—— Agent-Ready Data Platform
Ready for Agents
Governed by Design
Aralia is the governed data foundation between enterprise data and AI agents.
- Multi-Agent Compatibility
- Enterprise Trust
- Data Sovereignty
Enterprise Data
CRM
Customer
ERP
Operations
SCM
Supply Chain
DOC
Documents
Aralia Agent-Ready Data Platform
AI-Connected Layer
MCP · Access Control · Traceability
Semantic Layer
Metadata · Glossary · Knowledge Graph
Data Planet Layer
Independent governance · Zero-copy collaboration
HR
OPS
FIN
MKT
MCP
Gateway
Trusted Agent Access
AI Agent
Ask · Reason · Act
—— Why Aralia
A reusable data foundation
Changes the economics of AI
Aralia reduces repeated data work, preserves ownership and control, and gives teams a more trusted foundation for putting AI into production.
Efficiency
Prepare Once.
Reuse Across AI.
Prepare data once, then reuse it across agents, models, and applications — without repeating project-by-project work.
Sovereignty
Keep Ownership.
Share Insights.
Keep each Data Planet under its owner’s control while enabling authorized cross-domain insights without exchanging raw data.
Trust
Trace Every Answer.
Act with Confidence.
Trace AI answers back to governed data and context, so teams can make decisions with greater confidence.
Business Impact
Faster Time-to-AI
Shorten the path from data onboarding to usable agent experiences.
Lower Data Preparation Cost
Reuse prepared data instead of repeating project-by-project work.
More Trusted Decisions
Ground decisions in governed context with traceable sources.
Lower AI Reasoning Cost
Reduce avoidable search, retries, and token consumption.
Today’s application-centric data landscape
BI Dashboard
ERP Console
AI Project
CRM
POS
SCM
Files
Every new use case creates another path through fragmented systems.
—— Challenges
Enterprise data was
built for applications
Agents need more
AI agents need to work across systems, understand business context, and respect access rules. Today’s application-centric data stack was not designed for that operating model.
Data is fragmented
across systems.
One question may depend on CRM, ERP, POS, documents, external data, and more — each with its own structure and ownership boundary.
Structured is not
the same as understood.
Tables and fields rarely carry enough business meaning for agents to interpret them consistently across departments or domains.
Access is possible.
Trust is harder.
Permissions, context, provenance, and traceability are often rebuilt project by project — making AI difficult to scale safely.
The bottleneck is no longer access alone.
Enterprise data must be understandable, governed, and reusable across agents.
—— Platform
One Architecture
Three Layers
Aralia adds the three persistent layers agents need between distributed enterprise data and AI:
Governed Data, Shared Meaning, and Trusted Access.
AI Agents
ARALIA AGENT-READY DATA PLATFORM
AI-Connected Layer
Trusted Agent Access
MCP Gateway
Capability Discovery
Access Control
Full Traceability
Semantic Layer
Shared Meaning
Metadata
Business Glossary
Knowledge Graph
Document Library
Data Planet Layer
Independent Governance
HR
OPS
FIN
MKT
Ownership Boundaries
Independent Control
Zero-Copy Interoperability
FAIR Data Re-Engineering
Standardize · Structure · Enrich · Prepare
Enterprise Raw Data
Databases · Files · Systems · Streams
Foundation Principle
Point-n-Play. Not Rip-n-Replace.
Keep the enterprise systems and data architecture you already have. Aralia adds the Agent-Ready foundation AI needs without replacing your existing data stack or ownership boundaries.
FAIR + Semantic
Make data ready and understandable.
FAIR re-engineering standardizes structure and metadata, while the Semantic Layer adds the business meaning and relationships agents need across systems.
Data Planets + Zero-Copy
Keep ownership while enabling collaboration.
Data Planets keep governance and ownership boundaries explicit, while authorized analysis can span domains without exchanging raw row-level data.
MCP + Trusted AI Access
Give agents governed, traceable access.
MCP-compatible agents discover and query through one governed access path, with permissions and traceability built into each interaction.
Governance is enforced by the architecture, not by policy promises.
Access control, ownership boundaries, and traceability are built into how data is prepared, governed, and accessed by AI agents.
—— Proof
One proof pattern in agriculture
A platform for many domains
This smart agriculture deployment demonstrates how Aralia connects distributed, independently governed data for cross-domain decision support. The same architecture can support enterprise, public-sector, and cross-organization use cases across industries.
Distributed Data
Weather, production, market, and operational datasets remain aligned with their own management and governance boundaries.
Aralia Data Planets
Data is prepared, semantically aligned, and served through governed access in independently managed Data Planets.
Decision Insight
AI and analysts correlate signals across sources for earlier warning, faster coordination, and more informed policy or operational action.
—— Growth
Start with your data
Grow into an ecosystem
Begin with one use case and one governed Data Planet. Expand across teams, public data, partners, and data spaces while preserving governance and ownership boundaries.
One Use Case
Start with one team, one data scope, and one clear AI question.
Enterprise Data
Add more independently managed Data Planets across departments and systems.
Private × Public
Enrich internal data with AraliaOne and other governed external sources.
Ecosystem
Extend collaboration across organizations, partners, and interoperable Data Spaces.
Start small. Scale fast. Keep governance and ownership boundaries intact as the network grows.
LOOKING AHEAD · ARALIA GALAXY (In Progress)
From connected organizations to a broader distributed data ecosystem.
Aralia Galaxy extends the same governed model beyond individual organizations — enabling data discovery and collaboration across a wider ecosystem without transferring data ownership.
—— See It for Yourself
Two ways to explore
before you talk to us
See the platform in action through a public showcase or a private environment before moving into a broader deployment discussion.
Public Demo
AraliaOne
Explore a live showcase built on cross-domain public data. See how Data Planets make diverse datasets reusable and ready for AI-driven analysis.
Private Trial
AraliaCloud
Create a private environment for your own Data Planet, prepare your data, and test governed AI access with your own scope.
Make your data ready for agents.
Bring one priority use case and the data behind it. We’ll show how Aralia can fit into your current environment.