As part of their mission to scale digital coaching experiences, without the in-house bandwidth or infrastructure to support such ambition, they turned to our data engineers for help. In the process, they shared these challenges:
The organization lacked an AI foundation that could replicate coaching conversations with the empathy, tone, and flow of live, human sessions, without feeling robotic or generic.
Existing coaching content was dispersed across formats and channels, limiting its digital adaptability and reach, and making it hard to deliver consistent experiences to learners.
There was no clear way to track how users were engaging with the sessions, what content worked best, or how well the AI was performing, making content optimization nearly impossible.
To support their multilingual learner base, they needed natural language capabilities in both English and Arabic, along with real-time translation and culturally relevant tone adaptation.
The internal team struggled with the absence of a centralized dashboard to manage content updates, oversee AI performance, and analyze user-level insights in one place.
To help the client with their challenges, we proposed to build a scalable, AI coaching platform that mimicked the nuance of live sessions, while being accessible, multilingual, and easy to manage.
Our suggested solution used LLMs and the Whisper API to power bilingual conversations (English–Arabic) and was designed for scale, compliance, and internal usability from day one.
We developed context-aware LLM-based models with prompt engineering, capable of generating dynamic coaching responses in both voice and text. This helped maintain the flow, tone, and intent of live sessions, without losing personalization.
To give the client full control, we built a no-code dashboard that lets non-technical users set up sessions, refine AI behavior, and monitor engagement, all from a clean, intuitive interface.
A CMS was integrated to manage training modules, conversation flows, and media files, ensuring consistency, version control, and easy content updates.
We used a containerized architecture and cloud infrastructure to ensure high availability and smooth integration with existing systems. APIs were built to enable plug-and-play use.
The system included real-time usage tracking, full GDPR/CCPA compliance, and automated CI/CD pipelines for streamlined updates and performance monitoring.
Our team conducted hands-on training, delivered detailed SOPs, and ensured the platform was ready for client-led expansion and iteration, without external dependencies.
Deployed on a scalable cloud-native setup using Docker and Kubernetes. REST APIs powered seamless integration across web, mobile, and third-party platforms.
Built using LLMs with custom prompt engineering and the Whisper API for voice input. Models were fine-tuned for bilingual coaching, ensuring accurate tone and cultural relevance.
Delivered a web-based dashboard with role-based access to manage sessions, AI behavior, and training content. The drag-and-drop interface made session setup and updates effortless.
Real-time analytics and heatmaps provided visibility into engagement. GitHub Actions powered CI/CD pipelines, while human-in-the-loop feedback loops helped optimize model performance over time.
Data was encrypted at rest and in transit. The system followed GDPR/CCPA standards, with RBAC and audit logs ensuring secure, traceable access.
With a no-code admin dashboard, the client’s non-technical teams were able to launch and manage AI coaching sessions 65% faster, enabling more agile program delivery.
Automating session delivery and AI-led responses cut down reliance on moderators, resulting in a 70% reduction in manual effort across coaching operations.
AI-personalized interactions led to a 3x increase in user participation and session completion, enhancing the platform’s overall impact and user satisfaction.
LLM-generated responses achieved 85% contextual accuracy, successfully mirroring the tone, nuance, and intent of human-led mentorship.
All-in-all, by combining AI, full-stack engineering, and intuitive design, our team of AI and data engineers helped the client scale a culturally sensitive coaching experience across geographies, creating a way for AI-powered digital learning in the professional development space.
Education & EdTech
Middle East
End to End Project Lifecycle Management
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