Breakthrough: Convert internal and partner data into real-time AI insights – with zero data movement
For CEOs who expect business outcomes and CIOs who live the operational reality
By Benjamin Buswell, Founder & CEO
Enterprises increasingly run on data. Over the past decade, data became a product - and with it came new operating models. Data mesh emerged to put domains in charge of meaning and quality. Data fabric followed to knit together distributed data sources using active metadata and automation. Both pushed the industry forward. Both also exposed hard limits: data movement, uneven governance, slow approval cycles, and AI work that stalls because the insights live across on‑prem, clouds, and SaaS.
Tapestry was built to overcome those limits. We don’t ask you to centralize everything. We bring an AI Insight Engine to the data you already have, composing governed insights in place, enforcing policy at runtime, and attaching lineage and audit to every result.
Where most enterprises are today
Roughly 85% of organizations already run Data & Analytics in a hybrid/multicloud data estate, distributed data environment. In practice, that means your distributed data estate is real - and growing. At the same time, self‑reported data mesh adoption remains a minority (≈20–30%), and “data fabric” rollouts often become integration programs that still move and duplicate data. The result is familiar: more copies, more reconciliation, inconsistent definitions, and governance driven by meetings instead of code.
What data fabric promised - and why it’s not enough on its own
Data fabric brought powerful ideas: use active metadata to discover, connect, and manage data across endpoints; automate pipelines; apply policies consistently. It improves visibility and speeds up integration. But when insights require pulling data into yet another layer, two things happen: you create new copies to secure and reconcile, and you defer the very controls - purpose binding, residency, and row/column rules - that should shape access at the moment of use.
The Tapestry breakthrough: an AI Insight Engine, not another integration layer
We place a governed AI Insight Engine within your internal and partner systems. Instead of relocating data to answer a question, we compute the insight where the data lives and bring back only the governed result. Policies are code - including row/column filters, purpose binding, and residency - and are enforced at runtime. Every interaction generates a real‑time audit trail (who asked what, under which policy, from where), and every result is an explainable insight with lineage and a policy envelope. Separation of duties is built in: domains own semantics, stewards manage sensitivity and approvals, and the platform enforces and audits.
Why “connecting the distributed databases” matters
Your most valuable questions - and your AI features - span systems. A transaction in a core ledger, a behavior in a CRM, a record in an LMS or EHR: taken alone, each is partial. Connecting them into insights matters because it delivers the context your teams need without creating more datasets to inventory, copy, and secure.
That means:
Faster time to insight because there are no new pipelines to build.
Stronger governance because policy applies at the moment of use.
Higher trust because definitions and joins are standardized once and reused.
How we complement what you already have
We don’t replace Snowflake or Databricks - we augment them. Keep your storage and compute where they excel. Tapestry composes governed insights across your estate - before, beyond, and between those platforms - so you don’t create another copy just to answer a question. Governance tools like Rhino and Tamarin help catalog and manage policy; we add the missing piece: governed insights in real time, not only metadata or control planes.
Sector examples
BFSI. Combine ledger, exposure, and customer interaction signals in place to improve forecast variance visibility and model governance. Residency and purpose policies apply automatically; model‑ready features inherit row/column rules with full audit.
Education. Blend enrollment, learning outcomes, and aid data without extracts. Consent and FERPA‑aligned rules bind purpose (research vs. outreach). Deans, faculty, and compliance see lineage with every insight.
Enterprise IT (cross‑industry). Standardize metric and feature definitions once, publish insight products, and grant access via policy‑as‑code. Reduce copies while raising reuse; AI initiatives inherit the same controls everywhere.
What better looks like (modeled targets)
We set conservative planning targets so executive teams can measure improvement:
Time‑to‑first‑insight (cross‑silo): ↓ 70–90%
Analytic data copies: ↓ 60–90%
Reuse rate of insight products: ↑ 3–5×
Mean time to grant governed access: < 1 hour (auditable)
Policy violations: 100% observable (attempted/blocked)
Why not 100% fewer copies? Our core model requires no copies to generate insights. In real programs, some artifacts still make sense: governed extracts for regulated reporting, partner hand‑offs, or offline ML training snapshots when latency or vendor tools require it. The point is to eliminate incidental copies and keep the few that remain intentional, governed, and auditable.
Take the next step
Book your Insight Readiness Assessment → Schedule time
If you’re running a distributed data estate and want faster, governed AI insights without creating more copies, our Insight Readiness Assessment (30–45 min) will show where to start. We’ll identify 3–5 high-value insights, the semantic contracts they need, and the policies to encode (row/column, purpose, residency) so you can move immediately.
“We built Tapestry to unlock governed, real-time insights across your distributed data estate – without moving or exposing raw data. It’s the AI Insight Engine that makes your existing investments safer and faster to use together.”
About DatumSure
DatumSure is the technology company behind Tapestry, the AI-native Data Insights Platform that enables real-time AI intelligence from siloed, regulated, and distributed data without ever moving or copying it. Founded by industry veterans with deep expertise in finance, healthcare, defense, and technology, the DatumSure team has built and scaled mission-critical systems where privacy and compliance are non-negotiable. Today, we help leaders unlock faster innovation, reduce risk, and transform data from a bottleneck into a growth engine.