Scanalytics

Our landing page.
Key functionalities.
Intuitive chatbot to manage critical concerns.
Advanced metric analysis to give you more control over your business.
Client-focused SDK that streamlines metric analysis within client codebase.

Inspiration

As devs, our team faced a common frustration: our modern analytics tools show data, but they don’t explain what matters. Dashboards are often cluttered with charts created “just in case,” forcing founders and engineers to hunt for meaning rather than act on insight. We wanted to build a platform that felt less like a reporting tool and more like a Command Center . Something you could open and immediately understand the health of your product, without being an analytics expert.

What it does

Scanalytics is an AI-powered observability and decision intelligence platform designed to help founders and engineers understand the operational health of their product at a glance.

Instead of relying on static dashboards and disconnected charts, Scanalytics:

Translates raw event data into logical health signals
Evaluates metrics against AI-defined thresholds
Surfaces actionable insights, not just numbers

Users can define their product in plain language, preview the resulting analytics schema, and monitor live system behavior through a clean, high-signal interface that prioritizes clarity and urgency.

How we built it

Frontend: Built with React, and TypeScript, the frontend focuses on high-signal UI, state-driven interactions, and clear information hierarchy. Custom components and animations were implemented to create a responsive, command-center-style interface without relying on generic dashboard libraries.
Backend: The backend is designed with a FastAPI (App Router) to expose structured analytics and observability endpoints, with a focus on schema-driven data ingestion, query evaluation, and alert generation. It serves as the intelligence layer that powers dashboards, insights, and integrations, and is structured to support future real-time processing and AI-driven analysis.

Challenges we ran into

One of the main challenges in building Scanalytics was designing an interface that communicated system health and business impact without overwhelming the user. Traditional analytics tools tend to surface too much information at once, so a significant amount of effort went into deciding what not to show and how to distill complex data into clear, decision-oriented signals.

Accomplishments that we're proud of

Designing an intuitive analytics interface that still communicates system health clearly
Building a navigation system that feels alive and responsive, not static