Slack recently launched Real-Time Search (RTS) and the Slack MCP server.
We’ve integrated both directly into Nalvin. This gives Nalvin secure, real-time access to Slack conversations, within Slack’s existing permission model.
What Slack Real-Time Search actually is:
Slack Real-Time Search (RTS) is a new API that allows applications to query live Slack messages.
The Slack MCP server (Model Context Protocol) handles permission-aware retrieval, ensuring agents only access what they’re allowed to see.
In practical terms: Nalvin can now search Slack like a human would. Not exported data. Not summaries. Live conversations.
Nalvin as an official agent partner to Slack
Over the last couple of months, we’ve been part of Slack’s early partner group testing RTS and MCP. Slack launched the feature alongside partners like Cursor, Anthropic and Wordsmith.ai. Nalvin was included in that initial cohort. We integrated Slack RTS into Nalvin’s core workflows from day one. You can learn more here from Slack's official announcement:
Slack RTS in Nalvin
Most product context lives in Slack.
Customer feedback in Slack Connect.
Support escalations in threads.
Roadmap debates happening live.
Historically, that context had to be manually transferred into tickets or docs.
With Slack Real-Time Search, Nalvin can now:
Read Slack conversations as they happen
Detect relevant product signals
Link them directly to roadmap items or tickets
Use Slack as a permission-aware knowledge source
Slack is no longer a side-channel. It’s part of the system. Below are some selected examples of how Product Managers can reduce the amount of time they spend in Slack and help them make sense of the noise from channels, DMs and "quick pings".
Daily Digest grounded in Slack
Most product managers don’t start their day doing product work. They start by reconstructing context.
Slack. Email. Calendar. Linear. GitHub. Slack Connect. Customer threads. By the time you understand what actually changed, 30–45 minutes are gone.
With Slack Real-Time Search integrated into Nalvin, the Daily Digest is grounded in live Slack conversations, not just ticket updates.
Instead of only showing what moved in Jira or which PR was merged, Nalvin pulls in real signals from Slack:
customer feedback shared in Slack Connect
support issues discussed in threads
decisions made late in the day
internal debates that affect priorities
It then surfaces the relevant updates across Slack, Email, Calendar, Tickets and Code, along with suggested follow-ups.
You don’t start the day stitching information together. You start with a brief that reflects what actually happened.
Slack Connect insights without manual monitoring
If you rely on Slack Connect for customer communication, you already know the problem.
Feedback is scattered across channels. Some of it is highly actionable. Some of it is noise. Most of it depends on someone actively reading and extracting signal.
Before Slack Real-Time Search, capturing that feedback required manual tagging or copying context into tickets. It was process-heavy and inconsistent.
With RTS, Nalvin can read Slack Connect conversations as they happen and identify product-relevant signals automatically. When a customer shares a feature request or highlights friction, Nalvin can link that feedback to an existing roadmap item or cluster it with similar requests.
The result isn’t just automation. It’s coverage. You reduce the risk of missing important signals because no one happened to be watching that channel that day.
Slack Connect becomes a structured input into your product system rather than an informal side stream.
Using Slack as a real product knowledge source
Slack contains years of product history.
Why was a feature deprioritized?
Who pushed back on an integration?
What tradeoffs were discussed before launch?
Most of that context never makes it into the final ticket description or roadmap doc. It lives in threads.
With Slack Real-Time Search and the MCP server, Nalvin can retrieve relevant Slack conversations as part of its reasoning. When you ask about a roadmap item or a feature decision, Nalvin can reference the actual discussion that shaped it, within Slack’s permission model.
This changes the quality of answers. Instead of relying only on structured artifacts, Nalvin can ground responses in the conversations that led to those artifacts.
Slack stops being ephemeral chat history. It becomes part of the knowledge layer your product system is built on.
Slack Real-Time Search (RTS) and the Slack MCP server are now fully integrated into Nalvin. That means your AI agent can securely access live Slack conversations, monitor Slack Connect channels and use Slack as a knowledge source across tickets, docs and roadmap items.
Enable Slack RTS in Nalvin and see how context-aware product workflows actually work.