What is the precise difference between an LMS and an LXP?
A Learning Management System is top-down and compliance-oriented: the organisation makes courses available, assigns them and measures whether people have completed them. It works well for mandatory training. A Learning Experience Platform puts the employee at the centre: recommendations based on role and goals, content from multiple sources, peer recommendations, microlearning and self-chosen learning paths. Many organisations run both side by side — an LMS for compliance and an LXP for voluntary and personalised learning. Which route suits you depends on your learning culture and the nature of your content.
Do you use Moodle, TalentLMS or another off-the-shelf package as a base?
No, not as a foundation. We build our custom LXPs from the ground up on modern web frameworks (usually Next.js plus a Node or Python backend) with PostgreSQL as the data layer. Standard LMS packages such as Moodle or TalentLMS have a data model and plugin architecture designed for compliance training; working against that structure in an LXP context often costs more than starting afresh. What we do do: integrate with existing LMS instances if they remain in your landscape for the compliance side.
Which content standards do you support?
SCORM 1.2 and 2004 for classic course packages, xAPI (Tin Can) and cmi5 for modern tracking scenarios, including learning that happens outside the platform, LTI 1.3 for integration with external content providers, and H5P for interactive content. A built-in learning record store logs all activity regardless of source, so you have a single, central view of learning activity. For video, we usually use a dedicated video library (Mux, Cloudflare Stream or an internal S3 environment), so hosting isn't tied to a third party.
Can we migrate content from our current system?
In most cases, yes. SCORM and xAPI packages are relatively straightforward to migrate because they are built on standards. Content stored locally in a legacy system (video files, PDFs, hand-built HTML pages) requires a migration script that we write for each situation. We migrate metadata such as skill tags, audience assignments and learning paths automatically wherever possible. This is often the ideal moment to tidy up your taxonomy rather than carry errors from the old system across.
How exactly does the AI personalisation work?
It works on three levels. The first level is role-based: a new employee in a particular team receives a starting recommendation based on what colleagues in the same role have completed. The second level is skill gaps: the platform compares the skill profile from self-assessment and performance data with the role profile and suggests content to close any gaps. The third level is behaviour: what someone has already completed, what they have liked or saved, and what their peer group is following. For larger programmes, we add a Q&A bot that answers questions based on your own course material, with source references so employees can verify where the answers come from.
Does the platform integrate with our HRIS and Microsoft Teams or Slack?
Yes. For HRIS, we typically build a two-way integration with BambooHR, Workday, SuccessFactors or AFAS via API or SCIM, so role changes, joiners, leavers and performance data flow into the LXP automatically, and learning activity and skill progression flow back to HR. For Teams and Slack, we build a bot that handles recommendations, reminders and learning questions directly in the chat, so employees don't need to log in separately. SSO via Azure AD, Okta or Google Workspace is standard.
What determines the cost of such a project?
Scope (how many modules and which functionality), depth of integration (how many external systems are involved and in which direction), whether AI components such as a Q&A bot are included, the number of languages and regions, and how much you want to keep managing content or metadata yourself. A personalisation layer on top of existing content is a different project from an end-to-end platform with AI and deep HR integrations. After the scoping phase, we give you an honest estimate; without that context, any figure given upfront would be a guess, and we'd rather not make one.
How long before we can go live?
A defined first version, such as a personalisation layer for one department or a pilot group of a few hundred users, can go live in a few sprints. A broader project with multiple integrations, AI components and a rollout to thousands of employees takes several sprints. We always phase the work: first one target group goes live, we gather experiences, and then we scale up. We only expand the scope once that first group is working reliably on the platform.
What about GDPR, privacy and the retention of learning results?
Learning data is personal data and falls under the GDPR. We build role-based access so that only the employee themselves and, depending on your policy, their direct manager can see individual results; aggregated reports for L&D cannot be traced back to individuals. Retention periods are configurable per data category (progress, certificates, sentiment), so you decide how long results remain after someone leaves the organisation. For AI components, we run models either self-hosted or via Azure OpenAI with EU data residency, and course material never leaves your own tenant.
Do you work together with our in-house L&D, HR and IT teams?
Almost always. A learning experience platform (LXP) touches L&D (content and instructional design), HR (roles and the talent cycle) and IT (identity, security, hosting) all at once. We start with workshops involving all three disciplines, keep a fixed point of contact in each team throughout the build, and hand over at the end with runbooks, documentation and handover sessions. We build so that taking over is possible, even if you initially opt for our managed service.
