How to scope ai voice agent projects in 2026
Video walkthrough: https://youtu.be/vmEzJd6EdhU
  • This is the scoping process I use personally. It’s not the only approach, but it’s the one that consistently works for me.
The two questions that drive every voice agent project
1. What systems does the agent need to integrate with?
The technical landscape you must understand before building anything.
2. What does the agent need to do inside those systems?
The workflow, data flow, and behaviors required for the agent to succeed.
Step 1: Identify all required systems
  • CRM — Where contacts are stored, updated, tagged, and pushed into pipelines (GoHighLevel, HubSpot, Salesforce).
  • Scheduling System — Where appointments are fetched, created, rescheduled, or canceled (GoHighLevel Calendars, Calendly).
  • Voice Agent Platform — Where the AI handles speech, function calling, and event delivery (Vapi, Retell).
  • Automation Layer — Where logic is executed between systems (Make.com, n8n).
  • Phone Provider — Where the numbers, routing, and transfers originate (Twilio, Telnyx).
Additional technical dependencies
  • SMS/Email Systems — For confirmations and reminders (GHL SMS, Twilio SMS).
  • External APIs — Eligibility checks, service-area lookups, or pricing references.
  • Knowledge Base Sources — FAQs, policies, scripts, documents, compliance statements.
  • Compliance Requirements — Mandatory disclaimers, tone restrictions, data-handling rules.
Step 2: Define the core use case
  • Identify the primary function the agent must perform. Examples:
  • Appointment booking
  • Lead qualification
  • Call routing and triage
  • General inbound receptionist
  • This determines what data you’ll collect, what actions the agent must take, and what workflows must be built.
Map all caller intents
  • Break the conversation into branches:
  • New inquiry
  • Existing customer
  • Reschedule
  • Support request
  • Out-of-scope question
  • Each branch requires different data fields, actions, transfers, and workflows.
Define behavior, data, and system actions
  • Data Collection — name, phone, email, address, service type, reference numbers.
  • Transfer Rules — who to transfer to, when transfers occur, after-hours behavior.
  • Scheduling Rules — which calendar to use, how availability is fetched, buffer requirements.
  • CRM Actions — create contact, update tags, move pipeline stage, attach notes.
  • These decisions shape every part of the final architecture.
Example — FreshNest Home Cleaning
Industry: Residential Cleaning
Primary Goal: Automate appointment bookings and reduce call load
Call Volume: ~20–30 inbound calls per day
Systems Used: GoHighLevel only (CRM + scheduling)
What the client says (non-technical):
“We want a voice agent that answers our incoming calls, asks customers what type of cleaning they need, checks our GoHighLevel calendar for open time slots, and books them into our schedule.
The agent should collect the customer’s name, phone, email, and address and store everything inside GoHighLevel so our team has full visibility.
If someone calls about something unrelated or something we don’t handle, the agent should transfer the call to our office line.
If they want to reschedule, it should text them our GoHighLevel reschedule link instead of trying to handle it manually.
Basically, we want a simple booking agent that can handle most of our calls without needing a human.”
Key non-technical requirements:
  • Real-time availability using GoHighLevel calendar
  • Appointment creation inside GoHighLevel
  • Contact creation & updates
  • SMS confirmations via GoHighLevel
  • SMS rescheduling link
  • Call routing to a human line
  • Support for automation via GHL + optional n8n/Make
Note: All of this information is typically collected during the discovery call or onboarding call, depending on how you structure your intake process.
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