On paper there's one standard process. In practice, it depends on who did the training.
People complete the training. Then they're on their own when it counts.
Most teams only find out whether training stuck when something goes wrong.
Create a course
Set one up for the programme or playbook. Its modules come from your outline.
Upload & sync
Add playbooks, SOPs and frameworks (PDF, Markdown, text, images) to each module, then sync.
Update frameworks
Sophia, SLAN's co-pilot, reads your modules and proposes frameworks: the decisions, criteria and steps you teach.
Approve
Each framework arrives as Pending review. SMEs edit, decline, or approve it before any team member sees it.
Build & deploy the assistant
Single stage for Q&A and coaching, Multi stage for guided walkthroughs. Link frameworks to stages, preview, then deploy.
Open it to a cohort
One cohort per team, region, or intake. People join with a registration code, or you add them by email.
Exact onboarding and dashboards can be phased based on your pilot scope and governance requirements.
Deployments can avoid exposing raw materials and keep derived structures scoped to approved audiences.
Access can be scoped by team, region, or cohort: public, private, or restricted.
Completion, depth, and where learners got stuck, reported against your own baseline.
Generative AI executive programme, first three pilot cohorts.
“Half the [in-class exercise] debrief used to be me answering questions they should have already worked through. Now, the conversation focuses on what is important.”
If you need internal AI support with explicit content boundaries, request a demo and we'll map SLAN to your workflows.