Case Studies
See how engineering teams use Brainz Lab to ship faster, catch issues earlier, and do more with less. These are their stories.
SaaS Startup
The Problem
TechFlow's engineering team was drowning in support tickets and bug reports. With 500+ daily active users, their 4-person team spent more time triaging issues than building features. Tickets would sit in a queue for days before anyone could even look at logs to understand what happened.
The Solution
They deployed Reflex for error tracking and Recall for structured logging. With MCP integration, their AI coding assistant could now query logs directly and understand error context without manual investigation.
"Before Brainz Lab, I'd spend 2 hours per bug just understanding what happened. Now I ask Claude to investigate, and it pulls the relevant logs and traces in seconds. It's like having a senior engineer who never sleeps."
E-commerce Platform
The Problem
ShopMatrix processes thousands of orders during peak shopping days. Their previous monitoring setup only alerted them after customers started complaining about slow checkouts or failed payments. By then, they'd already lost sales and trust.
The Solution
They implemented Pulse for APM and Signal for intelligent alerting. Two days before Black Friday, Signal detected an unusual pattern: database connection pool exhaustion under simulated load that would have caused checkout failures at peak traffic.
"Signal caught a connection pool issue that our load tests missed. If that had hit during Black Friday, we'd have lost tens of thousands in sales. The AI analyzed the pattern and even suggested the fix. We deployed it in 30 minutes."
Development Agency
The Problem
DevStudio builds and maintains Rails applications for clients. With 12 active projects and growing, they had 5 engineers constantly context-switching between codebases. Each app had different monitoring setups, making it impossible to get a unified view of system health.
The Solution
They deployed the full Brainz Lab stack across all client projects. The unified Platform dashboard gives them a single pane of glass, while MCP integration lets their AI assistants investigate issues across any project instantly.
"We went from 5 engineers playing whack-a-mole with issues to 2 engineers proactively managing 12 apps. Our AI agents handle the monitoring and triage. We just review and approve the fixes. It completely changed how we operate."
Reduction in ops costs
Apps managed
Engineers (was 5)
Products Used
By The Numbers
Hours saved monthly
Monthly cost reduction
Faster issue resolution
Uptime on critical days
Your Story Starts Here
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