92% weekly AI companion engagement boost with Gemini Enterprise Agent Platform
Gemini APIs power a 21.2% catalog discovery surge
Generative AI compute costs slashed 6x on Google Cloud
Cloud SQL unifies vector database with 99.79% uptime
Sub-5.5s response latency achieved across 1.3M+ annual requests
Mindvalley leverages Gemini Enterprise Agent Platform and Cloud SQL to nearly double AI companion engagement.
Mindvalley leverages Gemini Enterprise Agent Platform and Cloud SQL to nearly double AI companion engagement.
Moving past high LLM latency and fragmented databases to scale personal transformation
Mindvalley, a global personal growth platform, set out to reach one billion learners by mapping individual customer intent directly to personal transformation outcomes. Operating a vast library spanning wellness, mind, and entrepreneurship, Mindvalley faced a critical discovery challenge: traditional keyword search and algorithmic feeds were causing choice paralysis. Learners struggled to quickly navigate the expansive catalog to find content tailored to their immediate life goals.
To solve this, Mindvalley initially experimented with third-party LLMs to construct conversational search tools. However, testing exposed severe technical and commercial roadblocks. API latencies stretched between 53 to 60 seconds per response, creating an unacceptable bottleneck for thousands of concurrent global users. Also, operating across fragmented infrastructure—combining external vector databases like Pinecone with disjointed data stores—introduced severe operational complexity, sync failures, and vendor outage risks. Mindvalley needed a unified, enterprise-grade cloud foundation that could deliver rapid AI responses while lowering total cost of ownership to support over 200,000 active users.
Gemini models delivered the latency improvements, context windows, and 6x lower costs we needed to scale customer-facing AI. Google Cloud gives us the unified data foundation to move beyond basic search into real-time, personalized conversational learning.
Swaraj Sunilkumar Dube
Data Science Manager, Mindvalley
Recognizing that baseline infrastructure survival was hindering innovation, Mindvalley expanded its Google Cloud footprint. In combining Gemini model context windows with Google Cloud managed data ecosystem, Mindvalley established a scalable foundation for its next-generation customer-facing AI agents.
Deploying agentic learning assistants and Cloud SQL to drive nearly double weekly AI companion engagement growth
Mindvalley deployed a multi-agent ecosystem driven by Google Cloud: Goals AI for conversational onboarding, EVE for catalog discovery alongside personal growth advice, and the Learning Assistant for in-course tutoring. Since introducing these AI companions, weekly active engagement has nearly doubled to 92%. These solutions leverage Gemini Enterprise Agent Platform and Gemini APIs to convert vague user queries into instant content matches, driving a 21.2% content engagement surge.
Industry focus often centers on the agent layer, but Google Cloud's underlying data infrastructure is the true workhorse. Hosting our vector store and transactional source of truth together on Cloud SQL gives us the reliability needed to serve 200,000 active users effortlessly.
Yashaswi Krishnadev Nayak
Staff Machine Learning Engineer, Mindvalley
To streamline its architecture, Mindvalley migrated its primary vector store and transactional source of truth from third-party vendors to Cloud SQL with PostgreSQL. This unified environment simplified data management, eliminated vendor dependencies, and improved operational stability.
For batch workloads, Mindvalley leverages Google Kubernetes Engine (GKE) to run open-source Gemma 3 models. Every day, GKE processes session history to generate personalized dynamic prompt batches for tens of thousands of active users. Additionally, Mindvalley implemented a ‘Teacher-Student’ evaluation framework on Gemini Enterprise Agent Platform, using Gemini Pro as a ‘teacher’ to continuously benchmark production model outputs against safety, accuracy, and brand personality rubrics.
The transition delivered remarkable operational and economic efficiencies. Response latencies dropped under 5.5 seconds while maintaining 99.79% uptime across 1.3 million annual agent requests. Achieving a 6x reduction in model compute costs provided the predictability to scale its agentic footprint effortlessly without blowing through operational budgets. With a Unified Customer Profile (UCP) in Cloud SQL, Mindvalley is now poised to leverage BigQuery Graph to unlock deeper behavioral insights and fuel its hyper-personalization roadmap.
Mindvalley is a global personal growth platform founded in 2003. It delivers transformative education programs across mind, body, wellness, and entrepreneurship to over 200,000 active learners worldwide.
Industry: Technology
Location: Malaysia
Products: Gemini Enterprise Agent Platform, Gemini APIs, Cloud SQL, Google Kubernetes Engine (GKE), BigQuery, Managed Service for Apache Airflow (formerly Cloud Composer), Cloud Run
