New Way Now: How Telmai is building a new way to help companies build trust in their data

Telmai is a data observability company that leverages AI to enable enterprise data teams to monitor and automate data quality across the entire data pipeline, from source to consumption. In this interview, Telmai's CEO and co-founder Mona Rakibe explains the top three generative AI use cases her organization focuses on. These include enabling their customers to achieve better generative AI outcomes through high-quality data, expanding Telmai's product feature capabilities with GenAI, and making their internal processes faster and more cost-efficient. Since day one, Telmai has been using Google Cloud to accelerate its digital transformation. They started by setting up their first email account on Workspace and then built their product prototype using BigQuery and Google Kubernetes Engine (GKE). They were able to validate their prototype rapidly in the market. Telmai is now exploring Vertex AI for generative AI use cases. Additionally, Telmai is using Google Cloud products such as Dataproc, Pub/Sub, Looker, and GCS to process high-volume and high-velocity data for DQ analysis and anomaly detection ML models. "We continue to piggyback on Google so we can focus on what is core to our business, and GCP can take care of the rest," Rakibe says. "All of these architectural decisions are paying its dividends." This interview was filmed live at Transform Studio at Google Cloud Next ’23. Join us at the next Transform Studio to feature your organization’s transformation with Google Cloud. Reach out to customerref@google.com. ____________________________________ Learn more: How AI can improve data quality and observability for startups and enterprises → https://cloud.google.com/blog/topics/partners/ai-benefits-for-startups-and-enterprises Telmai Partners with Google Cloud to Bring ML-Driven Anomaly Detection and Data Quality Monitoring to BigQuery → https://www.telm.ai/blog/telmai-partners-with-google-cloud-to-bring-ml-driven-anomaly-detection-and-data-quality-monitoring-t