Client at a glance
Advancing User Experience with AI-Powered Insights
Quantive (formerly Gtmhub) is a leading provider of strategy execution software and services, built on the Objectives and Key Results (OKRs) methodology. Their platform helps organizations achieve alignment, enhance visibility, and foster a results-driven culture. Quantive’s platform now offers an enhanced user experience powered by real-time semantic suggestions and predictive analytics. By combining cutting-edge NLP technologies with scalable infrastructure, we empowered Quantive to deliver smarter, faster, and more intuitive interactions that drive customer success.

Challenge
As digitalization drives innovation at unprecedented speeds, Quantive faced the challenge of optimizing its product to offer personalized and seamless user experiences. Specifically, they sought to:
- Deliver customized recommendations for OKR creation and management, alleviating the complexity of self-service workflows.
- Streamline navigation to Insights, ensuring users could quickly access the most relevant information.
- Boost customer satisfaction by automating form fill-ins and improving usability.
Our Approach
To address these needs, we collaborated with Quantive to deliver a data-driven solution that leverages advanced machine learning and natural language processing (NLP) technologies.
Key actions included:
- Data Infrastructure:
- Developed a PostgreSQL database connected to an automated pipeline in Azure Cloud.
- Integrated Azure Data Lake and Data Factory for sourcing data from MongoDB, later orchestrated through Azure Synapse for scalability.
- NLP Integration:
- Built an LSTM-based neural network using TensorFlow for automatic form fill-ins.
- Deployed a pre-trained Transformer model to generate real-time semantic recommendations for Insights, integrated via gRPC microservices fetching data from a Kafka stream.
- Operationalization of ML Pipelines:
- Automated data science workflows using MLflow, Jenkins, and SonarQube for model training, testing, and deployment.
- Set up Grafana dashboards to monitor real-time service accuracy and performance, ensuring ongoing reliability.
Impact Delivered
- Precision in Automation: Achieved over 95% accuracy in automatic entity recognition and form completion.
- Enhanced Engagement: Significantly boosted customer engagement by providing timely, relevant recommendations.
- Increased Usability: Improved adoption of OKRs and Insights features by streamlining workflows and enhancing user satisfaction.
- Performance Excellence: Delivered a model service with a mean response time of 150 milliseconds per request, seamlessly handling thousands of customer interactions daily.
Expertise and Scope
- Deliverables: NLP-based recommendation system, automated data pipelines, monitoring dashboards
- Technology Stack: Python, TensorFlow, Keras, MLflow, Docker, Jenkins, SonarQube, Azure Data Lake, Azure Data Factory, Azure Synapse, PostgreSQL