Automate Training Program Generation for B2B SaaS Teams

Replacing a senior engineer costs 1.5x their salary. Maya runs sourcing, scheduling, and screening end-to-end — with a 4.2-week median time-to-hire. But hiring is only half the story. Once new hires are in, they need to ramp fast. That's where Training Program Generation breaks down for most B2B SaaS teams — and where Maya takes over completely.

The Training Program Generation problem most teams have

Most B2B SaaS companies lose $14,000 per new hire in lost productivity during the first 90 days — because training is cobbled together from outdated slide decks, tribal knowledge, and a single overworked HR generalist. Manual training program generation costs teams an average of 40 hours per program cycle. With a 30% annual turnover rate in SaaS, that means your team is spending 12 full weeks per year just rebuilding onboarding content. And 67% of new hires say they'd leave a company after a bad onboarding experience. That's real revenue walking out the door.

How Maya owns Training Program Generation end-to-end

Maya doesn't just schedule interviews. She builds the entire learning journey from day one. Here's how she owns Training Program Generation for your team:

• Sourcing — Maya pulls skill gaps from performance check-ins and engagement pulse surveys, then sources the right internal experts to build training modules. No more guessing what your team actually needs.
• Onboarding workflows — She generates a personalized 30-60-90 day training plan for every new hire, mapped to their role, seniority, and learning pace. No two plans are identical.
• Performance check-ins — Maya monitors progress against training milestones and automatically adjusts the program when a learner stalls. She flags at-risk hires before they fall behind.
• Exit interviews — When someone leaves, Maya analyzes exit data to identify training gaps that contributed to the departure. She updates the program to prevent the next person from leaving for the same reason.

Maya works 24/7, never takes vacation, and scales from 10 employees to 1,000 without adding headcount.

A concrete Maya workflow

BEFORE: Acme SaaS (50 employees) hired a new sales engineer named Priya. The VP of Sales spent 18 hours manually assembling a training deck from five different Google Docs, two Notion pages, and a Slack thread. Priya's first week had no structured learning. She hit her first quota 90 days late — costing the company $27,000 in missed revenue.

MAYA'S ACTIONS:

• Day 0: Maya receives Priya's start date from the ATS. She sources the top three sales engineers from the engagement pulse data and asks them to record 15-minute training videos.
• Day 1: Priya logs in to find a complete 30-day training program with daily tasks, scored quizzes, and peer review sessions scheduled automatically.
• Day 14: Maya runs a performance check-in. Priya scores 72% on product knowledge. Maya reassigns two additional modules and schedules a 1:1 with a senior engineer.
• Day 30: Maya generates a progress report. Priya is 94% proficient — ahead of schedule by 11 days.

AFTER: Priya hit her first quota in 38 days — 52 days faster than the average. Acme saved $14,000 in lost productivity per hire. The VP of Sales reclaimed 18 hours per new hire, or 90 hours per quarter.

Why Maya wins vs. hiring

Hiring a human VP of People costs $180,000–$250,000 per year plus equity. They take 90 days to ramp, take 4 weeks of vacation, and have a 15% annual attrition rate. Maya costs a fraction of that, is fully productive on day one, never takes a day off, and never quits. She augments your existing team — not replaces them. Your human VP of People focuses on strategy and culture; Maya handles the repetitive, data-intensive work of training program generation. Together, they're unstoppable.

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