The Client: InvuAI is an AI-powered media monitoring platform. It tracks how a brand and its competitors are positioned across AI search engines and analyzes sentiment to show companies where they are losing market share.
The Challenge: The founder built a visual mockup using low-code tools and hired a freelance developer to turn it into a real product. However, the contractor failed to deliver, leaving behind a broken backend and deep architectural flaws on the eve of the official launch. Facing a critical pre-launch crisis, the client turned to us to recover the platform with a strict 60-hour and 14-day development window.
Instead of wasting time and money rebuilding the entire platform from scratch. We focused on the critical issues preventing a successful launch and resolved them one by one.
Users could complete the entire onboarding flow only to lose their data on the final step and start over. We fixed the project creation setup so information is saved smoothly without any risk of user data being overwritten or lost.
Subscription controls weren't properly enforced, creating a risk of premium features being accessed without payment.
We secured feature access and aligned it with subscription tiers.
A critical security flaw meant client data wasn't fully isolated between accounts. We rebuilt the access layer to guarantee complete data separation across organizations.
An overly complex database structure and duplicate code were slowing the platform down and increasing hosting costs.
We simplified the architecture, improved performance, and reduced infrastructure overhead.
Large-scale AI tracking jobs would overload the system, causing failed runs and missing reports. We stabilized the processing pipeline so tracking completes reliably even under heavy workloads.
The fully stabilized AI SaaS platform was successfully handed over to the client precisely within the strict timeline, perfectly matching the original quoted cost with zero budget overages.
14
days from crisis to production-ready launch
0
budget overruns
70%
reduction in database complexity
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