How Reco transforms security alerts using Amazon Bedrock

2026-03-23 · Source: Artificial Intelligence · Field: Technology & Digital — Artificial Intelligence & Machine Learning, Cybersecurity & Data Privacy, Cloud Computing & IT Infrastructure · Depth: Intermediate, medium

Summary

Reco, a SaaS security firm, implemented Anthropic Claude on Amazon Bedrock to develop an Alert Story Generator that transforms complex, machine-readable security alerts into human-readable insights. This solution addresses challenges in alert comprehension and automated investigation by converting JSON alert data into clear narratives, correlating risks, generating cross-team summaries, and creating automated investigation queries. Reco selected Amazon Bedrock for its access to multiple foundation models, built-in security features like data encryption and VPC integration, pay-per-use pricing, and API-based architecture. The technical implementation uses few-shot learning, contextual prompting with alert metadata, and Amazon Bedrock prompt caching, which reduced inference latency by 75%. This system has led to a 54% improvement in investigation time and a 63% improvement in incident response time for Reco customers.

Key takeaway

For security operations teams struggling with alert overload and slow incident response, integrating AI-powered alert transformation tools like Reco's Alert Story Generator can drastically improve efficiency. Your team can achieve significant reductions in investigation and response times by converting raw, technical alerts into clear, actionable narratives and automated queries. Consider leveraging platforms like Amazon Bedrock for secure, scalable, and cost-effective deployment of generative AI solutions in your security workflow.

Key insights

AI-powered alert transformation significantly enhances security operations by improving comprehension and accelerating response.

Principles

• Contextual prompting improves LLM output consistency.
• Few-shot learning refines structured output generation.

Method

Reco's Alert Story Generator uses few-shot learning and contextual prompting with alert metadata to transform JSON alerts into actionable narratives, leveraging Amazon Bedrock for model access and prompt caching.

In practice

• Use prompt caching to reduce LLM inference latency.
• Integrate LLMs for automated security alert summarization.

Topics

• Security Operations
• Generative AI
• Amazon Bedrock
• Anthropic Claude
• Prompt Engineering

Best for: CTO, VP of Engineering/Data, Director of AI/ML, Security Engineer, AI Security Engineer, MLOps Engineer

Related on AIssential

• Intelligence-driven message defense and insights using Amazon Bedrock — Generative AI on Amazon Bedrock effectively detects disguised contact information and extracts sentiment from communications, surpassing regex limitations.
• How Lendi revamped the refinance journey for its customers using agentic AI in 16 weeks using Amazon Bedrock — Agentic AI can transform customer experiences in financial services while retaining essential human interaction.
• AWS Announces General Availability of DevOps Agent for Automated Incident Investigation — AWS DevOps Agent uses generative AI to autonomously investigate incidents and automate operational tasks across diverse environments.
• Transform Enterprise Search with GenAI: Build a Production-Ready RAG Knowledge Assistant Using… — RAG with Amazon Bedrock enhances enterprise search by providing accurate, grounded, natural language access to proprietary data.
• Talking to the Ground — AI-powered natural language analytics on a unified lakehouse transforms raw drilling data into actionable operational insights.
• With $1 Cyberattacks on the Rise, Durable Defenses Pay Off — Generative AI accelerates both cyberattacks and defenses, necessitating a shift to foundational security rather than reactive patching.

Open in AIssential →

Editorial summary, takeaway, and curation by AIssential. Original article published by Artificial Intelligence.