Where corporate training fails
Most corporate training is frontloaded — a 2-day workshop, a half-day onboarding session, an annual compliance module. Knowledge retention from frontloaded training falls off a cliff: within 30 days, learners retain only 21% of what was taught. The investment leaks straight out of the team.
A training assistant GPT changes the model. Instead of frontloading, it provides spaced practice — 5-minute role-plays, scenario-based coaching, and just-in-time refreshers. Competency builds over months, not days, and the data on actual skill development becomes visible to the L&D team for the first time.
What we build
Sales Role-play Coach
Reps practice discovery calls, objection handling, and pricing conversations against realistic AI customers. Detailed feedback after each session. Manager sees which reps are getting better at what.
Customer Service Practice
Support agents practise difficult conversations (angry customer, fraud claim, escalation request) with calibrated AI personas. Real-world handle time drops as practice volume rises.
Compliance Scenario Training
Instead of a multiple-choice quiz, staff work through realistic scenarios ('a vendor offers you a $300 gift voucher — what do you do?'). Adaptive, retention-focused.
New Hire Onboarding Coach
Walks new hires through their role's core scenarios in their first 30 days. Knows when to push and when to ease off. Manager dashboard shows ramp-readiness.
LMS and platform integrations
- Litmos — competency tracking and SCORM compliance
- Cornerstone OnDemand — for enterprise L&D
- Docebo — modern LMS with AI integrations
- GoLearn — for SMB L&D
- Slack/Teams — daily 5-minute practice via DM
- Salesforce/HubSpot — to correlate training with actual sales outcomes
What L&D teams are seeing
A 380-rep B2B sales organisation in Sydney measured a 42% increase in objection-handling proficiency (measured by win rate on competitor-displacement deals) after 6 months of daily 5-minute role-play with a training GPT. The same team's onboarding ramp time (days to first quota-meeting month) dropped from 110 to 76. A national contact centre cut average handle time by 18% after deploying a customer service practice bot for tier 1 agents.
Practice over consumption. The single most important design decision is short, frequent, scenario-based practice — not long-form content delivery. The GPT works for 5 minutes a day, every day, instead of 4 hours once. Retention curves are dramatically better.
Frequently asked questions
Doesn't this just generate generic role-play scenarios?
Not in the right configuration. We feed the GPT your actual sales call recordings, your support ticket archives, or your real compliance scenarios so the role-plays mirror reality. A generic 'angry customer' role-play has limited value; a role-play of an actual scenario your team faced last month is genuinely useful practice.
How does it measure competency?
We track multiple signals: completion rate on scenarios, scoring against rubrics (calibrated against your top performers), pattern recognition across attempts, and integration with downstream outcome data (sales win rates, support CSAT, compliance error rates). The metric stack is more honest than a frontloaded test score.
Will staff actually use a daily 5-minute training bot?
Adoption requires social design. We deploy as a Slack/Teams DM with a daily nudge, gamified streaks, and team leaderboards (opt-in). Voluntary daily-active rates we've seen: 60–75% in mature deployments. Mandatory deployments hit 90%+ but with mixed quality of engagement.
Is the AI feedback actually useful, or just generic encouragement?
We tune the feedback model on your top performers' actual coaching language — so the GPT gives feedback the way your best sales managers do. Generic 'great job!' feedback is the failure mode; we measure it and tune against it. The feedback is sometimes blunt; that's the point.
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