Наталя Хандусенко AI Eng 26 August 2026, 14:33

How to stop the "death of context" in Slack: IT Project Manager created SignalOps

Slack has long since become a place where important decisions are made in three or four messages and instantly hidden under the next thousand chats. IT Project Manager Sergey Skrynnikov developed a tool called SignalOps that automatically reads team conversations, combines them with work trackers, and extracts real blockers, risks, and promises. Thanks to this, you can get a complete picture of what is actually happening in projects, saving dozens of hours of rereading channels and searching for lost context.

What problem does SignalOps solve?

The main goal of SignalOps is to return control to team communication without additional bureaucratic burden on people.

The typical workflow has a critical weakness: blockers, agreements, customer complaints, and risks are discussed once and then forgotten. The same issue comes up every few weeks, and no one mentions the casually mentioned risk until it turns into an incident.

Attempts to solve this manually (emojis, custom tags, or /decide) stop at the first peak load. Unlike standard tools, SignalOps doesn’t require any additional action from the team — it works with what people have already written.

How the tool works

SignalOps is based on creating a single database from two types of sources: communication platforms and task trackers.

The tool integrates discussions from Slack, Teams, or Discord with tasks in Jira, Linear, Asana, or ClickUp. If a solution is discussed in a thread, it is automatically linked to the corresponding task;
the same issue raised in chat and logged in Jira is rolled up into a single alert. Alerts from different channels are correlated to provide a holistic view;
The algorithm transforms chaotic messages into structured records. The system generates four separate types of reports, each of which calculates its own dimension: from company and counterparties to threats and specific work units;
the system generates a visual map that shows what exactly caused the problem and what processes it blocks further;
Each recommendation is rigidly tied to specific messages or tasks, which allows you to check the grounds without personally rereading the entire story.

Unlike many solutions (e.g. Slack AI), SignalOps is not limited to a single platform, but sees the full context, combining conversation and workflow into a single analytics layer.

How it works for the user: 3 simple steps

Connecting sources: the user selects the necessary channels in the messenger and projects in the task tracker (setup takes up to two minutes).
Background analysis: the system runs on a schedule (daily, weekly, or on demand) without a bot on calls and without tagging.
Inbox processing: instead of an endless stream of messages, the manager opens a convenient inbox where signals are already filtered by types, statuses, and performers.

What stage is the project at now?

SignalOps is currently in open beta. The tool was created with the help of Claude Code and has already been successfully tested by Serhiy on his own team.

To test the effectiveness on other teams with different processes, Sergey Skrynnikov opened free access to the beta version.

Terms of participation: Access is completely free for the entire beta testing period. Teams that help test and refine the tool will retain free access after the official launch.
Support: the developer personally helps with the connection and guarantees a joint analysis of the first generated report.

You can test the tool using the link or by writing to Sergey Skrynnikov in a private message to connect.