Architecture
How we think about the context layer, the knowledge graph, and how Neither fits into your stack.
The problem
Decisions and commitments are scattered across email, chat, docs, and meetings. AI assistants have no durable organizational memory — every session starts from scratch. Neither targets the missing context layer: structured, persistent intelligence humans and agents can query.
Conceptual layers
Surfaces (Chat, Inbox, and other UI) sit above a context layer: a knowledge graph with projects, people, decisions, dependencies, and evidence. Agent runtimes and integrations can consume that context through authenticated APIs — so Neither stays the system of record for organizational intelligence.
Knowledge graph
Ingestion and structuring turn raw content into entities and relationships that improve over time — with provenance back to sources. This is not keyword search alone; it is structural understanding that powers answers and prioritization.