Customer Support and Voice AI
AI receptionist for small business: calls, bookings and handoffs
What an AI receptionist does on a real call, the rules that apply, a sample greeting and a pass/fail checklist to launch one safely.
Call Intelligence
AI Call QA
Every call scored against your own quality checklist, with the misses and the reasons attached.
Supervisors can only listen to a handful of calls, so most quality problems go unnoticed until a customer complains. AI Call QA scores every recorded call against the checklist you already use, from greeting and required disclosures to tone, and flags the ones that fall short with reasons. You set the rules and the pass mark.
- Scores every recorded call against your own checklist
- Flags missed disclosures and low scores for supervisor review
- Explains each failed score so coaching starts from facts
$4,900
20–30 working days
Optional maintenance $249/mo
What it is
AI Call QA is an AI agent that listens to your recorded calls and scores each one against the quality checklist you already use: greeting, required disclosures, script adherence and tone. It flags the calls that fall short and explains why.
Why businesses buy it
Manual call reviews cover a small sample, so coaching relies on luck and compliance gaps hide in the calls nobody heard. This agent checks every recorded call the same way, using the scoring rules your team already trusts, and puts the calls that need attention in front of a supervisor with the reasons attached. Reviews take less time and coaching gets fairer. The Scope Card fixes the checklist, the data sources, the delivery channel and the testing against three months of your past calls before you buy, so scores match what your reviewers expect.
Problems this solves
Supervisors can only review a small sample of calls by hand
AI Call QA listens to your recorded calls and scores each one against the checklist you already use. Supervisors see scores across far more calls than manual sampling ever reached.
Missed disclosures are only found long after the call
Required disclosures are part of the scoring checklist. Calls that miss one are flagged with an explanation, so you can act while the issue is still fresh.
Quality scores differ depending on who does the review
Every call is scored against the same criteria for greeting, disclosures, script adherence and tone. That gives your team a consistent starting point for feedback.
Coaching time goes on finding problem calls, not fixing them
Flagged calls arrive with the reason they fell short, through email, Slack or a web dashboard. Supervisors can go straight to the conversations that need attention.
A good fit if
You have a call quality checklist, but a person only has time to review a small sample of calls each week.
You need every agent, not just a handful, checked against the same standard.
You want the calls that failed a check flagged automatically, with the reason attached.
You already coach agents on calls and want the review work done before the coaching conversation.
Not the right fit if
You just want a short note on what happened, not a score. See AI Call Summarization, which writes a summary with no grading.
You want to know why a lead was or was not qualified, not how the call was delivered. See AI Call Qualification Agent.
You want volume and outcome trends across all calls, not a per-call grade. See AI Call Analytics.
You want quality checked while the call is still happening, not afterwards. See AI Voice Supervisor, which watches live queues.
How it works
- Recorded calls come in through the telephony account you already use, such as Twilio, Aircall or RingCentral.
- Each call is transcribed, then checked line by line against the rubric you approved, such as greeting, disclosures and required questions.
- A score is calculated per call, with the specific lines that passed or failed the checklist attached as evidence.
- Calls that fall below the pass threshold you set are flagged for a supervisor to review first.
- A recurring QA report rolls scores up by agent, team or call type, so patterns are visible without listening to every call.
- Warm transfer is not part of this build. It reviews completed calls; it does not sit on the line during them.
What you provide within 72 hours
Your portal lists these the moment you order. Delivery starts the working day after everything is in and your access is checked.
- Your business information (company basics, hours and brand voice), shared during intake.
- A telephony account or the phone number you want ported or forwarded to it.
- Your quality checklist, call scripts and business hours, in the wording your team already uses.
- The phone numbers a call should escalate to when a caller needs a person.
- Read-only access to each data source the scores pull from, plus your own definitions of a pass and a fail.
- At least three months of historical call data, so we can check the scoring against real cases before launch.
- Admin access and API keys for every connected system, shared by adding our team as a user or creating a key you control, never by email.
- One decision-maker on your side who can approve the rubric and sign off on launch.
- An API key for your own AI model account (for example OpenAI or Google Gemini), created for this build with a spending limit.
The 72-hour rule. Send everything on your checklist, including access, within 72 hours of ordering so your build starts on time.
Timeline
Start
Intake verified and the scoring rubric agreed with you.
Weeks 1–2
Call ingestion, transcription and the scoring logic are built.
Week 3
Your CRM or dashboard and delivery channel are connected.
Weeks 3–4
Scores are checked against three months of your historical calls.
Week 4
Your review and two rounds of changes to the rubric.
Go-live
Live, with a recorded handoff session, and support starts.
| Option | Delivery time | Price |
|---|---|---|
| Standard | 20–30 working days | $4,900 |
| Express | 15–25 working days | $5,750 |
| Rush | 10–20 working days | $6,600 |
What you receive at handover
- AI Call QA, configured and deployed to your environment
- Your quality checklist set up as workflow, prompt and guardrail configuration, within up to 25 defined criteria
- Read-only connection to up to three data sources, such as your call recording platform
- One dashboard or recurring report in your chosen channel, plus up to five alerts
- A test report comparing scores with three months of your historical calls
- An admin guide, recorded 60-minute handoff session and 30 days of post-launch support
Expected benefits and how to measure them
- More of your calls can be checked for quality, not just a sample.
- Compliance gaps can be spotted sooner.
- Supervisors can spend more time coaching and less time searching.
- Calls reviewed per week
- Compare manual reviews logged before launch with calls scored by the agent each week.
- Disclosure misses
- Track flagged disclosure misses per month in the report, and watch the trend after coaching.
- Average quality score
- Follow the team's average checklist score month by month from the dashboard.
Before you start: Record how many calls you review by hand each week and your current scores. Note any known compliance issues from the last quarter.
These are things to track, not promised results. Outcomes depend on your data, your team and your market.
Running costs
The build price is one-time. Running it costs roughly $20 to $150 a month in your own accounts, covering AI model usage and the hosting or scheduler that produces the scores.
AI usage during the build and testing is also billed to your accounts, so every provider relationship stays yours. Nothing runs through us.
Ask about running costsCustom requirements
If you need something outside the Scope Card, add a note at checkout. You get a written Change Quote, and that work only starts once you accept it. Larger or bespoke projects go through the Custom AI request form instead.
Request a custom versionKeep it running
We recommend monthly maintenance, which covers monitoring, fixes and a monthly allowance of change hours, for things such as a new checklist item or an updated pass threshold. It starts after the 30 days of included support and can be cancelled any month.
$249/mo (the minimum fee, includes 2 change hours)
Optional. Starts after the post-launch support period. Cancel any month.
How maintenance worksHow this compares
| Do it yourself with a SaaS tool | Hire a custom agency | Upmark Labs | |
|---|---|---|---|
| Price | A QA platform is priced per agent seat, per month | A custom build gets quoted after discovery calls | Ours is one fixed price, shown on this page before you buy |
| Scope | A QA platform ships a generic rubric you adapt to | An agency agrees scope during the project | Ours scores against the checklist you already use |
| Coverage | A QA platform often samples a percentage of calls | An agency build depends on what was agreed | Ours checks every call inside the agreed scope |
| Delivery | A QA platform needs weeks of rubric tuning | An agency project usually runs several weeks, set per project | Ours has a fixed delivery time shown before you buy, with faster options |
| What it judges | A QA platform rarely separates scoring from lead qualification | An agency build depends on what was agreed | Ours only scores quality; qualification is a separate build |
Questions about this product
How much does AI Call QA cost?
The fixed build price for each delivery speed is listed in the price and delivery panel on this page, and it covers everything on the Scope Card. That includes building your checklist into the scoring, testing it against three months of your own call history, two rounds of changes and thirty days of support after launch.
Can AI Call QA use the checklist we already grade agents on?
Yes, we build the rubric from the checklist you already use, so scores map to categories your team recognizes, such as greeting, disclosures and script adherence. You define what counts as a pass during intake, and we test the scoring against three months of your real calls before it goes live, so results match what a human reviewer would flag.
What does AI Call QA cost to run once it is live?
Running costs sit at roughly $20 to $150 a month in your own accounts, covering AI model usage plus the hosting or scheduler that produces the scores. You pay those providers directly, in your own name, so you keep full ownership of every account. We charge nothing per call scored.
How does AI Call QA differ from AI Call Analytics?
AI Call QA grades individual calls against your quality checklist, with a pass or fail and the reason for each. AI Call Analytics looks across all calls for patterns, such as volume, duration and outcomes over weeks. One tells you how a single call was handled, and the other tells you what is happening across the whole line.
What do you need to give us to start AI Call QA?
We need read-only access to your call recordings or transcripts, at least three months of history to test against, your current checklist or scoring rubric, and the pass mark for each item. Tell us where results should go, such as a dashboard or a weekly email. Access is shared by adding our team as a user or creating a key you control, never by email.
Will agents know their calls are scored by AI?
Yes, the QA report is labeled as AI-generated, so anyone reading it knows its source before using it in a coaching conversation. Some regions expect disclosure when automated tools assess staff performance. You confirm the exact wording during intake, and it can be updated later through monthly maintenance.
Can we add checklist items after launch?
Yes, small changes such as a new checklist line or an adjusted pass threshold fit inside the monthly change hours that come with maintenance. A larger change, such as scoring a second call type on a different rubric, comes through the Additional Workflow add-on, quoted before the work starts.
Guides on this topic
All guides Grade every call, not just the ones you have time to hear.
Order AI Call QA today and it goes live on a fixed delivery date. The scope above is exactly what you get, in writing, before you pay.
Works well with
Call Intelligence
AI Call Summarization
Summarizes calls into notes, outcomes and next steps in your CRM.
Call Intelligence
AI Voice Supervisor
Monitors AI and human calls, escalations and quality in one console.