Open Data and Models
Data is the heart of AI. And models are the heart of the intelligence of an AI system. The AI Alliance includes most of the companies and research labs that have built and released open models. The AI Alliance is focused on studying, tuning, adapting and applying open models and releasing them to advance open science and research and ensure they are useful to many people and organizations.
Open Trusted Data Initiative (OTDI)
A catalog of open datasets scored by trust, built on a metadata specification for data provenance, lineage, and utility. AI systems are only trustworthy if the data is trustworthy.
SYNTH
Open standards and tooling for synthetic data generation, helping the community build datasets that respect provenance and licensing.
Semikong
A fully open foundation model for the semiconductor industry — the template for domain-specific open models that compete with proprietary alternatives.
GEO-Bench
An open benchmark suite for evaluating geospatial foundation models, supporting open research at the intersection of AI and Earth observation.
The Open Agent Hub
The Open Agent Hub is a collaborative community of open source AI projects and domain-specific work groups that seek to make AI Agents successful in the real world through fast experimentation and distillation of learning into usable reference architectures and implementations, and build out of new tools to enable development and deployment.
Dana Agent Framework
An open framework for building reliable, domain-aware agents that connect language models to real-world tools and workflows.
Open Agent Hub
A community hub of open source blueprints, evaluation frameworks, and domain-specific architectures for production AI agents. Agents fail at "demo to deployment" — domain-specific architecture fills the gap.
Semiont
Reusable functions, UI tools, and frameworks for building, managing, and enriching sophisticated open source AI agents and applications.
Safety and Governance
AI Alliance's safety, governance, and advocacy work builds public trust in open AI through evaluation, benchmarking, and red-teaming, alongside advocacy for healthy, sustainable, and open regulatory environments and technical standards across the industry.
Achieving Confidence in Enterprise AI Applications
Creates reusable techniques and examples for deterministic and generative AI evaluation, helping enterprises ensure deployed AI meets safety and requirements standards.
