The four pillars

One framework. Four services. Built to work together.

Each stage builds on the last. Data Sense produces intelligence. Data Ask consumes it. AI Warehouse provides the platform foundation. Agentic puts the build in the hands of the domain expert.

  • Understand

    Data Sense

    Application Knowledge Graph (AKG) · Content Intelligence · Intelligent Classification.

    Encodes the business objects, relationships, terms, and tested query patterns inside your enterprise applications — across the value streams every enterprise runs on. Pre-built AKGs for the major enterprise applications. The graph learns with use: confirmed answers become verified query patterns. Customer-supplied taxonomy on classification.

  • Answer

    Data Ask

    Natural-language access across structured + unstructured + hybrid.

    Grounded in the AKG with citations. One governed interface. Ask one question, get a synthesized answer that pulls from your databases AND your documents — rare in market.

  • Build

    AI Warehouse

    The governed foundation for customer-built AI applications.

    Apache Hudi lakehouse with ACID transactions. Ingestion + connectors. Data quality + preparation. ML Flow + BYOM. Sits on top of any data platform — no migration.

  • Activate

    Agentic

    Describe it. Build it. Run it.

    The domain expert describes the application in natural language. AI agents build and test it. The deployed application is alive — runtime agents power autonomous monitoring, alerting, and action.

    In-preview

What makes EAI different

Not a better toolkit. A different question.

Most platforms are racing to make developers faster. EAI changes who builds the application.

  • The incumbent question

    "Whose developer toolkit is better?"

    • Lakehouse and storage
    • ML model development
    • Notebook IDE
    • Developer ecosystem

    A race we choose not to enter.

  • EAI's question

    "Who builds the application?"

    • Platform-agnostic. Sits on top of any data platform — no migration.
    • Domain expert as the builder. Not the developer.
    • AI agents build and test. Domain intelligence + governance from day one.
    • Applications are alive. Runtime agents power autonomous monitoring.
Use cases

What EAI delivers.

1

Self-Service Enterprise Analytics

Business users ask questions across live production data in natural language. Grounded answers on demand.

2

Customer-Built AI Applications

AI Warehouse + Data Sense as the foundation for revenue optimization, risk mitigation, operational intelligence.

3

Dark Data Discovery & Classification

Intelligent Classification sorts records into customer-defined categories — driving retention, access, compliance.

4

Cross-Platform AI Intelligence

EAI services consumed by Solix CDP, EDG, ECS, and non-Solix platforms — one intelligence layer across the estate.

Need help getting EAI deployed?

20 years of services depth. Implementation, AKG Construction, AI Foundry Build, Managed Services.

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Deployment options

SolixCloud delivery platform: MTC, STC, on-premises, hybrid. Trust & Security from day one.

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See Enterprise AI on your data.

A guided walkthrough of Data Sense, Data Ask, AI Warehouse, and the Agentic pillar anchored on your specific use case.

See a guided walkthroughDownload Product Data Sheet (PDF)
Resources

Related Resources

Explore related resources to gain deeper insights, helpful guides, and expert tips for your ongoing success.

Frequently Asked Questions

FAQs for Solix Enterprise AI (EAI)

What is an enterprise AI platform?

An enterprise AI platform is a governed system that connects an organization's structured and unstructured data to AI so it can be understood, queried, and built on safely at scale, and Solix Enterprise AI delivers this today through Data Sense, Data Ask, and AI Warehouse.

How do you make enterprise data AI-ready without a full migration?

Solix Enterprise AI makes data AI-ready in place through governance, classification, and semantic mapping, so platform-agnostic deployment on a customer's existing lakehouse, warehouse, or on-premises system is demonstrable today without migrating to a new platform.

How can enterprises get accurate, grounded AI answers without hallucinations?

Solix Enterprise AI grounds every answer in the Application Knowledge Graph and returns cited, permission-aware results instead of unverified model output, reducing the hallucination risk of ungrounded AI.

What is the difference between AI-ready and AI-activated data?

AI-ready data is governed, validated, and preserved through CDP, ECS, and AI Warehouse, while AI-activated data is that same data put to work by Data Sense, Data Ask, and Agentic so it answers questions, powers applications, and eventually acts on its own.

What's the difference between an enterprise AI platform and an AI/ML developer platform?

Developer-focused AI/ML platforms compete on lakehouse storage, model development, and notebook IDEs built for data engineers, while Solix Enterprise AI is built so the domain expert, not the developer, can query, build, and eventually operate AI applications directly.