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30s to get it, 7d to prove it.

Ask a business question.

Data auto-connects.
Get accurate,
verifiable results.

Arisyn Semora helps business teams see answers faster.
Powered by Intalink, it auto-links data—no manual matching, querying, or checking first.

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Why is traditional data analysis inefficient?

Traditional

Wait on IT → slow response
Rewrite SQL → high prep cost
Cross-system links → manual checks

Arisyn Semora

Ask in NL → see direction first
Auto-find links → less upfront work
Faster path → actionable analysis

— Product Definition

The semantic operation layer your enterprise has been missing

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.

Platform Components

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Query and Insight Interface

Natural language processing, structured queries, APIs

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Governance and Policy Level

Access control, version control, audit trail

Semantic intelligence engine

Mapping, reasoning, and intent interpretation

Data and Relational Foundations

Data source, schema, relationship diagram

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

Questions raised

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.

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What do enterprises gain?

Quantify the value—decide fast if it’s worth a try.

60%-80%

Faster query efficiency

50%-70%

Less reliance on IT

55%-75%

Shorter analysis prep time

Note: Sample data. Actual results vary by data, complexity, and setup.

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.

READY TO TRY

Start with a real use case—run a 7d PoC.

No system changes / fast validation.See value first, then decide.

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