Why this comparison is different from the others
There are dozens of comparisons of digital training platforms out there. Most evaluate the same variables: feature depth, learner experience, price, integrations. These criteria measure the ability to produce and deliver content.
But none measure what actually determines ROI: once the learner clicks Complete, what's left in their memory 30 days later? And more recently: can your enterprise AI (Claude, ChatGPT, Copilot, Mistral) run your platform via MCP? These two questions radically change how you should compare tools.
Digital training platform: a tool for creating, delivering and tracking training for employees. Three families structure the French market: classic and frontline LMS (Cornerstone, 360Learning, Rise Up, Beedeez), mobile-learning solutions (LumApps Learning, and historically TeachOnMars), and microlearning platforms (Cards, Sparted).
The science behind choosing a training platform
The forgetting curve: 140 years of replicated results
In 1885, psychologist Hermann Ebbinghaus documented what would become one of the most replicated findings in psychology: retention of information decays exponentially without reactivation. By Day 1: 70% forgotten. By Day 7: 90%. By Day 30: less than 5%. This phenomenon — the forgetting curve — is independent of content quality and learner motivation. It's simply how human memory works.
The spacing effect
The scientific answer to the forgetting curve is called the spacing effect. Several short sessions spread out over time produce significantly better retention than one long session of the same total duration. The meta-analysis by Cepeda et al. (2006), published in Psychological Bulletin across 254 studies and 14,000 participants, confirms retention gains of 200% to 400% with spacing.
The testing effect
Roediger & Karpicke (2006), in Psychological Science, showed that being quizzed on content improves retention more effectively than rereading it. Recall exercises aren't assessment tools: they are the training.
The classic-platform paradox
Classic LMS (Cornerstone, 360Learning, Rise Up) are built around a single-session paradigm: the learner opens the module, consumes it, completes a final assessment. Mobile-first microlearning platforms (Sparted, TeachOnMars, Beedeez) add reminder notifications, but without a real, scientifically grounded anchoring engine. All of these models ignore or underuse the forgetting curve: none has a proprietary adaptive spaced-reactivation engine.
Full comparison: 10 criteria, 3 tool families
| Critère | Plateformes LMS | Solutions mobile-learning | Plateformes microlearning | Cards |
|---|---|---|---|---|
| PÉDAGOGIE ET FORMATS | ||||
| Microlearning natif | ◑ Ajouté en surface | ◑ Selon plateforme | ✓ Cœur de la conception | ✓ Natif |
| App mobile native (iOS & Android) | ◑ Selon plateforme | ✓ Cœur de proposition | ✓ Selon plateforme | ✓ Incluse |
| ANCRAGE ET MESURE D'IMPACT | ||||
| Moteur d'ancrage propriétaire | ✗ Absent | ✗ Notifications uniquement | ◑ Selon plateforme | ✓ Learning Routine® |
| Mesure de rétention long terme | ◑ Complétion principalement | ◑ Engagement principalement | ◑ Selon plateforme | ✓ Via Learning Routine® |
| IA ET PILOTAGE | ||||
| Connecteur MCP avec IA d'entreprise | ✗ | ✗ | ◑ Selon plateforme | ✓ Natif |
| Agents IA spécialisés | ◑ AI Assistant générique | ✗ | ◑ Selon plateforme | ✓ 4 agents IA |
| DÉPLOIEMENT ET COUVERTURE | ||||
| Conformité, certifications, parcours longs | ✓ Force principale | ◑ Selon plateforme | ✗ Hors périmètre | ✗ |
| Multilingue (interface + traduction modules) | ◑ Selon plateforme | ◑ Selon plateforme | ◑ Selon plateforme | ✓ FR/EN + traduction modules |
| Souveraineté UE / RGPD natif | ◑ Selon plateforme | ◑ Selon plateforme | ◑ Selon plateforme | ✓ Français, hors GAFAM |
Legend: ✓ fully present · ◑ partial or varies by platform · ✗ absent or very limited. 2025-2026 data.
Detailed profile of each family
Cards
Cards is a French microlearning platform built around one conviction: delivering content isn't enough if that content doesn't anchor in learners' memory. Cards brings together, in one platform, creation (formats designed 100% for microlearning and mobile, 4 Cards AI agents), multi-channel delivery (web, iOS & Android mobile app, Microsoft Teams, SCORM), the proprietary Learning Routine® anchoring engine, configurable to the pace chosen by the training team, and the MCP connector that lets your enterprise AI (Claude, ChatGPT, Copilot, Mistral, sovereign LLM) run the platform directly. Natively multilingual (FR/EN interface, free built-in module translation), Cards deploys anywhere in the world.
Strengths
- MCP connector — your enterprise AI runs the platform
- Native formats built for microlearning and mobile (iOS and Android included)
- Retention measurement via Learning Routine® at the pace set by the training team
- Natively multilingual: FR/EN interface + free built-in module translation
- EU sovereignty, GDPR-compliant, French
- Native multilingual support, deployable worldwide
- The only platform with a proprietary anchoring engine (Learning Routine®)
Limitations
- Not suited to long-format certifying modules (60+ min)
- No complex administrative LMS features (payroll, OPCO in France)
- No software simulation or virtual reality
- Not a full Digital Workplace solution (collaboration, HR, etc.)
To go further: discover the full Cards platform and the Cards MCP connection in detail.
Classic and frontline LMS
This family covers platforms built for full administrative training management: compliance, certifications, long programs, HR reporting, HRIS integrations. It includes legacy LMS (Cornerstone, for example) as well as newer, more collaborative LMS geared toward peer-to-peer or frontline populations (360Learning, Rise Up, Beedeez). These platforms are the backbone of training in large organizations. Microlearning is present but stays complementary to the historical long-module paradigm.
Strengths
- Complete administrative and compliance management
- Global HR reporting and Qualiopi certifications (France)
- Long, certifying and collaborative (peer-to-peer) programs
- HRIS integrations (Workday, SAP) and frontline population fit
- Maturity on regulatory tracking and internal policy
Limitations
- Microlearning is a complement, not central to the design
- No proprietary scientific anchoring engine in most cases
- Generative AI capability still being built, no MCP connector
- Measurement often limited to completion rather than long-term retention
- High total cost and rollout complexity
Rise Up: a legacy token model
Rise Up bills in tokens, i.e. course sessions purchased in advance. Concrete consequences: if usage spikes, cost climbs beyond the initial package. If usage drops, unused tokens are lost at the end of the period. Your training budget becomes a variable that's hard to plan around.
The Cards model is different: Netflix-per-movie, not tokens. An annual subscription per active user, unlimited training delivered. You pay for the value consumed, not a stock of tokens to burn through before a deadline. Total cost of ownership becomes predictable.
On a 500-employee rollout, moving from a token model to a Cards model smooths out training costs and frees up budget for content production. No more token friction during a seasonal usage spike.
Mobile-learning solutions
This family covers platforms natively built for microlearning: short formats, mobile, a learner experience designed for engagement and repetition. In the French market, the two major players are Cards and Sparted. Sparted favors a heavily gamified approach, particularly adopted by retail chains. Cards favors scientific cognitive anchoring with its Learning Routine® engine, and paves the way for a platform your enterprise AI can drive via MCP.
Strengths
- Native mobile experience (iOS & Android), particularly suited to frontline teams
- Notifications and gamification at the heart of engagement
- Suited to distributed networks, retail and dispersed populations
- LMS capability for some players (Beedeez on the frontline)
Limitations
- Microlearning often managed through notifications, with no proprietary anchoring engine
- Category in flux: some platforms are evolving toward broader LMS
- Generative AI capability and MCP with enterprise AI rarely available
What the Learning Routine® anchoring engine actually changes
Without an anchoring approach, training gets delivered. With Cards Learning Routine®, it anchors. Five measurable differences on the ground versus Rise Up, 360Learning, Cornerstone and Articulate Rise.
- Completion rate as the only indicator
- Long modules, single session, no reactivation
- 70% of content forgotten within 24h, 90% by Day 7
- ROI hard to defend to the executive committee
- No enterprise AI drivability via MCP
- Retention measured per learner at Day 7 and Day 30
- 5-10 min sessions, adaptive spaced reactivation
- 80%+ retained at 30 days on critical topics
- Memory impact you can put a number on, defensible to the exec committee
- Platform drivable by Claude, ChatGPT, Copilot, Mistral via MCP
Decision guide: which family fits which need?
Scientific anchoring and AI drivability
- Onboarding, lasting regulatory compliance, recurring sales training
- Real retention measurement expected by leadership
- Running training from your enterprise AI (Claude, Copilot, Mistral)
- Training ROI to justify to the executive committee with hard numbers
Regulatory compliance, long programs and HR reporting
- Strong regulatory compliance needs (banking, insurance, healthcare, public sector)
- Global HR tracking and critical HRIS integration
- Long programs and Qualiopi certifications as a priority
- 1,000+ employees, mature HR structure
Mobile engagement, gamification or frontline populations
- Strong priority on engagement and gamification
- Mobile-first, native (iOS & Android)
- Gamification and reminder notifications
- Short modules, frontline populations or multi-site retail
Cognitive anchoring: the 4 key mechanisms no other French platform operationalizes
Spaced repetition
Reactivating content at growing intervals consolidates the memory trace. Cepeda et al. (2006) meta-analysis (254 studies, 14,000 participants): +200% to +400% improvement vs. a single session.
Active recall (testing effect)
Roediger & Karpicke (2006): learners tested a week later get +50% retention vs. those who just reread. Quizzes anchor: they don't just assess.
Interleaving
Alternating different types of content during reminders improves retention and transfer. Rohrer et al. (2015) document +43% vs. blocked practice.
Micro-dosing
5-10 minute sessions repeated over time are more effective than a single long session. Cards generates 10 minutes of average engagement per session.
The cost of forgetting
If 70% of content is forgotten by Day 1, memorized value represents less than 30% of your production investment. For a €5,000 module: you pay €5,000, you get €1,500 of real memorized value. The historical benchmark, Bryan Chapman (Brandon Hall Group, 2023), estimated an average of 197 hours (about 28 days) to produce 1 hour of standard e-learning in 2023. With generative AI, that ratio is now outdated: per the 2026 ISTF survey (460 French training professionals), 33% of designers now use AI in their practice (the #1 priority for 30% of training departments, +4 points in one year). Ratios observed in 2026 range between 60 and 100 hours per hour of e-learning, or about 14 days instead of 28. With Cards and Cards AI, design time is no longer solely in the hands of training and communication teams: it's distributed directly to subject-matter experts. In 10 to 45 minutes, an average of 5 microlearning courses are produced, at a consistent level of relevance and quality.
An organization investing €200,000/year in training with no anchoring produces real memory impact of €40,000 to €60,000 at 30 days. The same budget with Cards anchoring: €150,000 to €180,000 of memory impact.
The real question isn't "which platform delivers the best modules?" but "which platform produces training that anchors into teams' daily work for lasting impact?"— Matthieu THOMAS, co-fondateur Cards · Dir. Learning & Devlopment
Three concrete ROI scenarios
Costed scenarios based on real ICP contexts. Public assumptions, 2025-2026 data. Methodology: cost of forgetting = (1 - 30-day retention) × training budget.
Scenario 1: Banking onboarding, 100 new hires per year
French bank, existing Cornerstone LMS, adding Cards as a complement to anchor role-specific onboarding modules (KYC, anti-fraud, ethics).
Scenario 2: GDPR compliance, 500 employees
Mid-size services company, annual GDPR training obligation. Migration from Articulate Rise + legacy LMS to Cards Authoring Tool + Cards Platform.
Scenario 3: Frontline sales force, 1,000 reps
Multi-site retail, choosing between Sparted (gamification) and Cards (cognitive anchoring). The stakes: retaining product pitches 30 days after a launch.
Assumptions: retention with no anchoring 30%, Cards retention 80% (Cards customer measurements, 2025-2026). Details in the full cost-of-forgetting analysis.
Frequently asked questions
Sources and references
- Ebbinghaus, H. (1885). Uber das Gedachtnis. Duncker & Humblot, Leipzig.
- Cepeda, N.J. et al. (2006). Distributed practice in verbal recall tasks. Psychological Bulletin, 132(3), 354-380.
- Roediger, H.L. & Karpicke, J.D. (2006). Test-enhanced learning. Psychological Science, 17(3), 249-255.
- Chapman, B. (2023). How Long Does It Take to Create Learning? Brandon Hall Group Research.
- ISTF (2026). Les chiffres clés du digital learning, 12e édition. Enquête ISTF auprès de 460 professionnels de la formation.
- Taylor, D.H. (2026). L&D Global Sentiment Survey 2026: Into the unknown. donaldhtaylor.co.uk
- Rohrer, D. et al. (2014). The benefit of interleaved practice. Psychonomic Bulletin & Review, 21(5).
- Kapp, K.M. & Defelice, R.A. (2019). Microlearning: Short and Sweet. ATD Press.
