for Slack

Daimon for Slack

Your Slack workspace just hired a data scientist.

Ask where work already happens. Daimon reads the thread, measures the pattern, fits the PyMC model, and brings the evidence back to your team.

Add to SlackComing soonSee the work

Launching soon · try it today in our Discord

DaimonDaimon#support-ops

Which support themes are increasing week over week?

01 · ask where the work is

One question goes in.
Evidence comes back.

#support-opsIllustrative Slack analysis
  1. N

    Nina 09:41

    Which support themes are increasing week over week?

  2. DaimonDaimon

    Daimon 09:43

    I grouped eight weeks of support threads, checked the trend by theme, and kept uncertainty in the comparison.

    2.4×growth in onboarding questions
    Weekly support threads by theme, eight-week trend

02 · inspect every step

It doesn't hide behind an answer.

Every result leaves behind code, assumptions, a chart, and a notebook your team can run again.

analysis.pyrunnable notebook
In [1]threads = slack.history('#support-ops', weeks=8)
In [2]themes = classify_and_validate(threads)
In [3]trend = pm.fit(themes, varying_intercepts=True)
Out [3]2.4×

growth in onboarding questions, with uncertainty carried through the estimate.

03 · the useful parts

Built for workspaces that need more than chat.

  1. 01

    Works in the thread

    Turn an operational question into analysis without moving the team to another tool.

  2. 02

    Connects the evidence

    Ground work in Slack history and the live sources attached to your agent.

  3. 03

    Quantifies uncertainty

    Compare trends with Bayesian estimates, intervals, and assumptions intact.

  4. 04

    Leaves an artifact

    Return a chart and runnable notebook that the team can inspect and reuse.

The offer

One click.
Then ask the real question.

Launching soon: no API key, no setup, $5 of Anthropic credit on us.

Add to SlackComing soon
DaimonDaimon

Built by PyMC Labs

Warm welcome.
Serious machinery.

  • Hosted by PyMC Labs. No API key or local setup.
  • One tenant per workspace; its data stays scoped to it.
  • $5 of Anthropic credit on us, with every feature unlocked.

Put Daimon in your workspace.

The next question can become a model, a chart, and a notebook.

Add to SlackComing soonOr explore Daimon first