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First research run

End-to-end walkthrough from importing a client to reading your first findings and score.

This walkthrough takes you from a blank workspace to a completed research run with findings and a propensity score. It covers the golden path: the minimal steps to get value quickly.

Before you start

You need:

  • An offering configured in Settings > Offerings. If you do not have one yet, follow Offerings to create one.
  • At least one client to research. You can add one manually in this walkthrough.

Step 1: Add a client

  1. Go to Clients in the main navigation.
  2. Click Add client.
  3. Enter the company's legal name and domain (for example, acme-corp.com).
  4. Click Save.

The client now appears in your client list.

The clients list showing a newly added company row

Step 2: Start a research run

  1. Go to Research runs in the main navigation.
  2. Click New run.
  3. Select the offering you want to research against.
  4. In the client picker, find and select the client you just added.
  5. Click Start run.

The run starts immediately. You will see a status indicator showing progress through the research pipeline: web search, document extraction, finding synthesis, scoring.

The research run progress view showing pipeline steps and a status indicator

Step 3: Wait for completion

Research typically takes two to five minutes per client, depending on how much public information is available and which LLM tier is active.

You can leave this page and return. The run continues in the background. The run list shows current status for each run.

Step 4: Read the findings

Once the run completes:

  1. Click on the run in the run list.
  2. Select your client from the client list on the left.
  3. The findings panel shows all extracted findings, grouped by topic.

Each finding has a confidence indicator and a source reference. You can flag findings as incorrect or particularly important.

The findings inspector showing grouped findings with topic labels and confidence bars

Step 5: Check the propensity score

Below the findings, or in the summary panel at the top, you will see the propensity score, a number from 0 to 100.

The score comes from a rubric defined in your methodology. Higher scores mean stronger fit signals. The score panel also shows a breakdown by rubric category so you can see where the prospect is strong or weak.

Step 6: Read the report

The Report tab shows a structured narrative: an LLM-written synthesis of all findings into a prose document. It is useful for sharing with colleagues or as context before a call.

Step 7: Draft outreach (optional)

If your run is configured to generate outreach, click Outreach draft to see a personalised message anchored to the top findings. You can edit it before sending.

What is next