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AI Agents bring intelligence to your workflows, generating personalised content on the spot so your team can move faster without losing the human touch.

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Why use AI Agents?

Most sales and CS teams spend too much time on things like writing follow-up emails, pulling together business cases, or summarising call takeaways. AI Agents handle these steps for you — based on what actually happened, every time. That means you can:
  • Send better, more personalised follow-ups faster
  • Keep deals moving even when you’re back-to-back
  • Give your CS team rich context without manually writing it up
  • Scale your process without making it feel templated

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What can AI Agents do?

Drop an AI Agent anywhere in your workflow before an action. It reads the situation and generates something ready to use. Examples:
  • Write a personalised follow-up email based on form responses or room activity
  • Generate a business case from your call transcript
  • Summarise a kickoff form and share the highlights with your CS team
  • Notify your team with enriched contact info and engagement insights
  • Personalise a proposal or mutual action plan using CRM data
You can review and approve any AI-generated content before it goes out by routing the workflow through your Smart Queue.

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Real examples

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Example 1: Form submitted → Summary sent to team

  • Trigger: Kickoff form submitted
  • AI Agent: Summarise the key answers
  • Action: Email or Slack the summary to your CS team

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Example 2: Room not viewed → Nudge email

  1. Trigger: Room not opened after 3 days
  2. AI Agent: Write a friendly follow-up with key next steps
  3. Action: Send the email from the rep’s work address, personalised with the contact’s name and room link

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Example 3: Call transcript → Business case

  1. Trigger: Gong call recording processed
  2. AI Agent: Generate a business case from the key discussion points
  3. Action: Add it to the room and notify the deal owner

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Writing a good prompt

The better your instructions, the better the output. A strong prompt includes five things:
  1. Role — Who should the AI write as?
  2. Task — What should it produce?
  3. Context — What information should it use? (Use variables to pull in real data)
  4. Constraints — How long? What tone? What format?
  5. Example — What does a good result look like?
Example prompt: 
You are a sales rep at {{organization_name}}.

Write a brief follow-up email to {{primary_contact_first_name}} at
{{target_company_name}}. The room was shared 3 days ago but hasn't
been viewed yet.

Keep it friendly, under 100 words, and include a soft call-to-action
to check out the room.

Sign off as {{room_creator_full_name}}.
Include a short example of the output you want in your prompt — a concrete example produces better results than a long description alone.

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Best practices

  1. Be specific — Vague instructions produce vague results
  2. Add context — More relevant data leads to better personalisation
  3. Set constraints — Always specify the length, tone, and format you want
  4. Use the Smart Queue — Review AI-generated messages before they reach customers
  5. Refine over time — Test your prompts and tweak them based on the output you get