SuperML Ecosystem

Products

Six open source products built to help developers learn ML, ship AI-assisted software, analyze data, query databases in plain English, search governed enterprise knowledge, and remediate vulnerabilities autonomously. Free and open source.

Machine Learning

SuperML Java

A complete, free Java machine learning framework for enterprise developers. Train models, make predictions, and build ML pipelines with intuitive Java APIs.

  • Native Java API with object-oriented design patterns
  • 30+ algorithms: regression, classification, clustering, neural networks
  • Thread-safe, production-ready for enterprise applications
  • MIT licensed — free to use with attribution
Explore Framework GitHub
AI Development

Smart SDLC

A skills framework that gives GitHub Copilot, Claude, Cursor, and any AI assistant structured expertise across the full software development lifecycle — no runtime required.

  • 30+ skills · 6 AI personas (Product, Architect, Developer & more)
  • Native integrations: JIRA, Confluence, GitHub, GitLab, Azure DevOps
  • Works with any AI assistant — zero dependencies, zero config
  • MIT licensed — one npx command to get started
Explore Smart SDLC GitHub
AI Analytics

DataTruth

AI-native analytics platform that lets anyone query databases in plain English, visualize insights instantly, and enforce data quality — no SQL knowledge required.

  • Natural language queries — no SQL, no training needed
  • Auto-generated charts, dashboards & PDF/Excel exports
  • Connects to PostgreSQL, MySQL, Snowflake & BigQuery
  • Enterprise RBAC, audit trail & SOC 2 ready — MIT licensed
Documentation GitHub
AI Agents

NL-2-SQL Agents

Multi-agent AI system that translates plain-English questions into accurate SQL queries — with schema discovery, autonomous refinement, and full explainability.

  • Agentic query generation & autonomous refinement loop
  • Supports PostgreSQL, MySQL, SQLite, Snowflake & BigQuery
  • LLM agnostic — works with OpenAI, Anthropic & local models
  • Embeddable REST API + Python & Java SDKs — MIT licensed
Learn More GitHub
Enterprise RAG

Attribute Knowledge RAG

A reference architecture that turns enterprise attribute metadata into an AI-searchable knowledge layer — translating natural language into governed attributes, never hallucinated fields.

  • Indexes governed attributes, not documents — every output is a real, approved field
  • Hybrid BM25 + kNN retrieval with Reciprocal Rank Fusion per attribute phrase
  • Pluggable LLM, embedding & search providers — Claude, OpenAI, Bedrock, OpenSearch, FAISS, Chroma
  • Domain-agnostic pattern for healthcare, banking, insurance & retail — Apache 2.0 licensed
View on GitHub Architecture
AI Security

VAR

Vulnerabilities Autonomously Remediated — a multi-agent platform that analyzes, plans, patches, validates, and raises pull requests for security vulnerabilities across your repositories.

  • Fully automated pipeline: analyze → plan → patch → build → validate → PR
  • LLM-powered remediation planning with Claude, or any OpenAI-compatible endpoint
  • Neo4j dependency blast-radius analysis with a human-approval gate before merge
  • Multi-scanner (Snyk, Trivy) & multi-SCM (GitHub, Bitbucket) — MIT licensed
View on GitHub Quick Start

All free. All open source.

Every project is free and open source (MIT or Apache 2.0). Star us on GitHub and join the community.

View on GitHub
Explore Tutorials