{"author":{"name":"Puneeth Komaragiri","slug":"puneeth-komaragiri","article_count":2,"latest_published_at":"2026-06-11T10:45:09.734+00:00","profile_url":"https://vff.ai/authors/puneeth-komaragiri","api_url":"https://vff.ai/api/authors/puneeth-komaragiri"},"articles":[{"slug":"build-an-ai-powered-equipment-repair-assistant-using-amazon-bedrock-agentcore","title":"AWS Bedrock AgentCore Enables AI Equipment Repair Assistant","url":"https://vff.ai/article/2026/06/11/build-an-ai-powered-equipment-repair-assistant-using-amazon-bedrock-agentcore","content_type":"aggregated_news","summary":"AWS published a technical guide on building an AI-powered equipment repair assistant using Amazon Bedrock AgentCore, designed to help farmers and field technicians diagnose heavy machinery problems and access repair procedures through natural language. The solution combines AgentCore Runtime, Amazon Nova 2 Lite, Bedrock Knowledge Base for retrieval-augmented generation, and conversation memory to reduce diagnostic downtime and site visits. The architecture integrates Amazon Cognito for authentication, AWS Amplify for frontend hosting, and indexed manufacturer documentation for semantic search.","published_at":"2026-06-11T10:45:09.734+00:00","updated_at":"2026-06-11T10:45:04.341819+00:00","source":{"url":"https://aws.amazon.com/blogs/machine-learning/build-an-ai-powered-equipment-repair-assistant-using-amazon-bedrock-agentcore/","name":"AWS Machine Learning Blog"},"featured_image":{"url":"https://d2908q01vomqb2.cloudfront.net/f1f836cb4ea6efb2a0b1b99f41ad8b103eff4b59/2026/05/27/ML-18699-7.png","alt":null},"categories":[{"name":"AI Agents","slug":"ai-agents"},{"name":"AI for Business","slug":"ai-for-business"},{"name":"Generative AI","slug":"generative-ai"},{"name":"AWS","slug":"aws"}]},{"slug":"build-an-ai-powered-recruitment-assistant-using-amazon-bedrock","title":"AWS Demonstrates AI Recruitment Assistant Using Bedrock","url":"https://vff.ai/article/2026/05/21/build-an-ai-powered-recruitment-assistant-using-amazon-bedrock","content_type":"aggregated_news","summary":"AWS published a reference architecture for building an AI-powered recruitment assistant using Amazon Bedrock that automates resume parsing, candidate scoring, skill assessment, and interview question generation. The solution addresses a documented problem where recruiters spend an average of 17.7 hours per vacancy on administrative work, with 45% of talent acquisition leaders spending more than half their time on automatable tasks. The system incorporates Amazon Bedrock Guardrails for PII anonymization, bias filtering, and prompt attack detection across a serverless architecture combining Lambda, API Gateway, DynamoDB, and S3.","published_at":"2026-05-21T17:02:22.685+00:00","updated_at":"2026-05-21T17:02:39.422305+00:00","source":{"url":"https://aws.amazon.com/blogs/machine-learning/build-an-ai-powered-recruitment-assistant-using-amazon-bedrock/","name":"AWS Machine Learning Blog"},"featured_image":{"url":"https://d2908q01vomqb2.cloudfront.net/f1f836cb4ea6efb2a0b1b99f41ad8b103eff4b59/2026/04/24/ML-18419-image-1.jpeg","alt":null},"categories":[{"name":"AI Safety & Alignment","slug":"ai-safety-alignment"},{"name":"AI for Business","slug":"ai-for-business"},{"name":"AI Risk & Security","slug":"ai-risk-security"},{"name":"Generative AI","slug":"generative-ai"},{"name":"AWS","slug":"aws"}]}]}