MUCHBETTER.AI | Complete Company & Product Documentation | June 2026

MUCHBETTER.AI

Complete Documentation

• Product • Business Model • Technology • Market • Case Studies
• Version 2.0 | June 2026 | Based on Official FY27 Pitch Deck + Public Sources
• Confidential — For Internal Use Only | Source: Official Pitch Deck + Public Data

1. Executive Summary

Muchbetter.ai is a French B2B SaaS startup founded in Paris in 2023. It is the leading AI-powered sales training simulation platform for revenue and field teams. The platform enables enterprises to create ultra-realistic, AI-driven conversational simulations where sales reps practice with virtual customers, receive real-time expert coaching, and develop measurable skills — at any scale.

The company was built on a clear insight: 85% of corporate training spending has no impact on performance (Rain Group, 2024). Traditional e-learning, periodic coaching, and classroom training fail because they don't create behavioral change. Muchbetter.ai solves this through active repetition — combining cognitive science (Ebbinghaus Forgetting Curve) with AI to make skill practice continuous, personalized, and measurable.

Headquartered at 1 rue de Metz, Paris 75010. Backed by €4M+ seed funding (Educapital, Antler, Astorya.vc). The platform serves 40+ enterprise clients across France, Switzerland, Germany, and the US — including AXA, BNP Paribas, Bouygues Telecom, Boulanger, Orange, SFR, Schneider Electric, and Philips Healthcare.

• 35,000+ Active Users: sales reps & advisors on the platform
• 320,000+ Simulations Done: AI roleplays completed to date
• 4.9/5 G2 Rating: globally trusted by enterprises
• x2.3 Conversion Uplift: Bouygues Telecom cybersecurity offer
• +38% Sales per Hour: Boulanger — €12M revenue impact
• 61 NPS: Customer NPS across 17 languages, EU-hosted

2. Company Overview

2.1 Company Snapshot

2.2 Mission & Vision

• Mission: "We turn revenue teams from good to great through structured practice, measurable skills, and continuous improvement."
• North Star metric: Correlation between competency progression and business performance. The company's ultimate proof point is that skill development on the platform directly drives revenue outcomes — not just test scores.
• Market problem: 85% of professional training spending has no impact on performance (Rain Group, 2024). The Ebbinghaus Forgetting Curve shows that without active repetition, knowledge decays to near-zero within 60 days. Muchbetter.ai directly counters this with spaced repetition and deliberate practice embedded in a continuous training loop.

2.3 Team

The company was founded through Antler's Paris cohort (2023) and has grown to 30+ employees in under 3 years.

2.4 Investors & Advisors

3. Product Deep Dive

3.1 The Training Loop — Learn · Train · Coach · Measure

The platform is built around a four-stage structured training system. All four stages are AI-powered and form a continuous loop:

3.2 A Typical Program — 3 Phases

A standard Muchbetter.ai deployment follows three structured phases (Kirkpatrick model extended):

3.3 AI Simulation Engine

Voice-to-voice simulation: The core technology. Sales reps speak to a virtual customer persona (audio) and receive spoken responses. The AI persona maintains character consistency throughout, adapting tone, objections, and information based on the defined DISC behavioral profile and difficulty level.

• Multiple simulation types: complex sales, B2B/B2C prospecting, account management, retail sales, luxury retail, customer service, manager coaching (feedback, difficult conversations)
• Progressive difficulty — scenarios increase in complexity as reps improve
• DISC behavioral profiles on AI personas — virtual customers can be Dominant, Influential, Steady, or Conscientious

1. LEARN: Interactive courses and AI-generated quizzes for knowledge acquisition and certification. Self-paced (15 min courses, ~15 min quizzes). Users establish a baseline self-assessment (10 min).
2. TRAIN: AI conversational simulations — the core of the platform. Reps roleplay with a virtual customer persona in voice or text. Real-time evaluation and expertise analysis happen during and after each session (~90 min of immersive practice).
3. COACH: Continuous retraining and managerial coaching support. AI generates coaching recommendations for managers. Manager debriefs (30 min). Refinement sessions on specific skill gaps (10 min).
4. MEASURE: AI skills mapping. Individual and team performance dashboards. Before/after progression analysis. Business KPI correlation. NPS and CSAT tracking.

Phase 1: Know & Certify: Self-assessment (10 min) → Interactive course (15 min) → Certification quiz (15 min). Goal: establish knowledge baseline.

Phase 2: Practice: Roleplay simulations on representative real-world scenarios (~90 min of practice across multiple sessions). Goal: anchor behavioral reflexes across all customer profiles.

Phase 3: Coach: Refinement on specific gaps (10 min) → Manager debrief of simulations (30 min) → Final self-assessment measuring progression (10 min). Goal: measurable improvement and managerial alignment.

• Random persona mode — challenge reps with unpredictable customer types
• Real-time evaluation — scoring happens during the conversation, not just at the end
• Full transcript + audio replay available post-session

AI Coaching Engine

After each simulation, the coaching module delivers detailed, actionable feedback:

• Expertise analysis — gap detection between rep's discourse and the internal knowledge base
• Methodology scoring — adherence to chosen sales framework (SPIN, MEDDIC, BANT, etc.)
• Speech analysis — talk-time percentage, speech rate, filler

Word Detection

• Open/closed question analysis — conversational quality assessment
• Discourse positivity analysis — tone and sentiment evaluation
• Automated expertise mastery score against company's regulatory framework
• Personalized coaching recommendations and next-action suggestions

Skills Intelligence & Mapping

The Measure module aggregates all simulation results into a live skills graph:

• Individual competency radar — multi-dimensional skill profile per rep (Introduction, Discovery, Expertise, Objection Handling, Argumentation, Conclusion)
• Team heatmaps — performance by skill, by team, by evaluation criteria
• Baseline vs. endpoint analysis — measurable progression from start to finish of a program
• Manager coaching zone — AI identifies each rep's priority improvement area with concrete coaching actions
• Performance evolution charts — weekly simulation cadence tracking

AI Scenario Builder — 4 Ways to Create

The platform's content creation workflow eliminates the typical weeks-long scenario authoring cycle:

• What is auto-generated: realistic scenarios and dialogue, customer personas including DISC profiles, quiz questions and evaluation criteria, debrief and coaching prompts.
• From documents: Upload PDFs, slide decks, or playbooks — AI auto-generates scenarios, personas, quizzes, and evaluation criteria.
• From a URL: Paste a product page or support doc — AI ingests and builds training content automatically.
• From templates: Ready-to-use scenario library covering banking, insurance, telecom, retail, and more.
• From your KB: Centralized internal knowledge base — all content draws from company-specific documentation.

Result: First program live in under 30 minutes
17 languages · SCORM & video ready · 4 admin roles
Confidential — For Internal Use Only | Source: Official Pitch Deck + Public Data

Full Feature List

Conversational Formats

• Complex sales simulations
• B2B and B2C prospecting simulations
• Account management simulations
• Retail sales simulations (including luxury)
• Customer service / relationship simulations
• Standard evaluation-oriented quizzes
• Certification quizzes
• Pedagogical learning quizzes
• Guided learning with virtual coach
• Free learning with virtual coach
• Manager simulations: employee feedback, coaching, difficult conversations

User Skills & Assessment

• Detailed auto-evaluation post-simulation
• Detailed auto-evaluation post-quiz
• Full post-learning debrief
• Recommendations and next actions
• Talk-time % and speech rate analysis
• Open/closed question analysis
• Filler word (language crutch) detection
• Discourse positivity analysis

Dashboards & Metrics

• Personalized user dashboard
• Complete activity/evaluation history
• Audio and transcript access
• Strengths synthesis
• Improvement areas and recommendations
• Competency mapping
• Performance evolution analysis
• Average/skill/criteria performance by team
• Baseline and endpoint analysis
• Email notifications — weekly usage dashboard
• Skills report email notifications

Gamification & Engagement

• Mission-based learning paths
• Progressive difficulty pathways
• Badges and rewards
• Leaderboards and rankings
• DISC behavioral customer profiles
• Random persona mode
• Campaign launch email notifications
• Objective reminder notifications

Expertise & Compliance

• Automatic expertise evaluation
• Gap detection vs. internal knowledge base
• Regulatory framework integration in evaluation
  Confidential — For Internal Use Only | Source: Official Pitch Deck + Public Data

Admin & IT

• 4 user roles with granular access
• Unlimited hierarchical levels
• Manager validation of learning paths
• Activation tracking across 3 levels
• Employee activation and progress tracking
• Filters by path / team / user
• Access to individual performance, history, and profiles
• Written debrief per user
• Pending debrief notifications

Deployment & Integrations

• Template library: all industries
• Auto-generation of scenarios, quizzes, and personas
• Generation from URL, documents, or templates
• Content tagging and categorization
• Video and SCORM integration within learning paths
• Centralized business knowledge base
• Platform available in 17 languages
• Full white-labeling of learner UI
• Custom evaluation criteria and scoring
• SSO (OIDC / SAML, client's choice)
• Secure API for data export
• LMS and data lake integration
• Advanced / custom analytics dashboards
• NPS and post-activity CSAT tracking
  Confidential — For Internal Use Only | Source: Official Pitch Deck + Public Data

Business Model & Pricing

Pricing Tiers (Official — from FY27 Pitch Deck)

Three annual license tiers, billed per user per year. Base pricing shown for 30 users — volume discounts apply at scale.

Standard Support: 24/7 email support. SLO: 2 business days. Included in all tiers.
Premium Support: 24/7 email, phone, and SMS. SLA: 24h or same-day response + priority handling.
Professional Services: Onboarding, co-construction of scenarios, and post-implementation support. Available as add-on.

Implementation Timeline — 3 Months to ROI

A typical deployment follows a 10-week cycle from kick-off to ROI measurement:

• Week -6 (Kick-off): Scope definition, KPI setting, project governance, SMART objective formalization
• Resource commitment: Project team: ~1–2 days preparation + 1–2 days POC facilitation per person. End users: ~30 min/week. Managers: ~30 min/week.

ROI Measurement Methodology

The company applies 3 rigorous methodological principles to ensure credible ROI measurement:

• The platform applies the Kirkpatrick model across 4 levels:
  • L1 Reaction (NPS + satisfaction)
  • L2 Learning (score progression on platform)
  • L3 Behavior (manager field observations)
  • L4 Results (measurable business impact)

Content Requirements for Program Creation

To build a customized training program, clients provide 5 categories of input:

• Week -4 (Platform Onboarding): V1 learning path presentation, admin training, scenario co-construction
• Week -2 (Final Validation): Launch preparation, final sign-off
• Week 0 (Launch): Kick-off with managers and users
• Weeks 1–5 (POC): Weekly 30-min check-ins; bi-weekly with managers
• Week 6 (Mid-pilot review): Performance, usage, and adoption assessment
• Week 10 (Project close): Full REX presentation + ROI measurement

SMART Objectives: Specific, Measurable, Achievable, Relevant, Time-bound. Example: monthly conversion rate on a specific service offer.
A/B Test: One group with Muchbetter.ai vs. equivalent control group. Example: 50 reps with the platform vs. 50 without, matched on seniority and prior performance.
Trend Analysis: Dynamic measurement over time, not a point-in-time snapshot. Example: comparison over 2 months before pilot vs. 2 months after launch.

1. Conversation contexts: Representative call recordings (successful and failed), business context for discussions, target situation typology
2. Pe

MUCHBETTER.AI | Complete Company & Product Documentation | June 2026

5. Technology & Security

5.1 AI Technology Stack

For the first time publicly disclosed in the FY27 pitch deck, the company revealed its underlying AI technology stack:

5.2 Security Architecture (ISO 27001)

Security is embedded from architecture design, not added as an afterthought. All client environments are isolated; data is never pooled or reused for third-party model training.

Governance & Standards

• ISMS compliant with ISO/IEC 27001:2022
• Designated RSSI (Security Officer): Antoine Grenard
• Clear governance structure with defined responsibilities

Data Protection & Encryption

• Systematic encryption of all entrusted data
• At rest: AES-256 encryption
• In transit: TLS 1.2+ encryption
• Multi-tenant architecture with strict client isolation

Access Control & Authentication

• RBAC (Role-Based Access Control) policy
• Federated SSO authentication (majority of enterprise clients)
• Supported standards: OIDC / SAML (client's choice)
• 4 user roles with granular permissions

Business Continuity

• RTO: 48 hours | RPO: 24 hours | Semi-annual testing
• Active vulnerability monitoring: patch management + rapid remediation
• Vulnerability detection: SonarCloud + GitHub integration

5.3 GDPR Compliance

• Generative AI: Azure OpenAI — GPT-4.1 and GPT-5.1 for conversational simulation and coaching generation
• Speech-to-Text (STT): Azure Speech Services — real-time transcription of user speech during simulations
• Text-to-Speech (TTS): Azure Speech Services + ElevenLabs — high-quality AI voice for virtual customer personas
• Infrastructure: 100% hosted in Europe (EU sovereign cloud) — no data transfer outside EU
• Security scanning: SonarCloud + GitHub vulnerability detection — systematic code review
• OWASP compliance: Security best practices (OWASP / CWE) + systematic code reviews
• Roles: Muchbetter.ai = Data Processor. Client = Data Controller.
• DPO: Antoine Grenard (CTO) — reachable during business hours

5.4 EU AI Act Compliance

• Data location: Personal data processed exclusively within the EU. Zero cross-border transfers.
• Purpose limitation: Data (including anonymized) used exclusively for service delivery. No client data used to train AI models.
• Retention: Configurable per client. Secure/irreversible deletion at contract end or on request. Default recommendation: 6-month retention.
• Rights management: Full support for DPIA (Data Protection Impact Assessment), GDPR request handling
• Risk level: Limited risk — conversational training and simulation tool. NOT high-risk under AI Act taxonomy.
• Permitted use: Exclusively for learning and pedagogical feedback. Contractually prohibited from being used for formal HR performance evaluation.
• Biometric data: No biometric data analysis. Camera used only for video feedback purposes — not stored, transmitted, or analyzed.
• AI transparency: Disclosed AI models: Azure OpenAI (GPT-4.1, GPT-5.1) for generative AI; Azure Speech + ElevenLabs for STT/TTS.
• AI lifecycle: Secured AI system lifecycle management. Compliance with ANSSI (French national cybersecurity agency) recommendations.
• Principles: No social scoring, no automated HR decision-making, no sensitive profiling. Human remains central to the process.

6. Customer Success Stories

6.1 Boulanger — Retail, Insurance Upsell

• Industry: Retail / Consumer Electronics
• Objective: Boost in-store sales of insurance services
• Scope: Pilot in a French region (Dec 2024 – Feb 2025) → National rollout Sept 2025: 2,800 salespeople
• Sponsors: Sales, HR, and General Management
• Result: +38% insurance sales/hour WITH Muchbetter.ai vs. +10.5% in control stores (without)
• Impact: €12 million revenue impact at scale
• Quote: "The old-timers went back to basics. For the newbies, it gave them a real framework and helped them learn faster than face-to-face training." — Manager, Boulanger pilot store

6.2 Bouygues Telecom — Telecom, Cybersecurity Offer

• Industry: Telecom
• Scope: 8,000 B2C advisors already using platform. B2B SMB team tested on new cybersecurity offering (50% of team).
• Context: High technical expertise required + consultative selling environment
• Result: x2.3 increase in cybersecurity offer orders (treatment vs. control group, July 2025 pilot)
• Scale: National rollout from September 2025 | 8,000 users | 17 languages
• Quote: "It's a platform widely embraced by both frontline teams and managers, with strong demand to continue developing scenarios and learning paths." — Head of Support and Training, Bouygues Telecom

6.3 BNP Paribas Personal Finance — Finance

• Industry: Banking / Consumer Finance
• Scope: Pilot: customer service team + B2C sales team (50 people, October 2025)
• Objective: Boost sales conversions on incoming calls; boost credit repurchasing
• Result: 102% of targets achieved WITH platform vs. 51% WITHOUT (September vs. October/November 2025)
• NPS: 61 NPS — strong team engagement and enthusiasm
• Quote: "In addition to saving time and increasing autonomy, what's really positive is that it has created an overall dynamic of desire to perform — and healthy competition within the team." — Customer service manager

6.4 La Poste Solutions Business — B2B Services

• Industry: Postal / B2B Services
• Scope: Pilot end 2024 → 300 advisors by March 2025 (2,500 simulations since launch)
• Objective: Promote commercial recovery on secondary offers during incoming calls
• ROI: Manager time savings: from 2 hours of call listening to 45 minutes of coaching per week (-60%)
• Next step: Responding to tender for extension to entire group: 22,000 employees
• Quote: "This is a tool I would have loved to have had when I was in charge of telesales. Our advisors are more comfortable with follow-ups, and our managers save a considerable amount of time on double listening." — Director of the Sales School, La Poste

6.5 Philips Healthcare — Healthcare/Medtech

• Industry: Healthcare / Life Science
• Objective: Transform product detailers into trusted advisors; compliance-grade simulation
• Result: +105% methodology mastery — discovery skill progression measured on platform

6.6 Industry Expertise Summary

• Telecom: 8,000+ advisors trained. Clients: Bouygues Telecom, Orange, SFR, Paritel. Pain: consistent pitch & compliance at scale.
• Retail: €12M+ revenue impact documented. Clients: Boulanger, Leroy Merlin, MARS, Groupe Pomona. Pain: closing gap between top reps and average.
• Banking: 300 → 22,000 advisor trajectory at La Poste. Clients: BNP Paribas, La Banque Postale. Pain: commercial recovery on incoming calls.
• Insurance: +38% sales/hour documented. Clients: AXA, Allianz, CNP, AG2R La Mondiale. Pain: boost conversions in regulated environments.

Muchbetter.ai | Complete Company & Product Documentation | June 2026

7. Market Context & Product Vision

7.1 Market Problem

The company grounds its positioning in two powerful data points:

• 85% of professional training spending has no impact on performance (Rain Group, 2024)
• Without active repetition, the Ebbinghaus Forgetting Curve shows knowledge retention falls to near-zero within 60 days

The implication: traditional e-learning, videos, and periodic coaching are structurally insufficient to change behavior. Only spaced repetition with realistic practice produces lasting skill change.

Muchbetter.ai's benchmark data (from anonymized platform data across sectors) shows:

• Methodology proficiency reaches ~90% mastery after approximately 10–15 repetitions
• Expertise mastery reaches ~90% after approximately 5–8 repetitions

7.2 Product Roadmap — 2026

The FY27 deck disclosed a quarterly 2026 product roadmap across 4 seasonal releases:

7.3 Competitive Positioning

Muchbetter.ai positions itself as the European leader in AI sales simulation, with 5 key differentiators:

• Voice-to-voice AI simulation — audio-first, not just text chat, with ElevenLabs-quality TTS personas
• 100% client customization — scenarios built from the client's own documents, methodology, and compliance rules in under 30 minutes
• European data sovereignty — ISO 27001, GDPR, EU AI Act compliant, 100% EU-hosted (Azure)
• Manager analytics loop — not just training for reps, but a coaching intelligence layer for managers
• Vertical depth and proven ROI — documented case studies with hard revenue numbers (€12M, x2.3 orders, 102% targets)

8. Support Model

8.1 Premium Support Framework

• Spring 2026 (Q1): Complete, gamified & ultra-realistic: Realism & conversation dynamics | Gamification & engagement | 360° training loop & retraining
• Summer 2026 (Q2): Linking skills and performance: Competency mapping | Structured knowledge hub | Connected ecosystem (CRM, LMS integration)
• Fall 2026 (Q3): Adaptive & grounded in real practice: Adaptive learning | Real customer conversations (face-to-face, video) | Behavioral intelligence (incl. non-verbal)
• Winter 2026 (Q4): Collaborative & immersive: Collective best-practice sharing | Manager Copilot | Immersive avatar learning

Pedagogical Expertise

• Custom design support, data piloting, best-practice sharing (Kirkpatrick methodology, spaced repetition, optimal repetition counts)

Enterprise Experience

• 35+ major enterprise clients, 350,000+ simulations analyzed, proven managerial best practices, sector benchmarks

Proactive Team

• Dedicated Account Manager (reachable anytime), structured follow-up rituals, Intercom in-platform support (May 2026), client-first culture

Evolving Platform

• Active listening to field and manager needs, co-construction (e.g., manager dashboard built from client feedback), roadmap informed by client returns, continuous deployment

9. Key Facts Reference

9.1 Key People

• Renaud Gravelle: Head of Sales — renaud.gravelle@muchbetter.ai
• Antoine Grenard: CTO, RSSI, DPO
• Octave Coulon: Account Manager
• Ying Dong: Contact (per thank-you slide) — ying.dong@muchbetter.ai
• Romain Mazeries: Strategic Advisor (Former Founder, Mangopay)

9.2 Full Client List by Sector

• Finance & Insurance: AXA, CNP Assurances, AG2R La Mondiale, BNP Paribas Personal Finance, UFF (Banque Conseil en Gestion de Patrimoine), Allianz
• Industry & B2B: Schneider Electric, Kiloutou, Würth, CFAO (Technology & Energy), EDF, Enedis, SCC, Selectra
• Retail & Distribution: Boulanger, Leroy Merlin, Groupe Pomona, MARS, KB (Kronenbourg Brasseries)
• Telecom: Bouygues Telecom, Orange, SFR, Paritel
• Healthcare & Pharma: Philips Healthcare, La Poste Santé & Autonomie
• Other: Concentrix, Sodexo, La Banque Postale, Danone, Pomona

9.3 Key Metrics Summary

• Active users: 35,000+
• Total simulations: 320,000+
• Enterprise accounts: 40+
• G2 rating: 4.9/5
• NPS (platform users): 61
• Languages: 17
• Geographies: France, Switzerland, Germany, United States
• Total funding: €4M+ (Seed, November 2025)
• Investors: Educapital (lead), Antler, Astorya.vc, Microsoft France, Business Angels
• Employees: 30+
• Founded: 2023, Paris
• ISO certification: ISO/IEC 27001:2022
• Compliance: GDPR compliant, EU AI Act compliant
• AI models used: Azure OpenAI GPT-4.1 & GPT-5.1 / Azure Speech / ElevenLabs

Document compiled June 2026. Primary source: Muchbetter.ai official FY27 pitch deck (April 2, 2026). Supplemented by public data from G2, Tech.eu, PitchBook, and the company website.