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How a Real Estate SaaS Made Its AI Reliable Enough to Bet the Roadmap On.

An AI reliability playbook for Heads of AI who need a system the product team can plan around.

In depth

Your AI works great on Mondays and breaks on Fridays.

01

AI reliability is a different problem from traditional software reliability.

02

The first symptom we see in unreliable AI is a product team that has stopped committing to AI-dependent features in roadmap reviews.

03

The second symptom is sales that has started apologizing for AI behavior to customers.

The detail

The 90-day program that gets you there.

Zone · 01

Weeks 1–3 - Define SLOs your customers care about

Latency, uptime, and quality. Quality is the one most teams skip because it is harder.

Zone · 02

Weeks 4–7 - Eval gate in CI

No prompt change ships without passing the eval. The eval suite is treated like the test suite.

Zone · 03

Weeks 8–10 - Regression suite for behavior change

When the model provider releases a new version, your behavior changes. Your customers notice before you do.

By the numbers

The figures that make it a board-level conversation.

7 ppt
Listing JSON validity rate - +3
5 ppt
CMA factual accuracy - +
1%
Hallucination rate
Inside the report

What you'll take away.

01

Define SLOs your customers care about

Latency, uptime, and quality.

02

Eval gate in CI

No prompt change ships without passing the eval.

03

Regression suite for behavior change

When the model provider releases a new version, your behavior changes.

Questions

Frequently asked.

How is this different from regular SRE?
What if our team is small?
Do we need to switch model providers?
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Next step

Product builds commitments on top of AI without flinching.

Talk through how this applies to your roadmap with our engineering leads - a working session, not a sales pitch.

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