Service · MVP in weeks

Claude MVP development — live in weeks,
not quarters.

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03MVP types

Five MVP shapes, and what we cut to make the date.

MVPWhat shipsWhat waits for v2

Claude-Powered Assistant

One assistant doing one job well, wired to your real data, with the reasoning shown rather than hidden.

Multi-agent orchestration

AI Feature in an Existing Product

A single feature layer — analysis, summaries, intelligent search — on the product you already run.

The rewrite

Two-Sided MVP

Both sides of the transaction, the matching between them, and one payment path that genuinely works.

Payouts at scale

Mobile MVP

One platform done properly, or both cross-platform, with the backend contract defined once.

Native rewrites

Internal Tool

The workflow your team actually runs, with roles and an audit trail from day one.

The full permission matrix
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04The calendar

How six weeks actually goes.

  1. 01Week 1Scope and architecture

    The workflow mapped as it really happens, the success measure written down, and the parts that are explicitly out. This is what makes the rest of the calendar possible.

  2. 02Week 1–2The risky flow first

    Whatever we are least sure of ships first. On FlyCRM that was the capture pipeline, in phase 3 of 20, which is why the last two weeks were polish.

  3. 03Week 2–4The core build

    The features that carry the hypothesis, and nothing that does not. Scope creep is the only reliable way to miss this date.

  4. 04Week 4The AI layer

    Scoped to the specific jobs it does well, behind a provider-agnostic interface, so swapping models later is a config change rather than a refactor.

  5. 05Week 5QA and guardrails

    The refusals encoded, the confirm gates placed, the failure paths walked. What the system does on a bad day is part of the build, not an afterthought.

  6. 06Week 5–6Deploy and handover

    Infrastructure, documentation and access. You should be able to keep going without us, and most clients do.

05Why Claude

Why We Build with Claude

Three reasons, each one a failure we would rather not spend a six-week build debugging.

01

Instruction-following that survives a long chain

14 agents across 6 layers

A system that reads a 50-page report, extracts fields, classifies them and fires the right workflow fails at whichever step drifts first. Across the fleets on this site — 14 agents in one, 8 in another — the compounding matters more than any single-shot benchmark. Claude held the chain best in the comparisons we ran before committing.

02

A context window that removes the chunking layer

96% ruled out on one pass

Whole documents, full ticket histories and entire exports go in on one pass. That deletes the chunk-and-stitch code that is the usual source of dropped context — and the usual source of a summary that quietly omits the important paragraph.

03

Predictability we can put in front of a client

0 writes without a confirm

Every build here writes into someone's production system. Consistent, well-bounded behaviour is what makes a human-confirm gate meaningful and what gets a build through an internal review. It is the reason the FlyCRM figure is 0 and not 'low'.

Frequently Asked Questions.

What is included in your Claude MVP development service?

Our Claude MVP service includes: product discovery and scoping, AI architecture design, Claude API integration, backend systems and REST APIs, a web or mobile interface (depending on scope), deployment to cloud infrastructure, and basic monitoring. We focus on getting a working, testable product in front of real users as quickly as possible.

Most Claude-powered MVPs ship in 3–6 weeks. Week 1–2 covers discovery, architecture, and design. Weeks 3–4 are the core build sprint. Weeks 5–6 are QA, deployment, and handover. Complexity factors that extend timelines include custom data pipelines, third-party integrations, and multi-user permission systems.

An MVP (minimum viable product) is the smallest version of your product that lets you test your core hypothesis with real users. It typically has one or two core AI features, basic authentication, and enough UI for users to get value. A full AI product adds scale infrastructure, advanced features, billing, analytics, and production-grade reliability. We recommend validating with an MVP before committing to full-scale development.

After launch, we can support with a post-launch monitoring period, iteration sprints based on user feedback, and a roadmap toward a full AI SaaS product. Many clients move from our MVP service into our AI SaaS development engagement once they've validated their idea and secured funding or early revenue.

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