01
Pre-seed founders
Get a real product in front of design partners before the round closes.
[ 04 / Services ]
Rapid MVP Engineering
From blueprint to production in 4 weeks. High-fidelity AI MVPs built for scale from Day 1.
04
[ Capabilities ]
01
Infrastructure-as-Code
02
Real-time Observability
03
SOC2-Ready Stack
[ Overview ]
Rapid MVP Engineering
Most AI MVPs die in PoC purgatory — slick demo, zero infrastructure, impossible to scale. We do the opposite. From blueprint to production in 4 weeks, built on infra that survives Day 1 traffic and a Series A diligence room.
Week 1 is discovery, model selection and architecture. Weeks 2–3 are build, eval and harden. Week 4 is launch, observability and a working playbook for the next iteration. You walk out with a real product, real metrics, real users — not a Figma file with a chatbot bolted on.
If you're raising on this, we'll help you talk to it like an engineer who shipped it. Because we did.
[ What you get ]
- Deployed AI MVP with auth, billing-ready stack and observability
- Infrastructure-as-code (Terraform / Pulumi)
- Eval suite + cost & latency dashboards
- SOC2-ready foundations (logging, secrets, RBAC)
- Founder-friendly handover deck for fundraising
[ Where it shines ]
Where it shines
02
Innovation labs
Validate an AI thesis inside a corporate without the 6-month procurement cycle.
03
Product teams
Spin up a parallel AI track without slowing the core roadmap.
04
Acquisition prep
Take a Powerpoint product to a working V1 before diligence starts.
[ Tools & stack ]
Next / TanStack Start · Bun · VitePostgres · pgvector · RedisCloudflare · Vercel · Fly.ioStripe · Clerk · ResendLangfuse · Sentry · OpenTelemetry
[ Frequently asked ]
Frequently asked
01Why 4 weeks?
It's the longest cycle that still forces real prioritization. Anything longer and scope eats the project; anything shorter and quality dies.
02Is it really production-grade in 4 weeks?
Yes — because we ruthlessly cut everything that isn't core to the wedge. The infra, observability and auth are real; the product surface is intentionally small.
03What if we want to extend the engagement?
We offer a fractional CTO retainer to keep iterating with you after launch.
[ 01 ]
What we deliver
UltraMVP combines deep model expertise with battle-tested production engineering. Every engagement ships measurable outcomes — not just prototypes — built on a stack that includes Claude Code, OpenAI Codex, and custom Gemma 4 fine-tuned adapters.
- Infrastructure-as-Code
- Real-time Observability
- SOC2-Ready Stack
[ 02 ]
How we work
- Step 0101
Discovery and technical audit (1 week)
- Step 0202
Architecture and model selection
- Step 0303
Build, evaluate and harden for production
- Step 0404
Deploy with observability and on-going optimization
Ready for the edge?
From blueprint to production in 4 weeks. High-fidelity AI MVPs built for scale from Day 1.
Book a discovery call→[ MORE SERVICES ]
Services →01
Custom AI Development
End-to-end AI products: agents, copilots, RAG systems, and autonomous workflows built for production.
02
Custom Model Training
Fine-tuning Gemma 4, Llama 3 and proprietary architectures on your data for niche domain mastery.
03
Claude Code & Codex Integration
Leverage the latest Anthropic and OpenAI coding agents to automate complex software lifecycles.