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Overview

AI Properties are custom research signals that the AI evaluates for each company in your pipeline. You define the question — “Has this company recently raised funding?”, “Is this company hiring for roles related to our product?” — and the system researches every target account to produce a structured, evidence-backed answer. AI Properties power multiple parts of the platform: they appear as signals on company pages, feed into prospecting task generation, and inform the AI agents when they reason about accounts.

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Property output types

Each AI Property has a configured output type that determines the format of the answer.
Output typeWhat it producesExample
Yes / NoA binary answer”Does this company use Kubernetes?” → Yes
DropdownOne value from a set you define”Primary industry vertical” → FinTech, HealthTech, DevTools, Other
ScoreA numeric rating on a 0–10 scale”How strong is this company’s product-market fit signal?” → 7
FreeformAn open-ended text answer”What is this company’s primary competitive differentiator?” → “AI-powered supply chain optimization…”
All output types include a 1–3 sentence description explaining the answer and up to 3 citations linking to the evidence sources.

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How to create an AI Property

  1. Navigate to the AI Agent Builder page.
  2. Click Add Property.
  3. Fill in:
    • Name — A clear label (e.g., “Recent Funding Round”).
    • Instructions — Tell the AI what to research and how to evaluate the answer. Be specific — the more detail you provide, the more accurate the output.
    • Output type — Select Yes/No, Dropdown, Score, or Freeform.
    • For Dropdown: Add at least 2 options for the AI to choose from.
    • Refresh Every (days) — Enter the number of days before the answer is re-evaluated (e.g., 7). Leave blank for no expiration.
    • For Score: Optionally set the scale description to guide how the AI assigns ratings.
  4. Click Save.

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Writing effective instructions

The instructions field drives the quality of research output. Include:
  • What to look for — “Check the company’s careers page, recent press releases, and LinkedIn job postings for roles mentioning Kubernetes, Docker, or container orchestration.”
  • How to evaluate — “Answer Yes only if there is direct evidence of production usage, not just job postings mentioning the technology.”
  • Edge cases — “If the company is a consultancy that implements the technology for clients but does not use it internally, answer No.”
Vague instructions produce vague answers. “Is this company a good fit?” gives the AI nothing to work with. “Does this company have an engineering team of 50+ that builds cloud-native applications on AWS or GCP?” gives it a concrete research target.

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How research works

When the AI researches a property for a company, it:
  1. Gathers available data about the company (CRM records, website, public sources).
  2. Searches the web for relevant evidence.
  3. Evaluates the evidence against your instructions.
  4. Produces a structured answer with the output value, a description explaining the reasoning, and citations linking to sources.
Research results are stored per company and refreshed based on the property’s refresh policy.

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Refresh interval

Each property has a Refresh Every (days) setting that controls how often answers are re-evaluated. Enter the number of days between re-research cycles (e.g., 1 for daily, 7 for weekly, 30 for monthly). Leave blank for no automatic expiration. When a property’s answer is still within its refresh interval, re-research is skipped to avoid unnecessary work. Use shorter intervals for fast-changing signals (e.g., hiring activity) and longer intervals for stable attributes (e.g., technology stack).

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Auto AI Research

Auto AI Research runs your property research automatically across companies in your target sales views on a recurring schedule.

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How to enable

  1. Open the AI Agent Builder and select a property.
  2. In the property editor, find the Auto Research section.
  3. Toggle Enable Auto Research.
  4. Set the Refresh Every (days) interval to control how often answers are re-evaluated.
  5. Select one or more sales views to target. The AI researches companies that appear in these views.
  6. Click Save.

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How it runs

When auto research is enabled:
  • The system evaluates all companies in the selected sales views.
  • Companies whose existing answer has exceeded its refresh interval are re-researched.
  • Companies with fresh answers are skipped.
  • Results are stored with updated evidence and citations.

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Monitoring progress

After triggering a research run (or when the scheduled run starts):
  • The property editor shows a progress indicator with the number of companies processed out of the total.
  • You can check the status at any time — it updates automatically.
  • If a run is taking too long or you need to stop it, click Cancel Research to halt the current run.

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Manual trigger

You can trigger a research run on demand without waiting for the next scheduled cycle:
  1. Open the property in the AI Agent Builder.
  2. Click Run Research Now.
  3. Monitor progress in the status indicator.

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Value distribution

After research has run across companies, you can view the distribution of answers to understand how your target accounts break down. The distribution view shows:
  • Yes/No properties — Count and percentage of Yes vs. No answers.
  • Dropdown properties — Breakdown by each option.
  • Score properties — Distribution across the 0–10 scale.
  • Freeform properties — Summary of the most common themes.
Use distributions to validate that your property is producing useful signal. If 95% of companies answer “Yes,” the property may not be discriminating enough to be useful for prioritization.

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Where AI Properties appear

LocationHow they’re used
Company Signals tabEach property appears as a signal card with the answer, description, and citations
Signal SummaryProperties feed into the AI-generated Fit, Timing, and Context scores
Prospecting configurationProperties can be selected as research signals in the Signals tab
Task generationThe AI references property answers when deciding what tasks to create and how to prioritize
Company Agent chatThe agent has access to property answers when responding to questions about a company

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Constraints

  • AI Properties are scoped to companies — they research company-level signals, not deal-level or contact-level.
  • Auto research processes companies in batches. Large sales views may take time to complete.
  • Each research operation consumes agent credits. See Agent Credits for details.

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FAQ

A few seconds per company. For large sales views with hundreds of companies, a full research run may take several minutes.
Yes. Editing instructions or output type creates a new version of the property. Existing answers are preserved until the next research cycle refreshes them.
Previous answers are kept as-is. New research produces answers in the updated format. The next auto research cycle or manual trigger re-evaluates all companies with the new output type.
Companies are skipped when their existing answer is still within its refresh interval. If you need to force a full re-evaluation, use the manual trigger with the resync option.
Yes. Properties are researched individually when company context is generated (either manually or by the overnight worker). Auto research is optional — it pre-computes answers across your sales views so they are ready before anyone visits the company page.
Check the value distribution after a research run. If answers cluster heavily on one value (e.g., 90%+ “Yes”), the question may be too broad. If descriptions are vague or citations are irrelevant, the instructions need more specificity.