AI in Miami is only as good as
its implementation.

Choosing the right AI model is 10% of the work. Connecting it to your systems, training it on your data, and keeping it running is the other 90%. Rendai handles all of it for Miami businesses.

Talk to Us See How It Works

The Problem

Most AI implementations fail. Here is why.

87% of AI projects never make it to production. The technology works. The implementation does not.

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No one to build it

You know AI could help your business. You do not have an AI engineer. Hiring one in Miami costs $200K+ and takes 6 months in a market competing with tech companies in Brickell and Wynwood.

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Your data is messy

AI needs clean data. Yours is in 5 systems, 3 spreadsheets, and someone's email. Before you can use AI, someone has to untangle the mess.

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Pilots die in production

The demo worked great. Then it hit real data, real edge cases, real users. It broke. Nobody fixed it. Now AI is "that thing we tried."

The Rendai Model

How Rendai implements AI that actually works.

We solve the implementation problem by staying embedded and building continuously.

Start with what matters

No 6-month planning phase. First War Room: we identify the single highest-impact AI opportunity. First month: it is live in production. We start immediately.

Build for production

Every AI system handles real data, real edge cases, and real users from day one. We test against your actual operations, not sample data.

Never stop implementing

12 months = 12 implementations. Not one big project - 12 discrete capabilities that compound. By month 6, your business operates fundamentally differently.

Common Questions

AI implementation in Miami - your questions.

Why do most AI implementations fail?

87% never make it to production. Common failures: no one to maintain it after launch, built on demo data instead of real operations, no plan for edge cases. Rendai solves all three by staying embedded.

How fast can you get the first AI system live?

Within 30 days. No 6-month planning phase. First War Room identifies the target. First month, it is live in production. We start immediately.

What if our data is messy?

That is normal. Part of our process is connecting to your data wherever it lives and building pipelines to clean and structure it. We do not require a data cleanup before we start.

What technologies do you use?

Model-agnostic - OpenAI, Anthropic, Google, and open-source models. We build primarily on AWS but work with any cloud or on-premise setup. Best tool for each job.

What happens if an implementation does not work?

Because we are embedded, we iterate fast. A failed implementation becomes a learning. We diagnose, adjust, and try again in the same cycle. No waiting for another SOW.

AI in Miami is only as good asits implementation.