Penumbra provides a platform that converts a company’s knowledge, workflows, rules, and expert judgment into structured domain context for AI systems. By letting teams describe business objects and processes in plain language, the platform supplies AI with clear, owned context that improves tool performance, memory, extraction, and provenance, starting with a single workflow and scaling to a company‑wide knowledge base.
Funding
Funding not disclosed
Founders
Product
Problem
Organizations deploying AI often struggle because the necessary business context—objects, rules, workflows, and expert judgments—is scattered across documents, dashboards, and people. Without a unified, structured domain model, AI tools miss critical information, leading to inaccurate outputs, poor memory, and unreliable extraction or provenance.
Solution
Penumbra provides a platform that lets teams describe their business entities, standards, and processes in plain language and automatically converts that input into a structured domain model. The resulting knowledge graph supplies the missing context for AI systems, enabling more reliable memory, extraction, review, and provenance capabilities. Users can start by modeling a single workflow where AI performance is lacking, then incrementally expand the model to cover the entire organization. The platform delivers the contextual data needed for AI tools, APIs, and agents to operate consistently across all surfaces. By centralizing domain knowledge, Penumbra reduces the need for AI to rediscover business rules from fragmented sources.
Target Audience
Penumbra is aimed at service firms formalizing expert methods, enterprise AI teams needing coherent business context, platform builders requiring typed domain models for agents, and founders building a company‑wide knowledge brain.
Features
- Plain-language authoring interface for defining objects, rules, workflows, and standards without requiring technical schemas
- Automated transformation of authored definitions into a typed knowledge graph that can be queried by AI services
- Incremental onboarding workflow that starts with a single use case and scales to a company‑wide domain model
- Integration hooks for AI memory stores, extraction pipelines, review tools, and provenance tracking systems
- API layer that exposes the structured domain context to internal agents, external platforms, and custom applications
- Built‑in validation and governance to ensure the domain model remains accurate and aligned with expert judgment