Megamind – Turn Enterprise Data into Powerful Models
Use big data technologies to transform your corporate data into reusable analytical and feature models that your AI and LLM platforms can trust.
The Data Foundation Behind Your AI
LLMs and AI assistants are only as good as the data that feeds them. Megamind focuses on the hard part: turning scattered, heterogeneous enterprise data into clean, structured and governed models.
By centralizing data pipelines and model definitions, Megamind gives your organization a single, consistent layer of truth that downstream systems such as Spell can rely on – without duplicating logic in every application.
Connect to databases, warehouses and lakes
Build scalable pipelines on big data technologies
Publish reusable data and feature models
Serve models to Spell and other platforms
Connect to the Systems You Already Use
Megamind integrates with the core systems that hold your business data and turns them into a unified view.
From Raw Data to Reusable Models
Megamind lets data teams define and maintain data models and feature layers that can be reused across analytics, machine learning and LLM platforms.
Define business-aligned data models using your own concepts and terminology.
Create feature sets that can be consumed by ML models and LLMs.
Use big data technologies to process large volumes efficiently.
Version your models and track how they evolve over time.
Built to Work with Spell
Megamind and Spell are designed to complement each other: Megamind prepares the data; Spell turns that data into private LLMs.
Megamind
Spell
Governed Data, Traceable Models
Megamind gives you control and transparency over how data flows, how it is transformed and how models are built.
Track data lineage from source systems to published models.
Role-based access control for pipelines, models and outputs.
Audit trails for changes to transformations and definitions.
Policies to manage sensitive data and restricted fields.
Built on Big Data Technologies
Megamind uses big data technologies to handle large volumes, high throughput and complex transformations.
Where Megamind Fits in Your Organization
Analytics and BI Teams
Provide analytics teams with consistent, governed data models instead of ad-hoc extracts.
Machine Learning and AI Teams
Give ML engineers and data scientists ready-to-use feature sets built from enterprise data.
LLM and Copilot Initiatives
Feed LLM platforms like Spell with structured, curated datasets instead of raw dumps.
High-Level Architecture
Data Sources
Data sources: operational systems, warehouses, lakes, logs and files.
Megamind Data Flow
Megamind data flow: ingestion, transformation, modeling and feature layers.
Outputs
Outputs: analytical data models, feature sets and curated datasets for platforms like Spell.
On-Premise by Design
Megamind runs inside your own infrastructure, alongside your existing data platforms.
In Active Development
Megamind is being developed with organizations that need a solid data foundation for analytics, ML and LLM projects.
Core Ingestion and Modeling
Connectors and pipelines to turn enterprise data into consistent models.
Feature Layers and Spell Integration
Feature engineering and first-class integration with Spell for LLM use cases.
Advanced Orchestration and Observability
Deeper scheduling, monitoring and optimization of data workloads.
Policy-Driven Governance
More automation around data policies, sensitivity and lifecycle.
Ready to Build a Data Foundation for Your AI?
If you want reliable analytics, ML and LLMs, you first need a strong data modeling layer. Megamind gives you that layer on-premise, on top of the data you already have.