Open Arsenal

The Provenance Backbone for AI

OriginSeal is an open-source AGPL 3.0+ provenance infrastructure platform designed for AI-native systems where context is constantly transformed, shared, and generated by autonomous agents. It introduces a foundational layer for tracking origin, attribution, and identity across AI workflows built on MCP (Model Context Protocol), ensuring that intelligence systems remain transparent and accountable as they scale.

At its core, OriginSeal focuses on preserving the lineage of information as it moves through AI pipelines. Whether data is being summarized, embedded, rewritten, or used to generate new outputs, OriginSeal maintains a structured record of those transformations. This creates a verifiable chain of provenance that connects every output back to its source context, making it possible to audit and understand how results were produced.

The platform is built around MCP-native integration, allowing it to plug directly into agentic systems and tool ecosystems without requiring custom integrations for every application. Through its MCP layer, OriginSeal can intercept, enrich, and track context as it flows between models, tools, and external systems. This enables standardized provenance tracking across diverse AI environments.

OriginSeal also introduces a sovereign identity and attribution layer, where creators, systems, and agents can be associated with cryptographically verifiable identities. These identities persist across transformations, ensuring that attribution is not lost when content is processed or modified by AI. This is paired with a lineage graph engine that models relationships between inputs, outputs, and intermediate transformations as a directed acyclic graph.

Together, these features make OriginSeal a foundation for trustworthy AI systems. It is designed for use in agentic workflows, enterprise AI governance, research reproducibility, and any environment where understanding the origin and transformation of information is critical.