OASIS Open-Source Ecosystem

A practical open-source ecosystem for teams building, governing, evaluating and scaling enterprise AI.

The OASIS Open-Source Ecosystem brings together 10 repositories covering key areas of enterprise AI — from opportunity discovery and engineering to data, human-AI workflows, evaluation, responsible AI, operations, economics and model architecture.

Explore the Ecosystem

OASIS

Enterprise AI transformation methodology
Outcome-as-a-Service using Intelligence Systems — a structured methodology for taking enterprise AI from idea to scale.

Nexus

AI opportunity and use-case discovery
An opportunity catalogue to help teams explore where AI and agentic systems can create value across business domains and functions.

AEGIS

Agentic engineering across the SDLC
Guidance for applying intelligence and agents across software engineering — from requirements and design through development, testing and delivery.

Forge

Data and knowledge engineering for grounded AI
Retrieval architectures, embeddings, grounding, enterprise knowledge and the data foundations required by AI systems.

Loom

Human-AI workflow and experience engineering
Progressive autonomy, escalation, human oversight and workflow design for systems where people and AI work together.

Verity

Evaluation and reliability engineering
A structured approach to evaluating AI and agentic systems, including multi-dimensional evaluation, statistical rigor and failure analysis.

Compass

Responsible AI, security, governance and assurance
Practical guidance for managing AI risk, security, governance, responsible AI and regulatory considerations across jurisdictions.

Helm

AgentOps and LLMOps for live operations
Deployment, observability, release management, runtime operations, incident response, resilience and security containment for production AI systems.

Fulcrum

AI FinOps, cost and value economics
Guidance for understanding the cost, value, efficiency and sustainability of AI systems as they move from experimentation to scale.

Axiom

AI model architecture reference
A structured field guide to modern AI model architectures including Transformers, Mixture-of-Experts, State Space Models and related architecture families.

Multiple Entry Points

The ecosystem is designed so that teams can start wherever their immediate need is strongest.

Business teams can begin with Nexus.
Transformation teams can start with OASIS.
Engineering teams can explore AEGIS, Forge and Loom.
Evaluation teams can use Verity.
Governance, risk and Responsible AI teams can begin with Compass.
Production teams can use Helm.
FinOps and value teams can explore Fulcrum.
Teams wanting to understand the underlying model landscape can use Axiom.

Each repository can be used independently. Together, they provide a broader open-source engineering ecosystem for enterprise AI.

Explore the Repositories

OASIS | Nexus | AEGIS | Forge | Loom | Verity | Compass | Helm | Fulcrum | Axiom

Explore the KnowledgeTrailsAI open-source ecosystem on GitHub →

For the detailed mapping between OASIS and its companion repositories, see the Companion Repository Index .