30s to get it, 7d to prove it.
The Semantic Intelligence Infrastructure for AI-Ready Enterprise Data
Arisyn Semora is a governed semantic query layer for enterprise structured data. It turns business questions into trusted SQL, explainable answers, and traceable data logic — powered by IntaLink’s relationship discovery engine.
Question
Which regions’ sales decline is linked to inventory mix changes?
Detected business concepts
Metric: Sales
Related entity:Inventory
Dimension: Region
Time range: Last quarter
Relationship path discovered by IntaLink
sales_order
→
product_sku
→
inventory_snapshot
→
warehouse_region
Governed SQL path generated
SELECT r.region_name, SUM(s.net_sales) AS sales,
AVG(i.mix_variance) AS inventory_mix_change
FROM sales_order s
JOIN product_sku p ON s.sku_id = p.sku_id
JOIN inventory_snapshot i ON p.sku_id = i.sku_id
JOIN warehouse_region r ON i.warehouse_id = r.warehouse_id
Returned insights
West region inventory imbalance increased 17%
Sales decline correlates with SKU concentration
Confidence: High
Lineage included
Semora Query Workspace
— Product Definition
What is Semora?
Most organizations invest heavily in data infrastructure—data lakes, data warehouses, data pipelines, and business intelligence tools. However, the fundamental problem remains: business users cannot directly ask questions that data can effectively answer.
The Arisyn Semora Semantic Layer platform changes all that. It sits between raw data structures and business understanding, creating a controlled layer of business semantics, relationships, and queryable intelligence that makes enterprise data truly accessible.
This is not just another business intelligence tool, nor is it a metadata directory or search engine. It is a specially built semantic intelligence platform that directly connects business language with data logic, and possesses complete governance, traceability, and explainability.
Without a semantic engine
✕ Business users do not know which table to query.
✕ LLMs guess fields, joins, and definitions.
✕ Metric definitions drift across teams.
✕ Data teams become the bottleneck
for every question.
With Arisyn Semora
✓ Business language maps to governed data structures.
✓ SQL is generated with relationship context.
✓ Every answer is traceable to fields, joins, and logic.
✓ Data teams control semantics, policies, and quality.
How Semora works
Ask a question
Natural language processing, structured queries, APIs
Map to governed semantics
Mapping, reasoning, and intent interpretation
Resolve relationships with IntaLink
Data source, schema, relationship diagram
Generate SQL, results, and lineage
Return the data results for your query
Platform capabilities → value to you
Each capability serves one goal: understand real data relationships faster.
🧠
Natural language query
Ask your business question directly—get structured insights and results fast.
🗂️
Auto relationship discovery
Find links from data itself—not just column names.
🔎
Cross-system analysis
Link data across
systems—no more
manual matching upfront.
🛡️
Auto SQL path generation
Output multi-DB/table join paths & SQL logic—faster validation and execution.
✅
Explainable Answers
Return results with query logic, source trace, lineage, and confidence signals.
Interactive demo → get business results fast
Step 1
Enter a question
" Which regions’ sales drop is linked to inventory mix? "
Step 2
System maps relationships
Inclusion analysis, cross-system linking, path computing…
Step 3
Results returned
Trend change cards
Key anomaly list
Multi-table join path suggestions
— Working principle
From Business Issues to Governance Insights
A seven-stage journey to transform natural language into decision-level semantic intelligence.
💬
🧠
📖
🔗
⚙️
📊
✅
STEP 01
Questions raised
Business users submit issues in natural language
STEP 02
Semantic Recognition
Semantic engines identify business concepts and intents
STEP 03
Term mapping
Business terms have been parsed into semantic objects and metrics.
STEP 04
The relationship has been resolved.
Metadata context and relationships
STEP 05
Query Arrangement
Application governance builds optimal query paths
STEP 06
Result
The structured results have been assembled and include complete phylogenetic information.
STEP 07
Insight delivery
Presenting well-reasoned and explainable business insights
— Architecture
Layered architecture for
enterprise-level semantic
intelligence
The three foundational layers work together—from the raw data infrastructure to the Arisyn Semora semantic engine, and then to every application and decision layer that relies on controlled data understanding.
Business Intelligence and Analytics
Semantic query results can bedirectly imported into analytics dashboards and reporting tools.
Natural Language Query
A pure language interface powered by a semantic engine, suitable forad-hoc exploration.
Artificial intelligence andintelligent agents
Semantic basis of Al assistants, co-pilots, and decision support systems
Embedded Analysis
Semantic API for embedding controlled data intelligence intooperational applications
Executive Report
Consistent KPI definitions and indicator hierarchy across allexecutive views
Insight and Application Layer
Application areas of semantic intelligence
ARISYN SEMANTIC LAYER PLATFORM
Semantic intelligence engine
Intent interpretation, relational reasoning, semantic mapping execution
Map layer
Business terminology analysis,technology mapping, and synonymmanagement
governance
Access control, policy enforcement,audit trail, version management
Query Interpretation Layer
Natural Language Processing,Query Planning, Optimization, andResult Assembly
Insight into the delivery layer
Result formatting, genealogyembedding, and interpretationgeneration
Arisyn semantic layer
Managed semantic intelligence platform
DATA AND RELATIONAL FOUNDATIONS
Data warehouse
Structured analytical data from enterprise data warehouses anddata marts
Data Lake
Semi-structured and unstructured data with metadata enhancement
Data Pipeline
ETL/ELT pipeline with column-levellineage and transformation metadata
operating system
ERP, CRM, SCM, and otheroperational systems as semanticsource objects
Relationship diagram
Cross-system entity relationships,foreign key mappings, and domainlinks
Data and Relational Foundations
Original data infrastructure andrelationship diagrams
Use cases
01
Manufacturing
Problem: Sales, inventory, and production data are siloed—slow issue diagnosis.
Use: Arisyn Semora links multi-system data to reconstruct impact paths fast.
Value: Faster alignment on decisions and execution priorities.
02
Retail
Problem: Manual data stitching for reviews; hard to align metrics across channels.
Use: Discover cross-table links and generate analysis paths automatically.
Value: Shorter review cycles, faster campaign iteration.
03
Finance
Problem: Reconciliation and risk analysis prep is time-consuming; high coordination cost.
Use: Auto-generate join paths and SQL logic, with human validation.
Value: More stable analysis and compliance workflows.
Built for business users and trusted by data teams.
Arisyn Semora lowers the barrier for business users while giving IT and data teams the governance they require.
👩💼
Business teams
Ask business questions directly and receive answers grounded in approved enterprise data.
👨💻
Data teams
Manage semantic definitions, mappings, access rules, and query validation in one workflow.
🏢
Executives
Improve decision speed while reducing data preparation cost and AI answer risk.