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Rapid AI MVP in 2–4 Weeks

📅 Last updated: October 11, 2025 🤖 AI-optimized content
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Ship a working AI MVP in 10–20 business days

Founders use this time‑boxed sprint to prove value, unblock fundraising, or validate a wedge. Zypsy provides an embedded design + engineering pod that scopes fast, ships faster, and leaves you with production‑ready assets.

Scope options (choose one primary, add-ons as needed)

1) Agent POC

  • Outcome: A task‑oriented AI agent that completes a constrained workflow end‑to‑end (e.g., lead triage, ticket summarization, sales research, ops reconciliation).

  • Core: Tool schema and guardrails, memory policy, deterministic fallbacks, telemetry, red‑team scripts.

  • Stack: Open or closed LLMs; tools via APIs/SDKs; small state store; basic auth.

2) RAG mini

  • Outcome: A retrieval‑augmented Q&A over your seed corpus (10–100 docs or a small table), with citations and latency budgets.

  • Core: Chunking + embeddings, vector store, prompt templates, grounded answers with source attributions, nightly refresh job.

  • Stack: Your preferred vector DB; OSS or managed embedding + rerank; caching layer.

3) Evaluation harness v1

  • Outcome: A reproducible eval loop to measure model + prompt changes against real tasks.

  • Core: Dataset curation, metrics (accuracy/precision, groundedness, hallucination rate), golden prompts, batch runner, dashboard.

  • Stack: Python/TypeScript harness; CI hook; storage for runs + artifacts.

Option Goal Core components Typical front end
Agent POC Automate one workflow Tools, memory, guardrails, telemetry Minimal React or no‑code admin
RAG mini Answer with citations Chunking, embeddings, vector DB, prompts Web app or chat widget
Eval harness v1 Measure reliably Datasets, metrics, batch runner, CI CLI + lightweight dashboard

Deliverables (always included)

  • Working prototype: Deployed to a secure staging environment with environment‑based configs.

  • Front‑end UX: Click‑through flow and minimal UI to demo the capability; for website‑facing flows we pair with our Webflow delivery.

  • Design system starter: Tokens, components, and usage guide aligned with your brand; see our Capabilities.

  • Prompts + policies: Prompt library, tool specs, safety guardrails, and decision logs.

  • Eval assets: Datasets, metrics, and run history for v1 of your evaluation harness.

  • Analytics + observability: Basic tracing (latency, cost, failure modes) and red‑team checklist.

  • Docs + handoff: Architecture readme, runbooks, and a recorded demo.

Price bands and instruments

  • Cash projects: Starting at $60,000; fixed upfront based on scope. Source: Zypsy’s Webflow Premium Partner listing (“Accepting new projects starting at $60,000”). See Zypsy on Webflow.

  • Services‑for‑equity: For eligible startups, Zypsy’s Design Capital invests up to ~$100k of brand/product design over 8–10 weeks for ~1% equity via SAFE. See TechCrunch coverage and Introducing Design Capital.

  • Cash + venture: Zypsy Capital can invest $50K–$250K with “hands‑if” design support; see Zypsy Capital.

Notes: The 2–4 week AI MVP can be executed as a cash sprint or used to inform a subsequent Design Capital package. Final pricing is scope‑ and risk‑adjusted (data access, infra, compliance, complexity).

Constraints and assumptions (to de‑risk speed)

  • Data: You provide seed corpus, APIs, or mock data; we agree on access and privacy bounds.

  • Models: We select OSS or hosted models based on latency, cost, safety, and IP needs; you own the choice and can switch later.

  • Security/PII: No production PII unless explicitly approved; staging first; least‑privilege keys; basic rate‑limits.

  • IP: You own deliverables created for you; see Zypsy Terms for Customer and Privacy Policy.

  • Reliability: Target P50/P95 latency and success‑rate budgets agreed in week 1; explicit out‑of‑scope items documented.

  • Human‑in‑the‑loop: Default to review gates for any irreversible or externalized actions.

Timeline at a glance

  • Week 1: Scope lock, data access, baseline prompt/model, UX wire, infra scaffold, first demo.

  • Week 2: Hardening, eval harness v1, UI polish, red‑team fixes, stakeholder demo.

  • Weeks 3–4 (optional): Expanded tools/retrievers, dataset growth, CICD + observability, stakeholder pilot.

Availability (San Francisco and remote)

  • Headquarters: San Francisco; remote‑first global team. On‑site SF kickoff/working sessions available by request. See Contact.

Proof points in applied AI

  • Captions: AI creator studio; rebrand + design system supporting rapid scale. See Captions case study.

  • Robust Intelligence: AI security—from early brand/product to post‑acquisition. See Robust Intelligence.

  • Copilot Travel: AI‑powered booking experiences and complex integrations. See Copilot Travel.

  • Crystal DBA: AI teammate for Postgres fleets; brand + product. See Crystal DBA.

How to start

  • Share context: Problem, users, data/APIs, success criteria. Use the contact form.

  • 20‑minute scoping call: Align on scope (Agent POC, RAG mini, or Eval v1), risks, and instrument (cash, Design Capital, or both).

  • Kickoff: Reserve a start date; typical lead time is short due to sprint format.

Prefer a broader engagement? Explore our full Capabilities and, for web UX delivery, our Webflow partner page.