Why We Promise 14-Day Deployments (And How We Actually Hit That Deadline)

When I tell people we deploy AI workflow integrations in 14 days, I usually get one of two reactions:

1. “That’s not enough time to build something real.”
2. “What’s the catch?”

The catch is that we only build things that can be done in 14 days. That sounds circular, but it’s actually the point.

The 14-Day Constraint Is a Feature

Most software projects fail because scope expands. A “simple automation” turns into a “we should probably also connect this to X” conversation, and suddenly two months have passed and nothing is in production.

The 14-day constraint forces a different conversation. Instead of “what could we build?”, it’s “what specifically needs to happen for this to be worth doing?” That question cuts through the noise fast.

How the 14 Days Break Down

Days 1–2: Understand Your World

We spend the first two days understanding exactly what you’re doing manually and why. This isn’t a discovery phase — it’s a scoping session. We’re looking for:

• What triggers the workflow? (A schedule, an event, a human decision?)
• What data does it need? (Where does it live? What format is it in?)
• What does success look like? (What’s the output, and who receives it?)
• What are the edge cases that matter? (Not hypothetical ones — actual ones that have happened)

At the end of Day 2, we have a spec. If we can’t produce a clear spec in two days, that’s a signal the workflow needs more scoping before we can commit to a deadline.

Days 3–10: Build & Connect

This is where we build. Using n8n, Make.com, or direct API integrations depending on what fits the workflow, we:

• Set up the automation framework
• Connect the data sources
• Build the AI processing layer (usually Claude) with tested prompts
• Connect the outputs to wherever they need to go
• Add error handling and alerting

We share progress daily. If something isn’t working, we know by Day 5, not Day 13.

Days 11–14: Ship & Hand Off

The last four days are for testing in your real environment, handling the edge cases we inevitably discover, and getting to a version you’re comfortable running. We also write documentation — not just for your future self, but for anyone on your team who needs to understand or modify it later.

What We Don’t Build in 14 Days

Some things genuinely can’t be scoped and shipped in two weeks. We don’t pretend otherwise.

If the data is messy (multiple systems with conflicting records, no clear source of truth), we tell you that upfront. If the workflow requires custom ML model training, that’s not a 14-day project. If the requirements need three rounds of alignment meetings before we can write a spec, we’ve failed the Day 2 gate.

We’d rather decline a project than miss a deadline. The 14-day promise only works if we’re honest about when it won’t.

The Guarantee

If we accept a project and don’t ship in 14 days, you don’t pay. That constraint keeps us honest about what we take on.

If you have a workflow you’ve been meaning to automate, book a 15-minute call and we’ll tell you whether it’s a 14-day project or something else entirely. Either answer is useful.