Arisyn Platform
The Enterprise Data Intelligence Infrastructure for the AI Era
Arisyn helps organizations make structured data understandable, connected, governed, and AI-ready. By combining semantic intelligence, data relationship infrastructure, and natural language interaction, Arisyn enables AI agents, analytics platforms, and business teams to query, reason, and act on trusted enterprise data.
· Metadata-only by default
· Governed semantic layer
· Trusted relationship graph
· VPC-ready deployment
· API & MCP ready
High-risk segment
(last 30 days)
Real-time
analysis
12,486
Auto-aggregates customer, credit, overdue, and transaction data—outputs risk tiers
Business query
NL Query
“Show risk distribution of clients with loans >1M in last 3 months and overdue records.”
Persona-based Value
Built for the Teams Making Enterprise Data AI-Ready
👩💻
For Data Engineers
Reduce manual schema analysis and map keys, constraints, and join paths into a trusted relationship graph.
🛠️
AI Agent Teams
Give agents approved metadata, semantic definitions, access rules, and query context.
💬
Analytics Teams
Align metrics, dimensions, formulas, and BI logic with the way the business operates.
📈
Governance Teams
Review semantic changes, enforce masking and permissions, and audit generated SQL.
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 disconnected from data
Metrics, dimensions, formulas, and business terms often live in dashboards, documents, or team knowledge instead of the metadata AI systems use at query time.
🕸️
Data relationships are hidden in legacy logic
Join paths and foreign-key-like relationships are often buried in SQL scripts, ETL pipelines, BI models, and application code rather than represented as a trusted graph.
⚙️
AI answers cannot be trusted without governance
Without approved semantic definitions, masking rules, row-level policies, and query lineage, AI-generated SQL can become inconsistent, insecure, or difficult to explain.
Arisyn solves this by combining governed semantic definitions and a trusted relationship graph into one governed context layer for enterprise AI and analytics
Platform Perspective
Beyond BI. Beyond chat-based querying.
Architecture Collaboration
Intalink + Semora:Where Data Foundations Meet Intelligent Systems
Intalink establishes the foundation of data relationships and metadata, while Arisyn delivers the intelligent interface for query and analysis—together creating an end-to-end loop from data foundations to business insight.
INTALINK Data Relationship Layer
🗄️
Multi-Source Data Connectivity
DB / DW / Lake
🕸️
Relationship Network Modeling
Tables / Fields / Tags
🔄
Lineage Tracking Engine
Impact / Upstream/ Downstream
📋
Metadata Management
Description /
Version / Tags
🔍
Relationship Discovery Algorithms
Cross-Source / Semantic Similarity
Semantic Engine Application Layer
🗣️
Semantic Understanding Engine
Intent / Context
💬
Intelligent Query Interface
Natural Language / SQL
🛡️
Semantic Governance Platform
Mapping /
Version / Audit
⚙️
Analysis Orchestration Engine
Workflow /
Metrics / Scheduling
📊
Insight Delivery Layer
Reports / Alerts / APIs
User Layer · End-to-End Business Loop
💬
Natural
Language Query
→
🧠
Semantic
Understanding
& Mapping
→
🗺️
Relationship-Aware Query Path
→
📊
Cross-Source Data Integration
→
💡
Explainable Insight Output
→
🎯
Decision Support
How Arisyn Works
Connect metadata, define business meaning, discover relationships,
and serve query context to AI and analytics systems.
🧩
01
Connect Metadata
Connect schemas, tables, columns, constraints, and metadata without moving raw business data.
📐
02
Govern Semantics
Define business terms, metrics, dimensions, formulas, and approved query logic in Semora.
🌐
03
Discover Relationships
Identify trusted relationships, join paths, inferred keys, and cross-system schema connections in IntaLink.
🚚
04
Serve Intelligence
Expose semantic definitions, relationship graph context, access rules, and lineage through APIs, MCP services, AI agents, BI tools, and analytics workflows.
Use Cases
Intelligent data scenarios across
core business domains
The Semantic Engine Platform is not limited to any specific industry. It is built for any organization that relies on data-driven decision making—from supply chain and finance to sales and operations.
🚚
01
Inventory & Supply Chain Analytics
Query inventory levels, turnover rates, and supplier performance in natural language—quickly identify anomalies and support procurement decisions.
📈
02
Sales & Business Q&A
From regional performance to monthly targets, ask in natural language and get answers grounded in multi-table relationships—complete with data lineage for full transparency and trust.
💰
03
Financial Drill-Through Analysis
Connect financial ledgers with operational systems through a semantic layer that links accounts to business metrics—enabling unified, natural language queries across finance and operations.
🔗
04
Cross-Domain Business Insight
Reveal hidden relationships across systems and business domains. Replace manual mapping with automated discovery—making complex data easier to understand and navigate.
🎛️
05
Executive Intelligence & Q&A
A natural language interface for leadership teams to query KPIs, trends, and anomalies—without relying on BI specialists.
🛡️
06
Knowledge Enrichment & Governance Collaboration
The semantic governance platform enables the execution of data standards, while field mapping and lineage tracking make data quality issues traceable and diagnosable.
Enterprise-Grade Foundation
Built for enterprise environments, at platform scale
From access control to audit logging, from multi-tenant isolation to high-availability architecture, the Semantic Engine Platform is designed to meet enterprise standards at every layer.
🔐
Access Control & Multi-Tenancy
Fine-grained data access control at the row and column level, with multi-tenant isolation and seamless integration with enterprise SSO systems.
📝
Audit & Version Control
Comprehensive audit logs, full change history tracking, and semantic version management—supporting compliance and governance at scale.
⚡
Multi-Source Integration Framework
Supports leading data engines including MySQL, PostgreSQL, ClickHouse, StarRocks, and Doris.
🧩
High-Availability Architecture
Built on distributed deployment with automatic failover and horizontal scaling—ensuring reliability and enterprise-grade SLA.
📐
Explainable & Traceable
Every query result is fully traceable—back to its data sources, lineage paths, and underlying analytical logic.
🏗️
Extensible Semantic Layer
The semantic model supports dynamic expansion and incremental updates—allowing the platform to evolve continuously without downtime.
🔌
Audit & Version Control
Comprehensive audit logs, full change history tracking, and semantic version management—supporting compliance and governance at scale.
🌐
Local Ecosystem &
Compliance Support
Fully compatible with local operating systems, databases, and middleware—meeting regulatory and compliance requirements.
Persona-based Value
Built for the Teams Making Enterprise Data AI-Ready
👩💻
For Data Engineers
Reduce manual schema analysis and map keys, constraints, and join paths into a trusted relationship graph.
🛠️
AI Agent Teams
Give agents approved metadata, semantic definitions, access rules, and query context.
💬
Analytics Teams
Align metrics, dimensions, formulas, and BI logic with the way the business operates.
📈
Governance Teams
Review semantic changes, enforce masking and permissions, and audit generated SQL.
Get Started
From data relationships to semantic understanding.
From intelligent queries to business insight.
Build a data intelligence entry point that works in the real world—where every business question is answered with intelligence that is trusted, explainable, and traceable.
Works with Your Existing Data Stack
Arisyn complements your existing warehouses, databases, BI platforms, AI agents, and application workflows by serving context through APIs and MCP.
Data Warehouses
-
Snowflake
-
BigQuery
-
Databricks
-
Redshift
Databases
-
PostgreSQL
-
MySQL
-
SQL Server
-
Oracle
AI & Agent Interfaces
-
MCP
-
REST API
-
AI Agents
-
LLM Applications
Analytics & BI
-
BI Platforms
-
Dashboards
-
Data Apps
-
Analytics Workflows