Multi-Cloud, One Mind: AI Insights from Your Cloud-based Data Estate
Get governed, real-time answers from AWS, Azure, and GCP (or any cloud provider) with zero data movement using Tapestry, the AI Insights Engine
DatumSure’s Tapestry turns multi-cloud data into governed AI insights in real time, executing queries where the data lives in AWS, Azure, and GCP and data lakes and analytics systems like Snowflake and Databricks, with zero movement.
The AI Insights Engine returns permissioned, auditable answers that cut risk, shrink cost, and speed decisions. Leaders stop waiting on pipelines and compliance resets, while analysts and business leaders get fresh results without creating new copies.
The Problem We All Feel
Most teams do not know exactly what is in each database, what format it is in, or which system is the one source of truth. Copies become outdated as soon as they are made. There are pipelines to build, normalization to create, feeds to maintain, and time-consuming compliance reviews that reset every time something changes. These realities create drag across the business. CEOs delay decisions, analysts wait for every answer, and models age before they ship. Risk grows with every export and shadow copy because the attack surface widens and governance fragments.
The Shift: An AI Insights Engine, Not More Infrastructure
Tapestry is an AI Insights Engine that brings the question to the data. It executes governed logic where your data already lives and returns permissioned, auditable answers in real time. There is no new store to feed, no extra copies to reconcile, and no sprawl for security to chase.
Augments Your Warehouses, Lakes, and Tools, Does Not Replace Them
Think of Tapestry as the intelligence that coordinates questions across the estate you already use. Your warehouses, data lakes, and BI tools stay in place. The AI Insights Engine orchestrates governed execution across them and unifies the answer without copying raw records.
Outcome: faster insight, tighter control, and AI insights you can ship using what you already own.
How It Works Safely and Effectively
Policy-aware execution. Every request is evaluated against roles, purposes, and data-owner rules before it runs.
Governed outputs. Results are permissioned, with masking, aggregation, or policy-based deny, and everything is auditable end to end.
Boundary-respecting merges. Only approved results cross accounts or clouds, and lineage plus policy context travel with the answer.
LLM guardrails. Retrieval and generation stay within governed limits so AI delivers permitted results, not unrestricted raw data.
How a Multi-Cloud Query Might Work
Imagine this question: What is our week-over-week churn risk by region and segment, plus top drivers?
The question is brought to each cloud account and project under native controls.
The compute takes place where the data resides, with no exports and no staging.
Governance is applied to mask sensitive fields, enforce purpose limits, and limit permissions.
An auditable answer is returned that can land in a dashboard or a copilot.
Following are two examples of how Tapestry may be used:
Education
Question: which student cohorts need support before midterms?
How it runs: the AI Insights Engine checks advisor permissions and purpose, executes next to SIS, LMS, and CRM records, suppresses small cells, and masks restricted fields
Answer: governed counts and risk bands by course and grade with lineage attached, no student records copied
Benefit: interventions in days, not months, with a transparent audit trail for compliance
Data Partners
Question: what is the weekly performance of a joint product across two companies, each on a different cloud?
How it runs: each partner executes the question inside its own cloud accounts, only permissioned and governed aggregates leave each boundary, and the AI Insights Engine compiles a shared, auditable view
Answer: harmonized KPIs and drivers that both parties can trust without exchanging raw data
Benefit: faster partner reporting and new monetization options without contracts to move data or prolonged security reviews
Why This Matters
Speed: real-time answers across clouds with fewer pipelines to build and maintain
Risk: no shadow copies, smaller attack surface, auditable by default
Cost: less storage, egress, and ETL churn, AI compute runs only where and when it is allowed
Focus: teams spend time on decisions and models, not on moving and reconciling data
How to Get Started
Pick one cross-cloud question that could solve a problem today.
Define purpose and roles, then set masking and threshold policies you already use.
Point the AI Insights Engine at your sources and run the question where the data lives.
Wire the governed, auditable answer into your dashboard or copilot.
Multi-cloud is not the problem. Copies are. Tapestry, our AI Insights Engine, turns AWS, Azure, and GCP into one governed mind for people and AI insights.
Ready to see your question answered without moving a byte? Let’s run one together.
About DatumSure
DatumSure is the technology company behind Tapestry, the AI-native Data Insights Engine 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.