If you are evaluating Dashworks, you want one place to ask questions across your company’s apps. Suda targets the same pain from a different angle. Dashworks is an assistant people chat with. Suda is a company brain for your team and enterprise that your own AI agents query directly. Here is the honest difference.

What Dashworks is good at

Dashworks connects your apps and gives employees a single chat box to ask across them, in Slack or the web. If the job is “let people ask one assistant instead of searching five tools,” it does that and it is a capable product.

Where the two diverge

The divergence is who does the asking and what sits underneath.

Dashworks is a retrieval assistant for people: it searches connected apps and generates an answer over the results.
Suda builds a context graph and exposes it over MCP, so the AI agents already running in your stack query the graph directly. The model underneath is connected facts with a current version, not a ranked search.

That difference shows up when an agent, not a person, needs context:

	Dashworks (AI assistant)	Suda (company brain)
Built primarily for	People chatting	AI agents querying
Underlying model	Search and generate	Graph of connected facts
Stale and conflicting facts	Surfaced in results	Retired and resolved automatically
How agents connect	Assistant and API	Native over MCP
Context sent to a model	Retrieved passages	Only what is needed (~85% less)
Scope	Team Q&A	Company brain and personal brain

When to pick which

Pick Dashworks if you mainly want a company-wide chat assistant for employees.
Pick Suda if you want a company brain that feeds correct, current context to the AI agents in your own stack over MCP, with permissioned access.

Trying Suda

Suda connects to more than 700 sources, including Notion, Slack, and Linear, builds the graph, keeps it current, and serves it to any agent over MCP. Setup is one command:

npx suda connect

For the architecture, read context graph vs RAG. For the concept, read what is a company brain.