How Lobos 1707 turned fragmented data into a growth engine with DataOS

A global, Fortune 500 technology manufacturer turned 150M+ connected devices into a real-time intelligence engine, in weeks, not years.

51%  faster cycles via predictive reorder alerts

19%  revenue lift through ML optimization

8 weeks  to deploy AI-powered data products

80%

Reduction in time-to-market for device intelligence and GenAI experimentation

3–4

quarters faster on strategic manufacturing initiatives

50%

less time spent on repetitive data engineering works faster on strategic manufacturing initiatives

See what's possible in 30 minutes.

Bring your data challenges. We'll show you how this manufacturer cut time-to-market by 80%, and what that could look like for you.

Challenge &
Outcome

The challenge: disconnected data blocked AI and ML deployment, leaving the team reactive instead of predictive, with no way to identify high-value customers or predict churn.

The solution: DataOS delivered consumption-ready data products with embedded ML for segmentation, churn prediction, and reorder alerts, turning reactive sales into proactive growth.

How DataOS Made the Difference

DataOS layered onto existing systems, turning scattered telemetry into governed data products.

Layer on, don't rip out

DataOS connects to existing infrastructure at any maturity level. No migration project, no torn-out systems, just a unified layer on top of what's already there.

Data products, not one-off tables

Data gets defined once, as a version-controlled, reusable data product, with quality checks, documentation, and governance built in, instead of engineers hand-building the same pipeline over and over.

AI-ready from day one

A built-in semantic layer describes data in business terms automatically, so natural-language queries and AI agents work immediately, with no separate modeling effort.

Governance without the overhead

Access controls, lineage, and quality monitoring deploy with the platform itself, not as a bolt-on project added months later.

Weeks, not quarters

Traditional builds ran 12-18 months. DataOS reached a working prototype in five days and completed full production deployment in four weeks, ahead of the original six-week target.

“With our unified data platform, developers can shift from 'just producing tables' to building reliable, discoverable data products with clear ownership and governance — all while supporting both real-time and batch processing needs.”

- Sr. Director of Data & Analytics

The Five-Day Breakthrough Made The Difference

Friday

Nearly 50 sample telemetry files delivered

Weekend

Data structure analyzed, environment built

Tuesday

Working demo environment ready

Following week

Results at a Glance

150M+ devices

Unified telemetry, streaming in real time

4 weeks

Full production deployment, ahead of a 6-week target

40+ engineers

Trained on a new, product-first way of working with data

"DataOS fundamentally changed how we think about data. Instead of building one-off solutions, we're now creating reusable data products that serve multiple business needs simultaneously."

- Sr. Director of Data & Analytics

Why It Worked

Executive sponsorship kept the project moving. A rapid-prototyping approach replaced months of upfront planning. And a deliberate shift from project thinking to product thinking turned one-off fixes into reusable, governed data assets, unlocking not just faster maintenance and quality wins, but new data-driven revenue streams like premium warranty offerings and partner analytics services.

See what DataOS can do with your data.

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