Discover how Salesforce optimized retrieval performance, enhanced AI accuracy, and built a secure, scalable, and highly available system.| Salesforce Engineering Blog
Discover how Salesforce optimized metadata interpretation and AI accuracy, reducing execution time from 10 minutes to just 10 seconds.| Salesforce Engineering Blog
Explore Einstein's team's initial LLM latency challenges, their selection of Amazon SageMaker, and the resulting performance gains.| Salesforce Engineering Blog
Learn how Salesforce reduced AI infrastructure costs, and improved GPU utilization across various AI workloads, and much more.| Salesforce Engineering Blog
Learn how Salesforce tackles challenges like balancing throughput and latency, ensuring secure AI deployments with AWS SageMaker, and more.| Salesforce Engineering Blog
Learn how Salesforce tackled GPU onboarding delays, integrated Bedrock, and addressed key reliability and security issues.| Salesforce Engineering Blog
Learn how Salesforce's new similarity model identifies incident commonalities, preventing alert overload and facilitating effective resolution processes.| Salesforce Engineering Blog
Explore Zero Copy, which transforms how Salesforce interacts with external data, enabling real-time analysis without the need for data migration.| Salesforce Engineering Blog
Learn how Salesforce scales their systems to handle billions of records and optimizes data retrieval speeds to provide fast lookups.| Salesforce Engineering Blog
Learn how Salesforce developed an AI-powered Test Failure (TF) Triage Agent, transforming how developers manage test failures.| Salesforce Engineering Blog
Learn how Salesforce created scalable modular AI agent architecture that transformed a six-year manual effort into a nine-month project.| Salesforce Engineering Blog
Learn how Salesforce tackled legacy architectural constraints, reengineering the Lakehouse to support 4 million Iceberg tables, 50 petabytes of data.| Salesforce Engineering Blog
Learn how Salesforce's Data Cloud team revolutionized indexing to bypass ElasticSearch limitations, introduced a dual-phase fuzzy matching system, and more.| Salesforce Engineering Blog
Learn how Salesforce tackled the challenges of scaling AI agents, implementing modular updates without disrupting functionality, and more.| Salesforce Engineering Blog
Discover how Agentforce combines agentic AI, multi-agent collaboration, and real-time observability to drive 1B predictions daily at enterprise scale.| Salesforce Engineering Blog
Learn how Salesforce tackled the complexities of reasoning across highly customized orgs, addressed latency and scalability issues, and more.| Salesforce Engineering Blog
How the Data Spaces team built structured security for 300,000 orgs, solved complex scaling challenges, and enforced cross-platform data governance.| Salesforce Engineering Blog
Discover how Salesforce reengineered Data Cloud to support Agentforce, AI grounding, and real-time activation across 100K tenants and 1,000+ domains.| Salesforce Engineering Blog
Learn how Data Cloud Engineering handles challenges in managing unstructured data, from processing multiple data formats to resolving scalability concerns.| Salesforce Engineering Blog
Explore Salesforce Engineering's CodeGenie, an internal IDE tool that boosts productivity by supporting multiple languages.| Salesforce Engineering Blog
Discover how Agentforce was engineered to orchestrate modular, multi-model AI agents for safe, scalable deployment in enterprise environments.| Salesforce Engineering Blog
Discover how Salesforce created dynamic retrieval systems that balance precision and speed by adjusting query complexity and much more.| Salesforce Engineering Blog
Discover how the Hyperforce team managed the Hyperforce migration and integrated AI to enhance performance, UX, and incident prevention.| Salesforce Engineering Blog
Learn how Salesforce's cross-cloud Scrum team built Einstein for Flow, a game-changing AI product that revolutionizes Salesforce workflow automation.| Salesforce Engineering Blog