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SaaS / B2B·AI Agents & Automations·10 Weeks

Ekho

Trading 40 Hours of Live Coaching for One AI Agent

A sales organization training 50+ reps hit the ceiling on how much live coaching their managers could deliver in a week. We built AI agents that run realistic buyer conversations with reps and give them scored feedback the moment a session ends.

15+ hours/week

Manager Hours Reclaimed

3 weeks to 4 days

Onboarding Time

Under 4 minutes

Avg Session Duration

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Responsive UI mockup of the Ekho AI sales coaching dashboard on laptop and mobile screens, a SaaS UI design case study by Hexaa.
“They took a process we thought only humans could do and automated it without losing any of the quality. Our managers got their calendars back in under two months.”
DM

Daniel Meyers

VP of Sales, Ekho

Before

3 week onboarding wait, 15+ hours weekly in live role play, uneven rep readiness at scale

After

4 day onboarding cycle, zero live sessions needed, same training for every rep

Narrative

The full story.

The Challenge

With the team growing fast, managers were spending 15+ hours a week on one on one role play sessions and still couldn't cover everyone. New hires waited 2 to 3 weeks for their first real practice round because there simply weren't enough hours in the day.

What We Built

We built an AI agent that plays the buyer, using custom personas that object, stall, and push back the way a real prospect would. A feedback layer scores every session automatically and routes the right data to managers, admins, and reps based on their role. A full training scenario now takes under 4 minutes, replacing the 45 minute live sessions entirely.

Results

Onboarding dropped from 3 weeks to 4 days. Managers got 15+ hours back every week to spend on strategy and deal support. Every rep now trains on the same personas with the same scoring, so performance across cohorts leveled out. The project paid for itself in one quarter through faster first deals, roughly 6 weeks sooner per rep.

Story gallery

Project snapshots.

Technical proof

How it was built.

Implementation details and the stack behind the delivery.

Implementation highlights

Key engineering decisions from this project.

Built hierarchical tracking so admins, managers, and reps each see the data that matters to their role
Set up automated cloud backups with point in time recovery so no training data gets lost
Shipped a continuous release pipeline that brought deployments down from days to minutes

Stack snapshot

Tools and platforms used in the delivery.

Python OpenAI PostgreSQLLiveKitAWS

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