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AI Agents in Flowla bring intelligence to your workflows. They analyze data, generate personalized content, and take action instantly—helping you scale without losing the human touch. Use them to write follow-ups, generate business cases, summarize forms or transcripts, and personalize content based on real-time engagement.

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Why it matters

Most sales and CS teams waste time on manual follow-ups, creating business cases, or summarizing takeaways. AI Agents handle these steps for you—on time, every time, based on real context. This means you can:
  • Move faster without sacrificing personalization
  • Send better follow-ups, faster
  • Align internal teams with rich context
  • Keep deals moving even when you’re in back-to-back calls

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What can AI-agents do?

You can drop AI Agents anywhere in your workflow, before an action. They analyze the situation and generate something smart.
  • Draft a personalized follow-up email based on form submissions or room activity
  • Generate a business case from your call transcript
  • Summarize kickoff forms and share the highlights with CS
  • Notify the team with enriched contact info and engagement insights
  • Personalize a proposal or mutual action plan using CRM or room variables
And yes, you can review and approve any AI-generated content before it goes out by adding the workflow to the Smart Queue.

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Real Examples

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Example 1: Form Submission → Summary

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

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Example 2: Room Not Viewed → Nudge Email

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

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Example 3: Call Transcript → Business Case

  1. Trigger: Gong transcription completed
  2. AI Agent: Generate business case from key discussion points
  3. Action: Add to room and notify deal owner

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Writing Effective Prompts

Good prompts include:
  1. Role - Who the AI should be
  2. Task - What to generate
  3. Context - Relevant information (use variables)
  4. Constraints - Length, tone, format
  5. Examples - What good output looks 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}}.

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Best Practices

  1. Be specific in prompts - Vague instructions produce vague output
  2. Include context - More relevant data leads to better personalization
  3. Set constraints - Specify length, tone, and format
  4. Use Smart Queue - Review AI-generated customer communications
  5. Iterate on prompts - Refine based on results