The Revenue AI Report

AI Tech Landscape · Sales Coaching & Training

Quantified AI

Visit Quantified AI ↗quantified.ai

AI sales simulator for role-play and coaching with custom rubrics and consistent scoring to accelerate onboarding and performance.

Journey stage
Enablement and coaching
Ambition level
Amplify
Owning seat
Enablement

What it claims to do

  • AI-generated Avatars
  • Custom Rubrics
  • Individual Analytics
  • Consistent Scoring
  • Performance Analytics

Claimed benefit. Increased practice frequency, faster onboarding, improved performance

Reported use case. Teams get 6x more practice and ramp 42% faster

Source: the vendor and the capability mapping work behind this map. The Revenue AI Report has not independently verified these figures. Verified findings live in Research, with method, sample, and field date attached. Unfamiliar terms are defined in the AI and Revenue Dictionary.

Published case studies

We found a minimum of 3 published case studies here. There may be more we have not found. Case studies are published by the vendor. Customer names, figures, and outcomes are the vendor's claims. The Revenue AI Report has not audited them. Independently checked findings live in Research, with method, sample, and field date attached.

How to read these claims

The sample is chosen by the seller
A case study is the best result the vendor is allowed to publish. It is not a sample of all customers. The accounts that churned do not get a page.
There is no control group
Almost no vendor study compares the team using the tool against a matched team that did not. Without that comparison, the lift reported cannot be separated from headcount changes, pricing changes, seasonality, or a good quarter.
The baseline is usually missing
A percentage gain means nothing without the starting number. A 300% increase in meetings from two meetings a week is eight. Ask for the absolute figures and the time window.
Activity is not revenue
Most published gains are activity metrics: emails sent, replies, hours saved, meetings booked. Closed revenue, win rate, and retention are the metrics that survive a board meeting. Ask which one the study actually measured.
Named logos are not always customers
Logos and case studies have been published for accounts that had already churned or had only run a pilot. Ask the reference directly, by name, and ask how long they have been live.

Field notes: what users say in public

Independent feedback from review sites and practitioner forums, not vendor marketing. This is what a buyer would hear from a peer who has already run the tool.

4.5G2, 16 reviews, observed 2026Check the live score ↗

What holds up

  • 75% of G2 reviews are 5-star, with a small minority at 2-star and none at 1 or 3-star, indicating generally consistent satisfaction G2 ↗

What people complain about

  • Review volume is small at only 16 ratings on G2, limiting statistical confidence despite the high average score G2 ↗

Fits enterprise and regulated-industry sales teams needing certification-grade roleplay, overkill for small teams wanting simple practice reps.

Ask these on the call

  1. 01What is the realistic implementation timeline for a compliance-grade certification program versus a simple roleplay use case?
  2. 02How does per-seat pricing compare once you include content configuration and avatar customization services?
  3. 03Can you share references specifically in a regulated industry similar to ours?

How to read review evidence

Review sites are a biased sample
Most reviews are collected by the vendor, often with an incentive attached. Scores cluster high across the whole category, so a 4.6 average is closer to par than to proof. Read the one and two star reviews first, and read the most recent ones, because product and pricing change faster than the average score does.
Forums show the failure modes, not the base rate
Reddit and Hacker News threads surface what breaks, which is exactly what a business case needs. They do not tell you how common the problem is. Treat a repeated complaint as a question for the vendor, not as a verdict.
Complaints about price are usually complaints about structure
Seat minimums, credit packs that expire, annual lock-in, and per-action pricing produce most of the pricing anger in public reviews. Get the structure in writing, not the headline number.
Ratings are a snapshot
Every score here is dated. Check the live page before you cite it in a board deck.

The friction above is the tool level version of a pattern the Report has already measured. See The Eight Seats baseline for the method, sample, and field date behind it.

Claims versus the record

No citable discrepancy between this vendor's public claims and independent reporting was found at the time of the last check. That is not verification. It means nothing has been published either way, so the claims above still rest on the vendor's own account.

What has to be true before you buy

The Report does not review tools in isolation. Every tool on this map is connected to three things we publish elsewhere on the site: a decision framework that tells you how to evaluate it, a research theme that shows what we have measured in the market around it, and an essay that applies both to a real case. Those links appear at the bottom of this section so you can verify our reasoning instead of taking this page at face value.

Ambition level: Amplify

The structure changes. Judge it on win rate, forecast accuracy, or churn, with a baseline.

Decide what the new rep is trained on when the tool does the first draft.

Friction at this stage

  • Ramp measured in quarters
  • Coaching capacity capped by manager time
  • Knowledge scattered across systems

The framework to apply

LOPAFT is the decision framework the Report uses for tools at this stage. Adoption is a ladder. Most rollouts lose the Feedback rung, not the Learn rung.

The research behind it

The Eight Seats baseline is the market evidence we have published for this category, with method, sample, and field date attached. What each seat reported getting from AI.

The essay that applies it

Just-in-time enablement with AI shows this framework and this evidence applied to a real situation, so you can see the reasoning end to end.

Common questions about Quantified AI

What does Quantified AI do?
AI sales simulator for role-play and coaching with custom rubrics and consistent scoring to accelerate onboarding and performance. It sits in the Sales Coaching & Training category and maps to the Enablement and coaching stage of the revenue journey.
Where does Quantified AI fit in a revenue team?
Quantified AI maps to the Enablement and coaching stage at the Amplify level of ambition, and is usually owned by the Enablement seat. Reported use: Teams get 6x more practice and ramp 42% faster
Does Quantified AI publish customer case studies?
Yes. 3 named customer stories are published, including Sanofi, Novartis, OpenLending. These are vendor claims, not figures verified by The Revenue AI Report. A case study is the best result a vendor is allowed to publish, not a sample of all customers.
What do buyers say about Quantified AI?
Public score 4.5 on G2 from 16 reviews, observed 2026. Praised for: 75% of G2 reviews are 5-star, with a small minority at 2-star and none at 1 or 3-star, indicating generally consistent satisfaction Friction reported: Review volume is small at only 16 ratings on G2, limiting statistical confidence despite the high average score Fits enterprise and regulated-industry sales teams needing certification-grade roleplay, overkill for small teams wanting simple practice reps.
What should we ask Quantified AI before buying?
What is the realistic implementation timeline for a compliance-grade certification program versus a simple roleplay use case? How does per-seat pricing compare once you include content configuration and avatar customization services? Can you share references specifically in a regulated industry similar to ours?

Answers are assembled from the vendor material, published case studies, and independent evidence shown on this page. Terms are defined in the AI and Revenue Dictionary.