AI Alliance Develops Dana Language and Semiont Knowledge Base

The AI Alliance, formed in late 2023 to advance AI technologies, has introduced several groundbreaking projects, including Dana, an AI agent-native language and runtime, and Semiont, a knowledge base designed for human-agent collaboration. These initiatives were highlighted by Anthony Annunziata, AI Alliance Director of AI Open Innovation, during a presentation at The AI Conference in San Francisco on September 17.

Dana: Intent-Driven Development for AI Agents

Dana (Domain-Aware Neurosymbolic Agent) is a language and runtime that enables intent-driven development, allowing developers to describe their goals while the language handles the implementation. Key features of Dana include:

• Native support for agent workflows, memory grounding, and concurrency.
• Designed to run locally or in the cloud.
• Leverages large language models (LLMs) with symbolic grounding for deterministic outputs.
• Built around domain-specific knowledge from human expertise and industry workflows.

Dana was formally announced in late June and represents a significant step toward simplifying AI-powered programming.

Semiont: A Shared Knowledge Base for Humans and Agents

Semiont is an AI-native wiki that facilitates collaboration between humans and AI agents. It offers:

• High-accuracy context retrieval.
• Integration via Model Context Protocol (MCP).
• Locally owned knowledge bases deployable on demand.

Additional AI Alliance Projects

The alliance is also working on:

1. Open Trusted Data for AI Models and Agents:
   • A metadata specification for provenance, lineage, and utility.
   • A catalog of open datasets with trust scores.
   • Curation of new datasets for agentic AI use cases.
2. Deep Research Agent Architecture:
   • Explores challenges of building production-quality agents using MCP servers.
   • Plans to release a reference implementation.

Open Agent Lab and Alliance Goals