DataFlint

DataFlint

Platform for cost-efficient data workflows

Mission

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Long Story Short

About Project

Trusted by AWS, WIX, and Similarweb

In large data-driven organizations, every workflow, every query, and every compute cycle has a cost. But few teams have a clear picture of what exactly drives those costs — and how to reduce them without slowing down innovation.

DataFlint was built to change that.

It’s an intelligent analytics platform that helps engineering and data teams monitor, analyze, and optimize their compute usage — turning infrastructure data into actionable cost insights.

With DataFlint, companies can finally see the real price of every job, every cluster, and every decision in their data pipelines.

Challenge Accepted

Requirements

Big data operations are expensive.

Hundreds of Spark, ETL, and ML jobs run daily across environments, often with overlapping logic and inefficient resource allocation.

The client came to us with a clear pain point: “We want to know exactly where our data pipelines waste money — and fix it before the next invoice arrives.”

Their team was struggling with fragmented monitoring tools and a lack of unified visibility. They needed a single system that could combine performance metrics, cost analytics, and optimization insights — in real time.

Our challenge was to design a product that felt as intuitive as a dashboard and as powerful as an engineering console — merging business visibility with technical precision.

UNLOCKING SUCCESS

Solution

Overcode developed DataFlint, a full-stack platform that visualizes how data workflows consume compute resources — and automatically detects where savings can be made.

We started with a deep discovery phase to understand how engineers, data analysts, and managers interact with job metrics and budgets. This helped us design user journeys that balanced simplicity with depth: surface-level insights for decision makers, detailed analytics for technical users.

DataFlint connects directly to cloud infrastructures, aggregates performance data, and translates complex logs into readable insights. Behind the scenes, a rules-based engine identifies patterns — such as recurring job inefficiencies, memory overuse, or CPU spikes — and converts them into optimization opportunities, complete with estimated yearly savings.

Core Features:

Real-time monitoring of workflow performance: run count, total cost, duration, and success rate.

Cost analytics dashboards visualizing compute trends, cost vs. savings potential, and resource utilization.

Automated recommendations with estimated yearly impact and implementation difficulty.

Admin panel for managing environments, teams, and job configurations.

Integrated reporting system that tracks progress and ROI from implemented optimizations.

Platform for cost-efficient data workflows

About Project

Requirements

Solution

Core Features:

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