Dependencies
Templates, playbooks, and handoffs AI can follow.
Keep the reusable parts of a workflow together so orchestration has better source material.
AI integrations
Give AI integrations real knowledge, context, and dependencies.
Sujour gives AI integrations the source layer they usually lack: human-maintained knowledge, live context, and reusable dependencies in real pages. Use it as an AI project knowledge base for retrieval-augmented generation (RAG), context-augmented generation (CAG), and DAG-based workflows.
AI project knowledge base
Retrieval-augmented generation
Context-augmented generation
DAG-ready dependencies
AI project knowledge base
Keep the source material AI projects actually depend on.
Most AI integrations break down because the knowledge behind them is fragmented, stale, or hard to trust. Sujour gives teams a human-first workspace for notes, docs, specs, research, playbooks, handoffs, and decisions — then keeps that material available as structured context.
- Keep pages, templates, and playbooks in one durable workspace.
- Preserve the headings, lists, and structure AI systems need to interpret meaning.
- Reduce the gap between how people document and how AI integrations consume context.
RAG and CAG
Ground RAG and CAG in live pages, not stale copies.
Sujour helps RAG and CAG workflows work from live documentation instead of disconnected copies. The same pages people update for specs, research, procedures, and handoffs become the context layer that retrieval and generation systems can use.
- Use structured pages as a higher-quality source for retrieval.
- Keep context visible so outputs stay tied to the underlying knowledge.
- Support summarization, rewriting, extraction, and follow-through without rebuilding context each time.
DAG-based workflows
Make project dependencies clearer for orchestration and routing.
Directed acyclic graph workflows depend on clear handoffs, structured steps, and reusable artifacts. Sujour helps teams keep that dependency context readable for people and dependable for systems.
Context
Live pages instead of stale copies.
Let AI integrations work from the same knowledge people maintain rather than drifting snapshots.
Human-first source layer
Better for people first, better for AI second.
Sujour starts as a usable knowledge workspace and naturally becomes the context runtime behind AI projects.
FAQ
Common questions about AI integrations in Sujour
How does Sujour help RAG workflows?
Sujour gives RAG workflows a human-maintained source layer with structured pages, templates, and playbooks that stay easier to retrieve from and easier to trust.
How does Sujour support CAG and DAG-based orchestration?
Sujour keeps live context, reusable dependencies, handoffs, and decision history in one workspace so CAG systems and DAG-based workflows can work from clearer project structure.
Request access
Tell us where Sujour fits in your AI stack.
Tell us whether you need a human-maintained knowledge base for RAG, CAG, DAG workflows, internal documentation, or AI project coordination.
Common starting points: AI project knowledge bases, RAG source layers, CAG context systems, DAG workflows, specs, research, handoffs, playbooks, and internal documentation.