A Sana AI alternative built as a company brain for agents
Sana is an AI assistant and agent platform for people. Suda is a company brain your own agents query over MCP. Here is the difference and when each fits.
If you are looking at Sana AI, you want one intelligent surface over your company’s knowledge. Suda targets the same pain from a different angle. Sana is an assistant and agent platform people use. Suda is a company brain for your team and enterprise that your own AI agents query directly. Here is the honest difference.
What Sana AI is good at
Sana connects your tools and gives employees a polished assistant, plus a platform to build agents and learning content on top. If the job is “give our people a smart assistant and a place to build workflows,” it is a capable, well-designed product.
Where the two diverge
The divergence is who owns the intelligence layer and what sits underneath.
- Sana is a destination: people go to Sana to ask, and agents are built inside Sana’s platform.
- Suda is infrastructure: it builds a context graph and exposes it over MCP, so the AI agents already running anywhere in your stack query the graph directly. The model underneath is connected facts with a current version, not an assistant you visit.
That difference shows up when the agent is not inside one vendor’s platform:
| Sana AI | Suda (company brain) | |
|---|---|---|
| Shape | Assistant + agent platform | Context infrastructure |
| Built primarily for | People, and agents built in Sana | Any AI agent, anywhere in your stack |
| Underlying model | Assistant over connected apps | Graph of connected facts |
| Stale and conflicting facts | Handled in-product | Retired and resolved automatically |
| How agents connect | Sana’s platform | Native over MCP, model-agnostic |
| Context sent to a model | Retrieved content | Only what is needed (~85% less) |
When to pick which
- Pick Sana if you want a finished assistant and a platform to build agents and learning in one place.
- Pick Suda if you want a company brain that feeds correct, current context to the agents in your own stack over MCP, with permissioned access, whatever built them.
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 connectRead what is a company brain or enterprise context for AI agents.