We've built an AI learning-path module that runs against your taxonomy and your learner data, recommending the next best course or competency for each learner. Crucially, it runs on infrastructure you control — no learner data leaves your tenant. The recommendation logic is auditable, not a black box.
AI in L&D is a real productivity multiplier — but only if it runs on data you control. Black-box vendor AI raises data-privacy and security concerns.
A large L&D team could not hand-curate development paths for thousands of learners. The recommendation engine, trained on their own taxonomy and learner data, suggests each person's next best course or competency, so guidance that once required a manager conversation now scales across the whole workforce without hiring a bigger L&D team.
A skills-led organization wanted to see where capability gaps clustered across teams. Manager-side analytics surface learning gaps by group, turning individual recommendations into a workforce-planning view, so leaders can see which competencies are thin across a department and direct training budget where it actually moves the needle.
A security-minded company wanted personalized learning but would not send learner data to a third-party LLM. Because the module is self-hosted and runs inside their tenant, they get AI-driven recommendations with no external data egress, satisfying the privacy review that would have blocked an off-the-shelf vendor AI outright.
A production-grade Workplace deployment in your cloud, configured to your org structure.
Independent sub-environments for divisions, brands, locations, or external customers.
Direct integration with Workday, BambooHR, SAP SuccessFactors, ADP, or Active Directory.
We'll review your current platform, map your pain points, and give you a plain-English report — including a fixed-price quote if there's a fit. No sales pitch, just honesty.