How do you choose a compliance training platform?

Define the obligations the training supports, the roles in scope, and the evidence you must be able to produce, then turn those into requirements. Starting from product demonstrations tends to produce a shortlist of attractive interfaces rather than a platform that answers an auditor's questions.

• Obligations. Which laws, standards, and internal policies does the training support? The mapping guide explains how to build this list.
• Evidence. What must you show, and to whom? For example, Australia's AUSTRAC suggests anti money laundering training records capture what was delivered, including the content and content version, how understanding was assessed, and each person's training history (AUSTRAC).
• Population. Employees, contractors, and third parties; how they are identified; and whether they have corporate accounts.
• Delivery mix. Online modules, face to face sessions, on the job assessment, and attestations all need to be recorded in one place. AUSTRAC notes its own e-learning modules cannot be relied on solely to meet training obligations, which is a reminder that the platform must record more than online completions.
• Constraints. Data location, security classification, integration with HR systems, and budget.

The criteria that matter most are the ones that determine whether you can prove the right people were trained on the right version and could apply it. The table lists criteria, why each matters in regulated settings, and the evidence to request from any provider.

Ask where personal information will be stored and processed, who can access it, how it is protected, and how it will be returned or destroyed at the end of the contract. Training records hold names, roles, results, and sometimes sensitive details from incident based training.

Privacy law governs where training records are stored and who can see them, so check the rules in each jurisdiction where you operate. For example, under the Australian Privacy Principles, APP 8 sets out the steps an entity must take before disclosing personal information overseas, and APP 11 requires reasonable steps to protect personal information and, in certain circumstances, to destroy or de-identify it (OAIC). If the platform includes AI features, the OAIC's guidance on commercially available AI products recommends due diligence on whether the product has been tested for the intended use and who can access information entered into it. Government entities will usually have additional protective security requirements.

Run the selection as a sequence of narrowing steps, each with a documented output, so the final decision can be explained to procurement, audit, and the board.

1. Write requirements. Turn obligations, evidence needs, population, and constraints into must have and should have requirements. Output: a requirements list with weights.
2. Decide the platform category. Decide whether you need a learning management system, a learning experience platform, a content management system, or a combination. Output: a category decision. See LMS vs LXP and LMS vs LCMS.
3. Issue a request for information. Ask providers to respond to the criteria table in writing. Output: comparable written responses.
4. Run scripted demonstrations. Give each shortlisted provider the same script using your own content, roles, and a policy change scenario. Output: scored demonstration results.
5. Complete security and privacy review. Assess data location, access, certifications, and incident handling. Output: a risk assessment for each finalizt.
6. Pilot. Run a real compliance cycle with a representative group, including managers and assessors. Output: pilot findings, including administrator time and learner feedback.
7. Score and decide. Apply the weighted scoring model and record the rationale. Output: a decision paper.
8. Negotiate exit terms. Confirm export formats, timing, and cost before signing. Output: contract clauses for data return and destruction.

Use a weighted scoring model agreed before demonstrations begin, so that scores reflect your priorities rather than the most recent presentation. Score each criterion on a fixed scale against the evidence seen, not claimed.

The main warning signs are answers that describe completion tracking when you asked about competence, and vague answers about data location or export. Both tend to become expensive problems after go live.

• Completion is the only status a record can hold.
• Content updates overwrite the previous version with no history.
• Records cannot be exported in full without a paid service.
• Data location or subprocessors cannot be stated in writing.
• The demonstration cannot use your content or your scenario.
• Accessibility conformance is claimed but no report or test method is available.

See completion tracking vs competency verification for why the first warning sign matters.

Knowledge Foundry sits upstream of delivery platforms: it defines the knowledge framework, obligations, outcomes, and assessment points that training must cover, and connects to existing systems for delivery and records. That means the selection criteria above can be tested against a defined framework rather than against content alone. The integrations page lists how it connects.