Description
Agience is an operating system for AI workflows, addressing the critical need for trust and reliability in AI-generated outputs. As AI adoption grows, organizations struggle to trace, validate, and approve what their systems produce. Agience provides the infrastructure to transform AI output into something organizations can build on.
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Agience works by structuring messy inputs, establishing identity, and tracking provenance. It creates a durable, versioned knowledge layer that is shareable by design. This allows teams, agents, and external consumers to access the same data with built-in identity, permissions, and versioning. The platform offers a four-stage process: ingest, curate, validate, and search. This process ensures that knowledge is trusted and reusable across an organization.
Key capabilities include structuring inputs into typed, addressable artifacts with stable identities, tracking the full transformation chain from raw input to published output, and providing a durable data layer. Agience is designed for a wide range of users, from solo developers to large enterprises. It supports various integrations and offers a free tier, making it accessible to different use cases. The platform is also open-source (AGPL-3.0) and self-hostable, providing flexibility and control over data.
Agience's value proposition lies in its ability to turn AI output into something an organization can build on. By providing identity, provenance, and a durable knowledge layer, Agience enables teams to trust and reuse AI-generated information. This is particularly important for regulated industries and organizations requiring audit-ready deployments. With its focus on governance built into the data model, Agience simplifies the process of scaling AI adoption while maintaining trust and reliability.
- CategoryAutomation & Agents
- Pricing ModelFreemium
- DeploymentSelf-Hosted
- PlatformsWeb
Agience: AI Workflow OS's Core Features
Structures messy inputs into typed artifacts
Establishes identity for every artifact
Tracks provenance from input to output
Provides a durable, versioned data layer
OAuth2-backed authentication and authorization
Offers a full audit trail
Supports custom content types and extraction agents
MCP-native for easy integration
Hybrid semantic + keyword search
Self-hostable on your infrastructure
Built-in version history and lineage
Authority-certified provenance
Granular access control and audit trails
How to use Agience: AI Workflow OS?
Choose your deployment: hosted cloud or self-hosted.
Ingest data from various sources (meetings, documents, streams).
Define artifact schemas and connect extraction agents.
Review and validate the knowledge entered into the system.
Search and query the trusted knowledge base.
Connect any MCP server to publish APIs, data, or resources.
Focus on domain logic, not infrastructure plumbing.
Utilize the platform tools out of the box.
Agience: AI Workflow OS's Use Cases
- Meeting Intelligence
- Incident Reconstruction
- Compliance & Audit
- Research Synthesis
- Architecture Decisions
- Knowledge Management
- AI Agent Coordination
