When Data Can’t Be Trusted, Decisions Slow Down

DataOS builds trust into enterprise data

By adding lineage, shared semantics, and governance directly into the data, teams can move fast without losing control.

Talk to Us About Data Trust

Works on top of your existing data stack

Learn more about DataOS

The Real Problem Isn’t Governance

It’s trust at decision time, Enterprises struggle when:
  • The same metric shows different values across dashboards
  • Analysts can’t trace numbers end to end
  • Business definitions live in documents, not data
  • Governance exists, but access still takes weeks
This creates hesitation. And hesitation kills momentum
What customers achieve with DataOS

"In just eight weeks with DataOS, we had a data infrastructure in place that allowed us to transform how we use data."

Global Head of Technology, Lenovo
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Why Lineage and Semantics Matter for AI and Analytics

AI and advanced analytics depend on three things:

  • Clear business meaning (semantics)
  • Explainability (lineage)
  • Confidence in data quality

Without these, models produce outputs no one is willing to act on

Talk to Us About Usable Data

How DataOS Solves This Without Slowing Teams

DataOS adds trust inside the data, not around it. it provides:

  • A shared semantic layer so metrics mean the same thing everywhere
  • End-to-end lineage visible to analysts and leaders
  • Inline governance and quality, not ticket-based approvals
  • Reusable, trusted data products teams can rely on

All of this works on top of your existing stack

Talk to Us About Semantic Layer

What Changes Once Trust Is Built In with DataOS

  • Faster access to reliable data
  • Fewer reconciliation cycles
  • Clear explanations behind every number
  • AI and anlytics outputs that business leaders accept

Decisions move faster because trust is no longer a question

Talk to Us About Your AI Readiness

How Enterprises Fix This Without Rebuilding Their Stack

You Keep

  • ▪   Snowflake or Databricks
  • ▪   Existing BI and analytics tools
  • ▪   Current source systems

DataOS Adds

  • ▪   A semantic layer that standardizes business meaning
  • ▪   Data products analysts can reuse across AI and BI
  • ▪   Inline lineage, quality, and access control
  • ▪   Native access for dashboards, APIs, and AI apps

No rip-and-replace. No new silos. No disruption to existing teams.

Who DataOS is Built For

Global CPG Distributor

Heads of Digital Transformation and Business Analytics

Industrial Manufacturer

AI and Innovation
leaders accountable for outcomes

Global Architectural Firm

CIO, CTO, CDO balancing speed with trust

Leading Device Manufacturer

Enterprises where analysts drive decisions, not just reports

Start With a Real Business Use Case.
Don’t start with just a demo.

A real forecasting,
analytics, or AI 
use case

Implementation in
your environment

A working outcome
your analysts
can validate

A clear path
to production

Learn more about DataOS

DataOS is recognized by the experts.
Proven by results.

Talk to us about making your data usable for AI

Start with a discovery conversation that leads to a Proof of Value.
Get Started

FAQs

Is this just a governance or catalog tool?

No. Governance and lineage are built into how data is delivered and consumed, not managed separately.

Will this increase process overhead for analysts ?

No. Analysts get faster access because quality, lineage, and access controls are already in place.

Do we need to standardize everything upfront ?

No. Semantics evolve incrementally as new use cases are added.

Can this work with our existing BI and analytics tools ?

Yes. DataOS works with the tools your teams already use.

How quickly can we see results ?

Most teams see a working, trusted use case in 4 to 8 weeks.