A Google Agentspace alternative that is not tied to one cloud
Agentspace is Google's enterprise search and agent layer. Suda is a company brain any AI agent queries over MCP, on any stack. Here is the difference.
If you are evaluating Google Agentspace (part of Gemini Enterprise), you want search and agents over your company’s knowledge. Suda solves the same problem without tying you to one cloud or model. Agentspace is Google’s enterprise search and agent layer. Suda is a company brain for your team and enterprise that any AI agent queries over MCP. Here is the honest difference.
What Google Agentspace is good at
Agentspace brings Gemini-powered search, prebuilt and custom agents, and connectors to enterprise data, tightly integrated with Google Cloud. If your company is committed to Google and Gemini, that integration is real leverage.
Where the two diverge
The divergence is coupling and reach.
- Agentspace is centered on Google Cloud and Gemini. It is strongest when your data and models live in that ecosystem.
- Suda is model-agnostic and cloud-agnostic. It builds a context graph across your tools and exposes it over MCP, so any agent, Gemini, Claude, GPT, or your own, reads the same current context.
That difference shows up in a mixed or multi-model stack:
| Google Agentspace | Suda (company brain) | |
|---|---|---|
| Ecosystem | Google Cloud + Gemini | Any cloud, any model |
| Built primarily for | Search + agents in Google’s stack | Any AI agent over MCP |
| Underlying model | Enterprise search + agents | Graph of connected facts |
| Stale and conflicting facts | Handled in-product | Retired and resolved automatically |
| How agents connect | Google ecosystem | Native over MCP, model-agnostic |
| Context sent to a model | Retrieved passages | Only what is needed (~85% less) |
When to pick which
- Pick Agentspace if you are all-in on Google Cloud and Gemini and want search and agents inside that ecosystem.
- Pick Suda if you want a company brain that any model or agent can query over MCP, without committing to a single cloud, 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 connectRead enterprise context for AI agents or the Glean alternative.