Doso — Concept Overview
Doso combines a workflow graph for execution with a knowledge graph for durable context. The two graphs solve different problems and meet through typed contracts, provenance, and review.
What you build remains yours:
- Knowledge and workflow graphs persist without vendor lock-in.
- Connections use your Composio account, your own integrations, or a paired desktop runtime that runs host CLIs.
- The runtime can host locally, on your server, or in any cloud and country.
- Inference uses any provider and any model you configure.
Two kinds of graph (keep them distinct)#
| Workflow graph (orchestration) | Knowledge graph (memory) | |
|---|---|---|
| Nodes | Agent jobs with contracts | Entities (people, orgs, places, events, artifacts, …) |
| Edges | Data dependencies / control flow | Typed predicates (S–P–O triples) with provenance |
| Purpose | Fan out work, verify, merge | Persist facts beyond a context window; multi-hop answers |
They compose: the workflow graph is how agents run; the knowledge graph is the durable substrate they read/write and fact-check against.
Glossary#
- Node (workflow): one bounded job — one agent, explicit input, schema-validated output.
- Edge (workflow): a real dependency; data must cross. “And then” without data is a fake edge.
- Contract: input shape + output schema + single responsibility; what makes a node wireable.
- Diamond: fan out → reduce (code) → synthesize (judgment) — the default serious topology.
- Verifier / checker: edge-gated node that tries to kill a finding before it reaches the answer.
- Anchor: non-negotiable ground truth (tests passed, real outcomes) — topology without anchors is self-deception.
- Entity / triple: knowledge-graph node and typed relation; descriptions aid resolution.
- Resolution: clustering surface forms into a canonical entity (description-aware, not string-similarity alone).
- Provenance: which document/chunk produced a node or edge — required for cited answers.
How the concepts fit together#
- The knowledge pipeline extracts, resolves, and assembles durable facts with provenance.
- Agentic memory gives workers and verifiers a shared substrate that survives individual sessions.
- The workflow graph coordinates bounded jobs, parallel branches, joins, and approval gates.
- Ontology and grooming turn the underlying graph into useful product views without creating a second source of truth.
- The architecture keeps these concerns separate while exposing them through one product.