The company was hiring in waves and losing money on every one. New engineers, product and sales people took nearly four months to reach full productivity, too many left before they got there, and the knowledge they needed was buried in old documents and hours of video no one had time to turn into a course.
In an organisation growing this fast, a slow onboarding is a direct cost. Ramp-up ran close to four months, early attrition was high, and every quarter's new intake hit the same wall: the material they needed to learn the job was scattered across ageing PDFs, an internal knowledge base and long recordings of meetings.
Nobody owned turning that raw material into training. HR and the department leads had no time to write and rewrite courses, so what existed was generic. A new hire sat through dozens of slides and readings that had little to do with their actual role or the experience they arrived with, which bored the seniors and left the juniors lost.
And whatever did get written went stale. Every time the product shipped a change or a process was updated, the training quietly fell out of date, and the next cohort was taught from material that was already wrong.
Generate the courses from the source material, tailor the path to the hire, and keep a human on the publish button.
We connected the company's knowledge, specs, process docs and meeting recordings, to an engine that scans the raw material, distils it, and produces interactive modules, summaries and knowledge-check quizzes automatically.
The pipeline reads the sources the knowledge actually lives in, long documents, internal wiki pages and hours of recorded sessions, and pulls the teachable substance out of all of them rather than leaving it locked in a file.
An algorithm tailors the plan in real time to the hire's role, department and experience level, skipping the fundamentals a senior already knows and focusing on the specific gaps the person actually needs to close.
Before a module reaches anyone, a structured draft goes to the relevant department lead for a fast approval, so accuracy is guaranteed by a human and no unchecked content is ever published to a new hire.
When the product or a process changes, the pipeline regenerates the affected modules, so the course a new hire takes reflects how the company works today, not how it worked two releases ago.
Completion and quiz results show where hires slow down or trip up, which tells the team exactly which material to sharpen next, so the programme keeps getting better instead of sitting still.
A focused, current, personal onboarding, built from what the company already knew.
Time to full productivity for new engineers and sales people fell from about four months to roughly six weeks. Retention of new hires through their first six months rose 25%, as a focused and relevant onboarding replaced the generic slog that had been pushing people out early.
The time and resources needed to create, update and maintain the company's training and onboarding programmes dropped about 60%. The knowledge stopped ageing in a drawer, and keeping courses current became a byproduct of the pipeline rather than a project no one had time for.
Hand-written training rots the moment the product moves, and generic training wastes the learner's time. The value here is a pipeline anchored to the company's own source material, with a manager's sign-off before anything ships, so the courses stay accurate and personal without a person rewriting them each release. It is the same enablement discipline behind our agent-training work, aimed at onboarding across the whole company rather than a single contact-centre desk.
Seasonal spikes doubled ticket volume faster than a month-long onboarding could staff for. An AI training simulator and a grounded copilot cut onboarding to ten days and scaled the desk 30% with zero breaches.
Read the case → Enablement · RetailA retailer had the AI tools and almost no one using them. Role-specific enablement, guardrails and real change management took adoption from 15% to 85% and cut administrative time about 40%.
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