500 employees
72%
say AI is a priority but don't know where to start
85%
of AI projects fail to reach production
Unique Insight
Companies treat AI adoption like buying software.
But it actually works like hiring a new team member.
Because AI adoption isn't a technology problem. It's a people and process problem.
Buying Software
- Evaluate features, pick a vendor, install it
- One-time purchase decision
- If it doesn't work, switch vendors
Hiring a Team Member
- Understand the role, train on your processes, integrate with the team
- Ongoing relationship that deepens over time
- Success depends on fit with your specific business
Every AI tool company optimizes features. We optimize outcomes.
Competitive Landscape
The entire industry optimizes the wrong layer.
AI SaaS Tools
ChatGPT, Jasper, etc.Generic tools not customized to business workflows. Employees don't know how to use them. No integration with existing systems.
Big Consultancies
Accenture, Deloitte, etc.$500K+ engagements, 6+ months to deliver. Reports and recommendations, not production systems. Inaccessible to mid-market.
DIY / No-Code
Zapier, Make, etc.Can't handle complex workflows. Break when processes change. No AI intelligence layer.
Freelancers
Upwork, referralsInconsistent quality. No ongoing support. No strategic thinking or product vision.
ChatGPT, Accenture, and Zapier each optimize one layer. None of them build custom AI employees that do specific jobs for specific businesses.
Solution
We find where AI has the highest leverage and build it into your operation.
Discovery
Technical discovery call with the client's team. Understand workflows, pain points, and where AI has the highest leverage.
Build
Custom AI agents built specifically for their business — not templates, not off-the-shelf. Real production systems deployed in ~15 days.
Deploy & Manage
We operate what we ship: reliability, monitoring, and iteration are part of the service. The AI becomes a permanent part of their operation.
Product screenshots — agent dashboard, deployment flow, client portal
Case Study
WedLaunch AI
Our first vertical platform — proving the productization thesis.
We built a custom AI employee for a wedding venue — automated lead follow-up, scheduling, and vendor coordination. It worked so well we productized it into a vertical SaaS platform for the entire wedding industry.
How it works
The CRM is free. The AI employee add-on is $2K/mo — handles lead qualification, follow-up, scheduling, and vendor coordination autonomously.
Why it matters
Every custom build reveals patterns. WedLaunch proves we can turn a one-off project into a scalable, high-margin recurring product. This is the playbook for every vertical we enter.
$2,500/mo
MRR from first client
~80%
Gross margin
Minutes
Response time vs. days industry avg
$2K/mo
Target per-client MRR at scale
Traction
We have receipts.
Monthly revenue
~$40K/mo
Pipeline
$270,000+
38 deals
Locked MRR
$7,650/mo
Cold outbound
211K emails
1,717 replies
Qualification
50-60%
vs. 25-30% industry
Named pipeline
Maze Freight
$36,000
Millenium Logistics
$31,000
Stutsman
$30,000
DataRemote
$30,000
Connext
$30,000
Cadence Sports
$30,000
Elite Technical
$25,000
Contender
$25,000
Go-to-Market
Services fund the product. Product creates the moat.
0–6 months
Services cash engine
Fixed-fee AI agent builds ($20–30K average). Higher revenue, ~70% margins. Funds product and GTM.
6–12 months
Vertical platforms
Productize winning patterns into vertical platforms. WedLaunch is first ($2K/mo MRR, 80%+ margins, Meta Ads acquisition).
12–24 months
Multi-tenant agent platform
Maia Platform: enable other businesses to build and run agents on shared infrastructure—expanding TAM while keeping services velocity.
Cold Email (Doug)
Live since Jan 2026
Cold Calling (Christian)
Launching April 16, 2026
Paid Meta Ads
Launching with SAFE funds
Content & Referrals
Ongoing
Market Opportunity
Entry point to a $400B+ market.
Now
Phase 1: AI Services
6M US businesses (10-500 employees). 0.1% penetration = 6,000 businesses at $25K avg project + $15K/yr hosting.
$240M
6-12 months
Phase 2: Vertical Platforms
Wedding industry alone: 300K+ venues/planners at $24K/yr. Expand to logistics, staffing, real estate, and more.
$7.2B
12-24 months
Phase 3: Agent Platform
US enterprise software market. Enable other businesses to build and run AI agents on shared infrastructure.
$400B+
Financial Model
Three scenarios. Built from real funnel math.
Best case
~8–9 deals/mo, $25K avg, 60-day cycle. WedLaunch 6 new/mo.
$3,100,000
Year 1 Revenue
Month 3
Cash Flow +
$2,900,000
Month 18 Cash
Most likely
~5–6 deals/mo, $25K avg, 75-day cycle. WedLaunch 3 new/mo.
$1,850,000
Year 1 Revenue
Month 4
Cash Flow +
$1,300,000
Month 18 Cash
Worst case
~2 deals/mo, $20K avg, 90-day cycle. WedLaunch 1.2 new/mo.
$644,000
Year 1 Revenue
N/A
Cash Flow +
$0
Month 18 Cash
Even in the worst case, $500K provides ~18 months of runway. Interactive model on the portal.
The Ask
We're not asking for capital to find product-market fit — we already have it.
We're asking for a bridge to scale. The $500K professionalizes the team, funds WedLaunch ad spend, and de-risks the growth ramp.
$500,000
SAFE Amount
$10,000,000
Post-Money Cap
5%
Dilution at Cap
YC SAFE
Cap Only, v1.1
$100K/mo revenue
Within 6 months
Cash flow positive
Month 4-5
5+ WedLaunch clients
Within 6 months
18 months runway
Even in worst case scenario
ben@madewell.ai
Ben Valentin, CEO / CTO