▸ Answer · Timeline

How long does it take to get AI to production?

QuantAimLabsUpdated Nov 20254 min read

Short answer: For a focused single-feature scope on existing infrastructure, 6–8 weeks from kickoff to live traffic. For greenfield platform plus multi-step agentic workflows, 10–14 weeks. Add 20–30% if data is regulated.

Week-by-week (typical engagement)

Week 0 — Pre-kickoff

Contract, access provisioning, kickoff prep. Free if you've signed; we don't drag this out.

Weeks 1–2 — Assessment

Architecture deep dive, current-state review, risk register. Output: written assessment, fixed-scope plan, ADRs for key decisions. You sign off before we build.

Weeks 3–4 — Foundations

IaC scaffolding, CI/CD wiring, observability stack, eval harness scaffolded. The boring stuff that prevents 67% of incidents (per our field research).

Weeks 4–6 — Build

The AI feature itself. Prompts, tool servers (MCP if applicable), retrieval pipeline, gateway integration. Weekly demos. Your engineers pair with ours from day one.

Weeks 6–8 — Hardening + launch

Load testing, cost guardrails, incident playbooks, redaction layer, rollout plan. Launch behind a feature flag, ramp traffic with kill-switch ready.

Weeks 9–12 (optional) — Operate

Second-line support, weekly office hours, eval expansion. Your team owns it; we're the hotline.

What can be parallelized

What can't

Compared to typical industry timelines

Big-firm transformations quote 6–18 months. The bulk of that time is roadmap meetings, multi-party kickoffs, and discovery debates. We skip those. The actual engineering for a focused first feature has never legitimately needed more than ~8 weeks in our experience.


Book an intro to scope your specific timeline. The first 10 minutes will tell you if 6 or 12 weeks fits.