AI-Powered Workflow Intelligence

Drop an AI Action Into Any Workflow - No Code Required

Centripe’s Workflow AI Action is simple and easy to use in the automation builder. Add it to any workflow, the same way you’d add a ‘Send email’ or ‘Create task’ step. But this one is based on AI model. It reads the data flowing through the workflow, process it, and gives an output that feeds into the next step.

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AI Actions

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Automation

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Accuracy

Smart Workflows

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AI Decision Engine

Makes intelligent decisions based on data and context

What the Actually Is

It's not a separate product. It's a step type inside the automation builder you already use.

Every Centripe automation has a trigger ("when this happens") and a sequence of actions ("do these things"). You already use actions like "send email," "add tag," "create deal," and "wait 3 days."

The Workflow AI Action is another action type in that same list. When the workflow reaches it, it sends the contact's data to an AI model, the model processes it, and the result gets stored on the contact record or passed to the next step in the workflow.

You set it up the same way as any other action through a visual settings panel. No code, no API keys, no complicated prompt writing. Just tell it what you want in plain English: "Score this lead based on their form answers and assign a priority tag."

Trigger: New form submission received
AI Action: Analyze form responses, score lead quality, draft personalized follow-up email
Condition: If lead score > 70
↓ Yes
Action: Send AI-drafted email + create deal in pipeline + notify sales rep
↓ No
Action: Add to nurture sequence + tag "low priority"

What You Can

Real workflow examples, not marketing categories.

Score leads from form data

A prospect fills out your intake form. The AI reads their answers. This includes company size, budget, timeline, and industry. Then, it scores them using your criteria. The score is saved to the contact record. High scored leads go to sales, low scores go to nurture. No manual review needed.

Draft personalized follow-ups

After a call or appointment, the AI writes a follow-up email. It uses the contact’s history, like what they asked, their stage, and the content they engaged with. It goes for review or auto-sends if you set it that way. Every email is different based on each contact’s unique data analyzed by AI.

Categorize and route support requests

A customer submits a form or chat message. The AI reads the message. It finds the category: billing, technical, feature request, or complaint. Then, it sets a priority, and routes it to the right team member.Urgent issues get flagged immediately. Routine questions get an auto-response from the knowledge base.

Summarize call transcripts

After a call is transcribed, the AI lists key points. It also notes action items, objections, and suggests the next step. The summary attaches to the contact record. Your sales manager can review 20 summaries in the time it takes to listen to 2 recordings.

Enrich contact records

A new lead enters with just a name and email. The AI checks the email domain, form responses, pages visited, and referral source. Then, it adds likely industry, company size, and interest tags. Not perfect, but better than a blank record in your pipeline.

Generate campaign content at scale

Running a nurture sequence for 6 audience segments? Instead of writing each email manually, the AI generates copy per segment. Agency owners get agency-focused language. In-house marketers get different messaging. Same workflow, automatically personalized for every segment at scale.

How This Is Different from the

The Copilot helps YOU work. The Workflow AI Action works WITHOUT you.

AI Copilot Workflow AI Action
When it runs When you open a contact, conversation, or campaign - you see its suggestions When a workflow trigger fires — automatically, in the background, no human present
Who initiates You do - by opening the CRM, reading a conversation, clicking "draft reply" The automation trigger - a form submission, a deal stage change, a time delay
Human in the loop? Yes - you review and approve every suggestion Optional - it can auto-execute, or you can add an approval step
Best for Interactive work — drafting replies, reviewing pipelines, creating campaigns Background automation - processing form data, routing leads, generating content at scale
Analogy Your personal assistant sitting next to you A machine running in the back room, processing work overnight

Most teams use both: the Copilot for their active work during the day, and Workflow AI Actions to process everything that happens in the background - form submissions, after-hours inquiries, lead scoring, automated follow-ups.

Setting Up a

Four steps inside the visual automation builder. No code, no API configuration.

Open the automation builder

Go to Automations in Centripe. Create a new workflow or edit an existing one. Set your trigger - this could be "form submitted," "deal stage changed," "appointment booked," "tag added," "invoice paid," or dozens of other events.

In the action list, select "AI Model Action." It appears alongside "Send Email," "Add Tag," "Create Task," and all the other standard steps. Drag it into your workflow where you want the AI to process data.

Tell it what to do

In the configuration panel, describe the task in plain language: "Analyze this form submission. Score the lead from 1-100 based on company size and budget. If the score is above 70, draft a follow-up email mentioning their specific use case." You can also select from pre-built templates for common tasks like lead scoring, content drafting, and data extraction.

Map the output

Tell the workflow where to put the AI's output. The lead score → custom field on the contact. The drafted email → next "send email" step. The category tag → contact tag. The summary → notes field. The AI Action's output plugs into the rest of the workflow like any other data source.

Triggers That Can Fire an

Any workflow trigger in Centripe can kick off an AI Action. Here are the most common.

The form builder captures the data, the AI Action processes it — scoring, categorizing, drafting a response. Most common trigger for lead qualification workflows.

When a deal moves to "Proposal Sent" in the pipeline, the AI Action drafts a case study email relevant to that prospect's industry. When it moves to "Closed Won," it generates an onboarding checklist.

Pre-meeting: the AI Action pulls the contact's history and generates a briefing doc. Post-meeting: it processes the call transcript and creates a summary with action items. Connected to appointment scheduling.

After the AI Receptionist or Aeri chatbot finishes a conversation, the AI Action can summarize it, update the CRM, and trigger follow-up sequences based on what was discussed.

When a contact gets tagged "VIP" or "at-risk," the AI Action drafts a personalized message for that scenario. Tag-based triggers let you build reactive workflows that respond to classification changes.

Run an AI Action every Monday morning: scan all stale deals (no activity in 7+ days), draft re-engagement messages for each one, and queue them for the sales team to review. Batch processing on a schedule.

How Agencies Use

The highest-leverage use cases for agencies managing multiple client accounts.

Build a lead qualification workflow once, then deploy it to every client sub-account as a snapshot template. Each client gets the same AI-powered scoring and routing. You maintain quality across 50 accounts without manually configuring each one.

Every month, a scheduled AI action pulls pipeline data, campaign stats, and lead counts from each sub-account, then writes a summary and drafts the client report. The agency rep reviews and sends it. This is done in 20 minutes instead of 2 hours.

Leads that come in after 5 PM through the AI Receptionist or website chatbot hit a workflow AI Action that scores, tags, and routes them. When the team arrives Monday morning, every weekend lead is already scored, categorized, and queued with a drafted first-touch message.

How Connect to the Platform

The AI Action step reads from and writes to every part of Centripe.

Reads From Writes To
Contact record (name, tags, custom fields, lead score) Contact custom fields, tags, notes
Conversation history (email, SMS, chat transcripts) Draft messages queued for sending
Form/survey responses New deals in the pipeline
Call recordings and transcripts Tasks assigned to team members
Pipeline data (deal stage, value, age) Lead scores and qualification status
Campaign engagement data (opens, clicks) Segment membership and list assignments

Frequently Asked

Everything you need to know about AI workflow automation

Available on both plans. The $99/month Starter plan includes basic automation workflows but not the AI Action step type. Check the pricing page for the full comparison.
AI Action usage is tied to your plan's AI credits. Each action execution consumes credits based on the complexity of the task. Simple scoring tasks use fewer credits than long-form content generation.
You describe the task in plain language - "score this lead based on budget and timeline" - not in technical prompt syntax. You can also choose from pre-built task templates for common scenarios (lead scoring, email drafting, data extraction, categorization). If you want fine-grained control, you can write detailed instructions, but it's not required.
Yes. The AI Action outputs a result (a score, a category, a yes/no decision), and the next step in the workflow can branch based on that output using standard if/then conditions. For example: if lead score > 70 → create deal + notify sales. If score < 70 → add to nurture sequence.
The workflow builder includes error handling: you can set a fallback path (e.g., "if AI Action fails → assign to human for manual review"), configure retry attempts, and receive notifications when failures occur. All AI Action results are logged so you can audit and improve.
Yes. The automation builder has a test mode where you can run a workflow with a test contact and see the AI Action's output at each step before activating it for real contacts. This lets you verify the scoring logic, check the drafted content, and confirm the routing works correctly.
With Zapier + ChatGPT, you're connecting external tools through API calls - your data leaves Centripe, gets processed externally, and results come back. With the Workflow AI Action, everything stays inside Centripe. The AI has direct access to the contact record, conversation history, and pipeline data. No data leaves the platform, no API latency, no token limits to manage, no Zapier subscription cost.
Yes. Each sub-account's workflows are independent. A dental client's lead scoring criteria can be completely different from a real estate client's. You can build a template workflow once and customize the AI Action instructions per client when you deploy the snapshot.