Reactiv built an AI Scheduler for Shopify merchants that automates native iOS and Android app updates using Amazon Bedrock AgentCore. It reduced merchant configuration time by 80 percent and cut time to production by 33 percent. By unifying interactive and scheduled agents on one AgentCore stack with shared memory, tools, and UI protocol, Reactiv enabled bidirectional learning so scheduled updates get better as merchants use the dashboard.
Amazon SageMaker AI Inference Recommendations adds concurrency sweeps to benchmark generative AI endpoints by sending controlled simultaneous requests and measuring throughput and latency to find the saturation point. In the walkthrough, the endpoint’s throughput-to-latency “knee” appears at 256 concurrent requests. Teams can use the results to right-size instance type and serving configuration (and optionally run an SLA-based search) to automate capacity planning and avoid over- or under-provisioning.
Tata Elxsi built IRIS, a real-time industrial safety platform on AWS that analyzes camera feeds at the edge, runs computer-vision models in the cloud, correlates detections, and triggers automated alerts. Its measured event-ingestion latency is under 200 milliseconds at p95. This shifts safety monitoring from recorded footage and 15–45 minute detections to continuous, near-real-time alerting without streaming raw video to the cloud.
Salesforce Agentforce for Public Sector is being extended to process unstructured evidence by storing files in Amazon S3, running Amazon Bedrock Data Automation, and exposing extracted results back to users through MCP in the Salesforce console. The integration triggers processing via S3 event notifications and uses DynamoDB and Lambda, including a second Lambda step that saves outputs to a dedicated S3 output bucket. This shifts evidence handling from manual review and extraction to automated, event-driven multimodal processing with natural-language retrieval from Salesforce.
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