Arisyn Platform
Stop AI from guessing how your tables join.
Arisyn discovers, validates, and governs table relationships and business definitions across your data stack — so AI agents, NL2SQL workflows, and BI tools can generate SQL you can trust.
Discover trusted join paths automatically
Ground SQL in approved business definitions
Explain every answer with lineage, confidence, and policy context
· Metadata-only by default
· Governed semantic layer
· Trusted relationship graph
· API & MCP ready
· VPC-ready deployment
· No raw data required.
AI Agents
BI Tools
Analytics Apps
Data Teams
Arisyn Platform
Semora
Governed Semantic Layer
IntaLink
Trusted Relationship Graph
User Question
“What is customer lifetime value by region last quarter?”
Semora resolved
Metric
Customer Lifetime Value
Dimension
Time
Region
Last quarter
IntaLink found
customers
→
refunds
→
→
orders
regions
96% confidence
Governed Output
SQL
Lineage
Access policy explanation
Snowflake
BigQuery
Databricks
PostgreSQL
Oracle
SQL Server
Why Enterprise Data Fails AI
AI can generate SQL, but enterprise data requires approved definitions, validated relationships, access controls, and lineage before answers can be trusted.
🗣️
Business meaning is not in the database
Metrics, formulas, dimensions, and business terms often live in dashboards, documents, and team knowledge — not in the metadata AI uses at query time.
🕸️
Data relationships are hidden
Join paths and foreign-key-like relationships are often buried in SQL scripts, ETL jobs, BI models, and application logic.
⚙️
Generated SQL is hard to trust
Without governed definitions, access rules, masking, and lineage, AI answers are inconsistent and risky.
The Missing Context Layer
Between Enterprise Data and AI
Arisyn connects warehouse metadata, semantic definitions, relationship graphs,
access policies, and lineage so AI systems can understand what to query and how to query it.
AI & Analytics Consumers
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AI Agents
-
BI Platforms
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Natural Language Query
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Analytics Apps
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Data Workflows
Arisyn Platform
-
Semora
-
Query Context
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IntaLink
-
Access Governance
-
SQL Lineage & Audit
Enterprise Data Systems
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Data Warehouses
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Databases
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Data Lakes
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Operational Systems
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Metadata Catalogs
Arisyn does not replace your warehouse, BI stack, catalog, or AI framework. It adds the missing context layer: governed semantic definitions from Semora and a trusted relationship graph from IntaLink, exposed through APIs, MCP, and enterprise workflows
Two Intelligence Layers.
One AI-Ready Data Platform.
Arisyn brings Semora and IntaLink together so business meaning and data relationships are available as
query-time context for AI agents, NL2SQL workflows, BI tools, and analytics applications.
SEMORA
Governed Semantic Layer
Semora maps business terms, metrics, dimensions, formulas, and approved query logic to the physical fields and tables AI systems need to use.
Business glossary and metric governance
Semantic mapping between business concepts and data fields
Approved calculation and aggregation logic
Natural language query grounding
Semantic access controls
Versioned semantic assets
Turning business language into trusted data context.
INTALINK
Trusted Relationship Graph
IntaLink discovers, validates, scores, and serves table relationships, foreign keys, inferred keys, join paths, and cross-system schema connections as a trusted graph.
Automated relationship discovery
Trusted join path analysis and scoring
Cross-source schema graph
Relationship validation from metadata and query patterns
API and MCP relationship services
Query lineage and explainability
Helping AI and data teams discover the right data connections automatically.
Semora tells AI what the business means.
IntaLink tells AI how the data is connected.
Arisyn combines both with access rules, masking, and lineage so generated SQL can be grounded in approved metadata and explainable join paths.
Business Meaning
+
Data Relationships
=
Trusted AI Query Context
Why Arisyn Is Different
Arisyn is not another catalog, a standalone semantic layer, or an NL2SQL wrapper. It provides the metadata, definitions, relationships, policies, and lineage AI systems need before they generate SQL.
1
Beyond data catalogs
Catalogs help teams find assets. Arisyn turns metadata into query context by connecting semantic definitions, join paths, access rules, and lineage.
2
Beyond semantic layers
Semantic layers define business meaning. Arisyn pairs Semora's governed definitions with IntaLink's relationship graph so AI can understand both meaning and structure.
3
Beyond NL2SQL-only tools
NL2SQL tools translate questions into queries. Arisyn supplies the approved metrics, validated join paths, masking rules, and lineage context those tools need.
Arisyn is not another place to document data. It is a governed context layer that AI and analytics systems can use at query time.
From Business Question to Governed SQL
Arisyn turns business intent into SQL by grounding every step in approved semantic definitions, validated join paths, access rules, masking policies, and lineage.
“What is our customer lifetime value by region for last quarter?”
1
Understand Business Intent
Semora identifies customer lifetime value, region, and last quarter as approved business concepts.
4
Apply Access Policies
Arisyn checks permissions, masking rules, and governed query constraints.
2
Resolve Semantic Definitions
Semora maps business language to approved metrics, dimensions, and calculation rules.
5
Generate Governed SQL
The platform generates SQL grounded in approved semantics and trusted relationships.
3
Discover Trusted Relationships
IntaLink identifies validated relationship paths between customers, orders, refunds, and regional dimensions.
6
Explain Lineage and Policy Decisions
Arisyn returns SQL with lineage, relationship paths, and access policy explanations.
Core Platform Capabilities
The platform capabilities data teams need to make structured enterprise data usable by AI agents, analytics workflows, and governed BI experiences.
Semantic Governance
Manage business terms, metrics, dimensions, formulas, ownership, and approved query definitions.
Relationship Discovery
Discover and validate table relationships, inferred keys, join paths, and cross-system schema connections.
AI Query Grounding
Provide LLMs and NL2SQL systems with governed metadata, semantic definitions, and trusted relationship context.
Access Control & Masking
Apply semantic permissions, row-level controls, column masking, and approved data access policies.
Lineage & Explainability
Trace generated SQL, semantic definitions, relationship paths, and policy decisions back to source metadata.
API & MCP Integration
Expose governed query context to AI agents, BI tools, data apps, and enterprise workflows through APIs and MCP.
Built for the Teams Making Enterprise Data AI-Ready
For Data Engineers
Reduce manual schema analysis, relationship mapping, and join-path discovery across complex enterprise systems.
AI Agent Teams
Give agents governed metadata, business definitions, relationship context, and policy-aware query constraints before they generate SQL.
Analytics Teams
Align metrics, dimensions, formulas, and BI logic so business users get consistent answers across tools and teams.
Governance Teams
Review semantic changes, enforce access policies, audit generated SQL, and explain how every answer was produced.
Try Arisyn with Sample Metadata
No raw data required. Explore the workflow before connecting your enterprise systems.
Ask business questions
See how natural language maps to approved metrics, dimensions, and calculation logic.
Inspect semantic definitions
Review glossary terms, formulas, field mappings, owners, and versioned semantic assets.
Explore trusted join paths
See how IntaLink discovers and scores relationships across tables and systems.
Review governed SQL context
Inspect generated SQL, lineage, access rules, masking decisions, and relationship explanations.
Enterprise-Ready by Design
Arisyn is designed for metadata-focused processing, enterprise-controlled deployment,
governed access, and auditable AI data workflows.
🔐
Metadata-Only Processing
Start with schemas, tables, columns, constraints, and metadata — no raw business data required for evaluation.
🔌
Audit and Version Control
Track semantic changes, relationship updates, generated SQL, and governance actions.
📝
Private and VPC-Ready Deployment
Support enterprise-controlled deployment models for sensitive data environments.
⚡
Explainable Query Context
Show how each answer was produced through metrics, fields, relationships, policies, and lineage.
📐
Access Control and Masking
Apply fine-grained permissions, row-level controls, column masking, and semantic access policies.
🧩
Enterprise Integration
Connect with warehouses, databases, BI tools, AI agents, REST APIs, and MCP workflows.