Reinvigoration eLearning – AI-Powered Learning Automation

Client: Reinvigoration – A leading enterprise learning and operational excellence platformIndustry: eLearning, Workforce DevelopmentLocation: United KingdomProject Duration: 8 monthsSolution Delivered: ProcessAI – AI-driven automation engine for personalized learning

“TDCM’s team didn’t just deliver—they revolutionized our approach to online learning!”— Chris Dando, CEO, Reinvigoration

The Challenge

Reinvigoration is an established name in enterprise learning, known for delivering robust training programs across industries such as manufacturing, healthcare, government, and logistics. Their platform was used by thousands of learners—from frontline workers to operational leaders—across multiple continents.

As the company scaled, a key problem emerged: manual inefficiencies were hindering learner engagement and course completion.

Their legacy system, while robust in content, lacked the intelligence to:

• Recommend personalized course pathways

• Track engagement effectively across user segments

• Automate administrative follow-ups (e.g., nudge emails, progress alerts)

• Adapt dynamically to learner performance and preferences
  

With dozens of concurrent learning programs and hundreds of enterprise clients, manual workflows and static recommendations were no longer sustainable. Their Learning & Development (L&D) team was overwhelmed with administrative tasks. Worse, learners were becoming disengaged, as they couldn’t find the right content at the right time.

Reinvigoration needed a smart, scalable, AI-powered system that could not only enhance learner outcomes but reduce the human workload required to make the system function.

That’s when they approached TDCM.ai.

Project Goals

1. Personalize the learning experience for each user using data-driven insights

2. Automate course recommendations based on individual performance, goals, and company training objectives

3. Reduce administrative overhead through intelligent workflows

4. Enable performance analytics for both learners and program administrators

We proposed a solution we had been refining for enterprise platforms like theirs: ProcessAI — a modular automation engine tailored to smart workflows and user engagement.

Our Approach

Phase 1: Strategic Discovery & Data Mapping (Month 1)

We began with a deep-dive discovery process that involved:

• Interviews with L&D managers, platform admins, instructors, and corporate clients

• A complete audit of existing workflows, data structures, and engagement patterns

• Analysis of their LMS backend, CRM integration, and learner behavior over a 12-month period

Insight: While Reinvigoration had rich content, learner journeys were largely linear and generic. Completion rates dipped by 20–40% halfway through multi-week programs, particularly in self-paced modules.

We also discovered manual friction points:

• Admins had to manually assign next modules

• Follow-ups were template emails sent on fixed schedules, regardless of learner behavior

• Feedback loops (e.g., learner surveys, knowledge checks) weren’t being used dynamically

This confirmed the need for behavior-based automation and AI-enhanced pathways.

Phase 2: System Architecture & AI Model Development (Months 2–4)

We architected a custom implementation of ProcessAI, focused on three pillars:

1. AI-Optimized Learning Journeys

We used a recommendation engine built on collaborative filtering and classification models. By analyzing learner history, content metadata, assessment scores, and peer behavior, the system could:

• Recommend next-best modules

• Suggest enrichment content (videos, case studies, interactive tools)

• Identify “struggling learners” and adapt their learning tempo

Tech used:

• Python, scikit-learn, TensorFlow (for classification models)

• Pandas for data processing, Postgres for storage

• FastAPI to integrate with the LMS backend
  

2. Automation of Engagement Workflows

We implemented behavior-triggered automations to replace manual interventions. Some examples:

• If a user didn’t complete a module in 3 days → send a reminder with a motivational nudge

• If a user scored <60% on a quiz → recommend a recap module before allowing progression

• If engagement dropped by >40% over a week → flag them for manager review
  

Tools used:

• ProcessAI’s internal orchestration logic (built on Apache Airflow)

• Integration with SendGrid for automated messaging

• Custom dashboard for rule editing and A/B testing of triggers
  

3. Real-Time Performance Dashboards

We developed role-based dashboards for:

• Learners: Progress, personalized recommendations, AI learning tips

• Instructors: Class-wide analytics, outlier detection

• Admins: Workflow efficiency, learner satisfaction trends, automation effectiveness
  

This allowed the client’s team to understand what was working, iterate fast, and deploy changes without waiting for IT.

Phase 3: Pilot & Iteration (Months 5–6)

We ran a two-month pilot with three enterprise clients in different industries:

• A global logistics firm

• A healthcare operations provider

• A local government training agency
  

What we learned:

• Learners responded positively to the nudges—particularly when messaging felt contextual.

• Managers loved having early warnings about disengaged users.

• The AI needed to be fine-tuned to avoid overwhelming users with too many simultaneous recommendations.
  

We rapidly adjusted the recommendation model, improved message pacing, and added controls for learners to “snooze” suggestions when overwhelmed

Phase 4: Full Deployment & Training (Months 7–8)

We rolled out ProcessAI across the full platform—over 14,000 users globally.

Our team conducted:

• Onboarding sessions for 30+ admins

• Playbooks and training videos for client managers

• Weekly standups with Reinvigoration’s L&D and product teams

We also provided a 6-month roadmap for further AI enhancements, including microcredentialing, multilingual content adaptation, and sentiment analysis from learner feedback.

Results

Within three months of full rollout, the impact was clear:

✅ Course completion rates increased by 35%Users were more likely to finish programs, especially in self-paced and hybrid formats.

✅ Manual admin workload dropped by 50%What previously required 2–3 full-time staff (assigning, reminding, tracking) could now be done with one part-time administrator monitoring the automation dashboard.

✅ Learner experience scores improved across the boardFrom surveys and app feedback, users appreciated the “smart” feel of the new experience—especially the recommendations and check-in messages.

Team and Culture

Our core delivery team included:

• 2 AI engineers

• 1 learning experience (Lx) strategist

• 1 automation architect

• 2 full-stack developers

• 1 dedicated project lead
  

Reinvigoration’s openness to co-creation made a huge difference. Their CEO, Chris Dando, was highly engaged and visionary, pushing for innovation but balancing user empathy. Their L&D team provided invaluable insight, allowing us to fine-tune the system iteratively.

We held biweekly design reviews and a shared Slack channel, creating a rhythm of mutual accountability and fast feedback loops.

Challenges & Lessons Learned

• Data quality issues: Historical data was fragmented across several systems. We spent 3 weeks cleaning and unifying it before modeling could begin.

• Change resistance: Some instructors were hesitant about losing manual control. We responded with clear analytics showing how AI helped—not replaced—their pedagogy.

• Model trust: Transparency in how recommendations were generated helped increase adoption. We provided confidence scores and explanatory labels (“Suggested based on your recent quiz score”).
  

What’s Next

Reinvigoration is now planning to expand ProcessAI to support:

• Certification pathway mapping

• Gamified learning based on predicted learner types

• Voice and chatbot integrations for hands-free learner interaction

Together, we proved that AI can humanize digital learning—by making it smarter, more relevant, and less administratively burdensome.

We’re proud to be helping Reinvigoration reimagine what’s possible in the future of enterprise education.

📢 "TDCM’s team didn’t just deliver—they revolutionized our approach to online learning!" – Chris Dando, CEO, Reinvigoration

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