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Cross-Platform Agentic Data & AI Automation

Leverage intelligent agents to automate and accelerate the entire analytics lifecycle across Microsoft Fabric, Snowflake, Databricks, and more.

Integrates with:
Microsoft Fabric Snowflake Databricks
Why iSpark?

Beyond Standard Integration

Democratizing data intelligence by liberalizing the Model Context Protocol (MCP) for business users—delivering impact where standard agents stop.

Liberalizing MCP for Business

We unlock the Model Context Protocol (MCP) for everyone. Unlike technical-only tools, iSpark empowers business users to drive complex data workflows directly, bridging the gap between raw data and real-world business strategy.

More Than Just "Connectors"

Standard agents from Fabric, Snowflake, or Databricks often stop at basic automation. iSpark brings intelligent orchestration, context-aware reasoning, and cross-platform synthesis that out-of-the-box solutions simply don't offer.

Unified & Framework Agnostic

Avoid vendor lock-in. iSpark operates above the platform layer, allowing you to switch, combine, or migrate engines without rewriting your business logic or losing your trained agentic intelligence.

Platform Overview

Unify Data Engineering, Modeling, and Reporting

From data ingestion to advanced analytics and operational dashboards, iSpark unifies the entire workflow in a seamless, automated platform powered by intelligent AI agents.

Key Capabilities

End-to-End Lifecycle Automation

Reusable AI Agents handle requirement capture, data assessment, modeling, testing, deployment, and managed operations across platforms.

Multi-Platform Data Integration

Seamlessly ingest, unify, and govern structured and unstructured data across Microsoft Fabric, Snowflake, Databricks, and other platforms.

Automated Analytics & Modeling

Generate predictive, prescriptive, and descriptive models tailored to platform-specific data structures.

Intelligent Reporting & Visualization

Power BI dashboards and semantic models automatically recommended by agents, independent of underlying data platform.

Operational Monitoring & Optimization

Continuous health checks, anomaly detection, and automated performance tuning across all environments.

Benefits

Accelerated Delivery

Accelerates analytics delivery across diverse, large-scale platforms with AI-powered automation.

Reduced Manual Effort

Reduces manual effort with intelligent agent-driven automation across the entire lifecycle.

Data Quality & Governance

Ensures data quality, governance, and actionable insights at every stage of your data journey.

Unified Real-time Insights

Provides unified, real-time reporting and predictive intelligence across multiple systems.

AI Agents

Intelligent Agents for Every Stage

Each agent specializes in a specific aspect of the data lifecycle, working together to deliver end-to-end automation and intelligence.

Analytics Lifecycle

Lifecycle Overview

A concise snapshot of the agent-driven lifecycle. See the full breakdown on the Overview page.

1

Requirements & Business Understanding

2

Data Assessment & Discovery

3

Architecture & Design

4

Ingestion & Integration

5

Modeling & Analytics Development

6

Testing & Validation

7

Deployment & Operationalization

8

Managed Operations