Your AI feature, shipped in 21 days.
A senior engineering team builds, evals, and ships one LLM-integrated feature on a hosted demo, then hands you the production code. Fixed scope, fixed price, milestone-paid.
$6K kickoff · $4.5K architecture lock · $3K demo live · $1.5K handoff
One feature, fully shipped
We pick one LLM-integrated feature, build it on a hosted demo, and hand you a production-ready repo at handoff. No 90-day discovery phase. No "we'll see what we find."
You own the code
GitHub repo transferred to your org on handoff. TypeScript, Next.js, deployment configs, eval suite included. Your engineers deploy from day one.
Paid as we ship
Four milestones tied to inspectable artifacts: kickoff, architecture lock, demo live, handoff. Each invoice fires when the deliverable lands — not on a calendar date.
“We’ve shipped production AI systems for our own portfolio: LedgerLens, LifeVault Secure, ReelDeck Studio, Heartwood Memory. The AI MVP Sprint applies that same engineering team to your feature.”— Edukas team
One tier. Fixed price. Complete delivery.
No negotiations, no surprises. The sprint price is set — what changes is the feature we build.
AI MVP Sprint
Paid in 4 milestones — $6K kickoff · $4.5K architecture lock · $3K demo live · $1.5K handoff
For product leaders who need a working AI feature in their hands before the next board meeting — not a 90-day roadmap.
Includes
- One LLM-integrated feature, hosted demo
- Production-ready code repo (GitHub transfer)
- 30-day hosted demo environment
- Eval suite — 10 test cases, ≥ 8/10 passing at demo-live
- Architecture brief (PDF + Markdown)
- Kickoff, architecture-review, and handoff calls
- Optional 4-week extension to production
Not included
- Hosting beyond 30-day demo window
- Ongoing maintenance or on-call
- More than one LLM feature
- Compliance certification
- Production system integrations
The kickoff payment is non-refundable once work has commenced. Later milestones are refundable only as set out in your signed scope of work. If a milestone artifact isn't delivered to spec, that milestone invoice doesn't fire and the engagement enters mutual renegotiation.
Frequently asked
We lock the feature spec at M1 kickoff. If you need a different feature or additional scope after kickoff, the original sprint completes as scoped (so you receive the deliverable you bought) and we quote the new scope as a separate engagement. The fixed scope is the productized constraint that makes the price possible.
You do. The GitHub repo transfers to your organization at M4 handoff with full commit history. We retain no ownership of your code, your data, or your AI feature. We may anonymously reference the engagement category ("we built an LLM feature for a fintech Series A") in our marketing unless you opt out in writing during kickoff.
Yes. You provide API keys for whichever LLM you choose (OpenAI, Anthropic, Google, open-source via your own infra) at M1. We do not pass through API costs. Typical demo-period API spend for a single LLM feature is $20–$200. We'll estimate your specific usage during the kickoff call.
Add a $1,000 AI Discovery Blueprint before you commit to the Sprint. We deliver model selection, eval rubric design, a risk register, and your locked Phase 1 quote in one week. Buyers with a clear feature spec can skip Discovery and commit straight to the Sprint kickoff deposit.