Kurtis Welch / Recursive AI

I build complete
SaaS products
in weeks

Not MVPs. Not prototypes. Production-ready applications that actually work.

20 years building software
Two companies founded and sold
CTO → $30M ARR → 3-year exit
Next opening: Nov 17 → Ship by Dec 29
See how it works

View open project slots and book your discovery call

What I build

What I DON'T Build

MVPs that need rebuilding in 6 months
Prototypes that aren't production-ready
Maintaining or extending existing codebases
Projects with unclear requirements
Augmenting your existing team

What I DO Build

Complete products ready for production
Greenfield systems built from scratch
Full rebuilds that eliminate technical debt
Data-heavy SaaS applications
Complex systems with clear specifications

Industries I've worked with

Fintech
Gaming
Logistics
Retail
Education

How I work

1

Build a rapid prototype

Start with the core concept. Build just enough to test with real users. Hours, not weeks.

2

Test with real users

Get it in front of actual users immediately. Learn what works and what doesn't. Real feedback on a working product, not wireframes.

3

Learn what's actually needed

Usage reveals the truth. Students gaming the system. Teachers needing real-time visibility. These insights only come from real use.

4

Prototype uncertain features

Not sure if something is feasible? Build a throwaway prototype to test it. A few hours to validate an approach before committing to it.

5

Rebuild with learnings

Update the specification with everything you learned. Rebuild from scratch. No compromises. No technical debt. Clean architecture.

6

Launch production-ready

Not an MVP you'll need to rebuild. Not a prototype. The actual product, battle-tested and ready for real use.

This is version-based development. You iterate on the concept, not the code. The code is disposable. The specification is what matters.

What makes this possible

The technology is capable. AI can generate complete systems from specifications. But knowing how to use it effectively requires deep architectural expertise.

I spent $500K and thousands of hours figuring this out. Not just "using AI to code faster" - understanding how to architect systems at a level where AI can generate them correctly at production quality.

What I systematically figured out:

How to architect complete systems that AI can generate correctly
How to write specifications at the level of precision needed
How to handle edge cases without constant human oversight
How to make this work at production quality, not prototype quality
How to do this reliably, repeatedly, profitably

Most people trying this casually will fail because they don't have the architectural expertise. This isn't something you pick up from a YouTube tutorial.

I believe we're at a turning point for humanity with AI. It makes it possible to build software in a completely different way. But most people are just using it to code faster - not rethinking the entire process.

I invested heavily in figuring this out because I think it matters.

The team

Great products need more than great code. My team brings expertise in data systems, fraud detection, product management, and organizational design - everything needed to ship complete, production-ready solutions.

Kurtis

Founder

20 years building software. Founded and sold two companies. Former CTO of fintech startup that grew to $30M ARR and successful exit. Father of six who values direct communication.

Jessica

Data Engineer & Fraud Analyst

Military intelligence veteran specializing in data engineering and fraud detection. Builds complex data pipelines and anomaly detection systems for high-stakes applications.

Nick

Product & Project Leadership

20 years of executive-level experience in software project and product management. Led teams at both enterprise companies and startups. Expert in organizational leadership.

Amanda

Program & Product Management

Master's degree in organizational psychology. Director-level experience in product, project, and program management. Specializes in building effective organizational systems.

How we work together

Two ways to engage. Both fixed-price. Both focused on complete products.

Most Popular

Build a Complete Product

$25K starting
3-6 weeks typical timeline
Complete system specification
Multiple build-test-learn cycles
Production-ready deployment
Full documentation
Custom AI agents for maintenance
Training on the agents
30-day warranty

Good for: Founders who want to own and maintain the product themselves.

Not sure which direction to go? Start with Concept Validation ($10K-$15K, 1-2 weeks). We'll build 2-3 prototypes, test with users, and pick the winner.

Rebuild Your Product

$50K starting
4-8 weeks typical timeline
Everything from standard build
Assessment of existing system
Migration strategy and execution
Data integrity management
Parallel deployment
Smooth transition management

Good for: Companies with technical debt, need to pivot, or want to start fresh with clean architecture.

What happens after launch

30-day warranty

We fix any bugs discovered in the first month. This covers functionality issues, performance problems, deployment issues, and user-reported bugs.

After 30 days

You own it and maintain it yourself using the custom AI agents we provide. These agents understand your codebase and can handle maintenance, bug fixes, and small feature additions.

Need a new major feature?

You have options:

  • Use the AI agents to build it yourself
  • Hire any development team (traditional approach)
  • If it requires architectural changes, come back to us for v2.0

Ready for v2.0?

When you've learned what users actually need and are ready for a complete rebuild with those insights, we can do another project engagement. Since we already know your domain and have the v1.0 specification, v2.0 is typically faster and cheaper than v1.

Common questions

Is this right for me?

This works best if: You need a complete product fast. You value speed and quality over cost. You're willing to let an expert own the technical decisions. You want to iterate on concepts, not code.

Not a fit if: You want someone to maintain your existing codebase, you're looking for a developer to join your team, you want hourly pricing, you need the absolute cheapest option, or you want to micromanage implementation details.

Do you do ongoing maintenance?

Not really. We build complete products and hand them off. You maintain them using the AI agents we provide. If you want us to build new features or v2.0, that's a new project engagement.

What if I need a bug fix after 30 days?

Use the AI agents we provide, or hire any developer. We built it with clean architecture and full documentation specifically so you can maintain it.

Can you work with my existing team?

If you're doing a rebuild, your team can observe and give input on tech stack and review the specification. But we build the product - that's how we move fast. After handoff, we'll train your team.

What tech stacks do you use?

Whatever makes sense for your project. We're stack-agnostic. AI agents write the code, so we're not limited to one language or framework.

What if my project is bigger?

Larger projects can take 6-8 weeks and cost more. Book a call and we'll scope it out. You'll know the fixed price upfront.

Can I see examples of your work?

Most client work is confidential, but the reading comprehension app on this page is one I built for my son. It's now used in classrooms.

Let's talk about your project

Book 30 minutes. I'll review your project, explain how I'd approach it, and we'll figure out if this makes sense. No pressure, no pitch.

Not ready to book? Email me with your project details:

[email protected]

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