Intugle is an Agentic AI platform for data teams that transforms raw enterprise data into AI-ready insights through intelligent agents and semantic understanding. It connects to 50+ data sources and helps build GenAI-powered applications.

What data sources does Intugle support?

Intugle supports 50+ data sources including Snowflake, Databricks, PostgreSQL, MongoDB, MySQL, BigQuery, Redshift, S3, Google Cloud Storage, Azure Blob Storage, and many more enterprise databases and cloud storage solutions.

Is Intugle secure and compliant?

Yes, Intugle is SOC 2 Type II and ISO 27001 certified. We maintain the highest security standards for enterprise data protection and compliance.

v2.0 Live

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Transform Your Data IntoGenAI-Powered Apps

Build an intelligent semantic data graph once. Power infinite AI applications.

Start vibing with your data

1Connect Data Sources

2Build Semantic Graph

3Power AI Apps

Connect Your Data Sources

Seamlessly integrate with your existing data infrastructure

MySQL

Connect to MySQL databases

PostgreSQL

Connect to PostgreSQL databases

Snowflake

Connect to Snowflake data warehouse

Databricks

Connect to another Databricks workspace

Salesforce Data Cloud

Connect to Salesforce Data Cloud (Data 360)

Amazon Redshift

Connect to Amazon Redshift data warehouse

SQL Server

Connect to Microsoft SQL Server

Google BigQuery

Connect to Google BigQuery

Oracle

Connect to Oracle Database

Amazon S3

Connect to Amazon S3 buckets

Azure Blob Storage

Connect to Azure Blob Storage

Azure Data Lake Gen2

Connect to Azure Data Lake Storage Gen2

Vibe Engineer Your Data Stack

Everything you need to build intelligent data applications

Semantic Data Graph

Semantic intelligence autonomously built on data, enabling LLMs with context.

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AI-Powered Data Agents

Purpose-built AI agents that understand your semantic graph to transform and explore data using natural language.

What you can do:

Join TablesFilter & AggregateBuild PipelinesData ProfilingCreate ChartsExport ReportsPredict TrendsSchedule Jobs

Data Transformation

Intelligent code generation

"Join sales, products & customers, calculate revenue by category, YoY growth%"

Generating SQL...

SELECT p.category,
  SUM(s.amount) as revenue,
  LAG(SUM(s.amount), 12) 
    OVER(ORDER BY month) as yoy,
  ROUND(100.0 * (SUM(s.amount) - 
    LAG(SUM(s.amount), 12) 
    OVER(ORDER BY month)) / 
    NULLIF(LAG(SUM(s.amount), 12) 
    OVER(ORDER BY month), 0), 2) as growth_pct
FROM sales s
JOIN products p ON s.id = p.id

Data Analysis

Instant visual insights

"What factors are leading to revenue decline?"

• Product returns up +23%

• Customer churn increased +18%

• Avg order value down -12%

Impact by Region

Returns

Churn

AOV

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Build Intelligent Data Applications

Leverage the intelligence from your semantic graph to power a variety of data applications

Data Products

Select attributes, auto-generate unified views

RAW DATA

CRM·customers

✓ cust_id✓ nameemailph

ERP·sales_orders

✓ total_val✓ ord_cntstatus

SVC·service_requests

✓ tickets✓ npspriority

FEDERATED QUERY

SELECT c.id, SUM(o.val)
FROM crm.cust c JOIN erp.ord
ON c.id = o.cust_id

DATA PRODUCT

Customer 360Ready

Schedule

Access

Integrate

Coming Soon

Chatbots

Configure & preview your analytics chatbot

Configuration

Source

15 tables

KPIs

23 defined

Instructions

7 enabled

Tools

4 active

Web Search[ON]

Visualization[ON]

Unstructured[OFF]

Autocorrection[ON]

Fewshot[ON]

Integration

MCP

Access

48 users

LLM Model

GPT 5.2

Preview

Summarize Q4 business performance

Creating analysis plan

Identifying tables & attr

Gathering context

Generating query

Q4 Highlights:

• Rev: $8.2M (+15% YoY)

• New customers: 2,340

• Top product: Widget Pro

• Best region: APAC

Coming Soon

AI Models

Build models with natural language

Forecast

Revenue Q1

Causal

Campaign +18%

Anomaly

3 alerts

Prediction

Build a churn prediction model for customers in NoAM region for next 90 days

1.Data preparation: 3 tables | 12.4K rows | NoAM

2.Feature engineering: 23 features | tenure | usage

3.Model training: XGBoost | 80/20 | 5-fold CV

4.Validation: holdout | calibrated

Model Ready:

AUC: 0.94 | Precision: 89% | Recall: 82%

Top predictors: tenure, usage_decline, support_tickets

High-risk customers: 234

Measurable Impact

Real results from enterprises transforming their data operations

90%

Contextual Accuracy

AI-powered semantic understanding delivers precise, context-aware insights from your enterprise data.

10x

Hyperacceleration

Automate data preparation and modeling tasks that used to take weeks into hours.

50%

Cost Savings

Cut your data engineering spend in half with automated pipelines and intelligent resource management.

Data Democratization

Enable business users to generate deeper insights from data without technical expertise.

Ready to Transform Your Data?

Join leading data teams using Intugle to build intelligent data applications

Talk to Us!

Have questions? Fill out the form and our team will get back to you shortly.