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A data signal is one claim, pulled verbatim out of something a customer or a system said. A line from a Slack thread. A sentence in an app store review. A complaint in a sales call. Everything above it (clusters, insights, briefs) traces back to a set of signals.
Data signalsData signals
For what happens to a signal after it lands, see The evidence pipeline.

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What a signal carries

Every signal has an SI- reference (SI-482) and these fields:

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Where signals come from

Signals come from three places.

Integrations

The providers you can connect today are Slack, GitHub, Linear, Jira, Notion, PostHog, Gong, and Fellow, plus four review sources (App Store, Google Play, Google Reviews, and Trustpilot).

Agents

An agent pointed at a URL reads the page on its schedule and writes signals from what changed. A research run produces them too, at a lower weight.

Documents

Files you upload and knowledge documents in the workspace get read for signals the same way an integration payload does.
If a tool is not on the Integrations page, nothing from it reaches your workspace.

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How a signal gets weighted

How much a signal counts depends on what kind of source produced it and how deliberately it was captured.
An integration signal is 1.0, the baseline everything else is discounted against.
Something a product owner captured on purpose counts double. An agent’s unprompted find counts least.
The two multiply together with the signal’s own strength. That combined weight decides how much the signal pulls its cluster’s centre of gravity and how much it contributes to an insight’s score. Strength also decays with age, so a complaint from two years ago pulls less than the same complaint from last week. One thing a customer told you in a call, captured by you, outweighs a dozen passively scraped mentions.

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The Data Signals list

Open Insights in the sidebar and pick the Data Signals tab. One row per signal, showing the SI- reference and summary, the source badge, whether it belongs to a cluster, its sentiment, and the capture date. Search with Search data signals or SI-… to match on text or reference. The filter toolbar narrows by Source, Cluster (has one or does not), Sentiment, Date, Type, and Strength. Strength offers presets at 0.2, 0.4, 0.6, and 0.8, and filters at or above the value you pick. Sorting and filters are held in the URL, so a filtered view can be bookmarked or pasted to a colleague. Right-click any row for Open, Copy ID, Copy URL, Copy content as JSON, and Delete. Click the row to open the signal.

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Inside a signal

The detail page leads with the summary as its heading and the verbatim quote below it, so you read the customer’s words before Squad’s version of them. When the source has a link, the quote card carries it. Cluster. The theme this signal was grouped into, with the cluster’s type and member count. Click through to see the rest of the group. Related data signals. Other signals close to this one. The first three show as quote cards. If there are more, View all opens the full table. Info. Source, sentiment, type, strength, and capture date, in the right-hand panel. Insights. The insights this signal helped produce. A signal that landed recently, or one in a cluster too small to synthesise, shows nothing here yet. Referenced by. Any brief or knowledge document whose body cites this signal.

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Cookbook

Check whether a complaint is isolated or a pattern. Open the signal, look at the Cluster card. A cluster with 2 members and a Pending label means Squad hasn’t seen enough of this yet. A cluster with 30 members and a confident theme label means it’s a pattern, and the Insights panel tells you whether it’s already been written up. Audit what a source is actually producing. On the Data Signals tab, filter Source to one provider and sort by Date. A connected tool producing nothing, or producing noise, shows up straight away. Fix it from Integrations. Find your strongest recent evidence. Filter Strength to the 0.6 preset and Date to the last month, then sort by strength descending. That’s the evidence worth quoting in a review.