Solution examples

Case studies and representative solutions

How Perixope designs AI agents and Generative AI applications on AWS: the problem, the solution, the AWS services and what the agent does.

Security agentCost agentOperations agentQueryDash

These are illustrative solutions and representative architectures. They show how Perixope approaches each problem and are not reports of specific customer results.

Illustrative solution

AI-Powered AWS Cloud Security Agent

Agentic AI + Cloud Security

Problem

Cloud environments generate large volumes of security findings across IAM, GuardDuty, Security Hub, Config and CloudTrail. Teams struggle to see which findings matter most.

Solution

An AI security agent that collects security signals, correlates findings, explains risks, prioritises issues and recommends remediation.

Agent capabilities

Analyse, correlate, explain, prioritise, recommend, and remediate with approval.

AWS services

  • Amazon Bedrock
  • GuardDuty
  • Security Hub
  • AWS Config
  • CloudTrail
  • IAM
  • Lambda
  • DynamoDB

Illustrative solution

AI Cloud Cost Optimization Agent

Agentic AI + FinOps

Solution

An AI agent that analyses AWS billing and usage data and identifies opportunities for rightsizing, resource cleanup, Savings Plans, Reserved Instances and architecture optimisation.

Questions it answers

  • “Why did my AWS bill increase?”
  • “Which resources are idle?”
  • “Where can we reduce cost?”
  • “What caused this month’s cost anomaly?”

AWS services

  • Cost Explorer
  • AWS Budgets
  • Amazon Bedrock
  • Lambda
  • S3
  • DynamoDB

Illustrative solution

AI-Powered Cloud Operations Agent

Agentic AI + AIOps

Solution

An AI agent that analyses CloudWatch metrics, logs and infrastructure signals to investigate incidents and recommend remediation.

AWS services

  • Amazon Bedrock
  • CloudWatch
  • ECS
  • RDS
  • Lambda
  • OpenSearch

Product: QueryDash

Conversational Analytics & AI Data Agent

Generative AI + Agentic AI

Solution

Users ask business questions in natural language. The QueryDash agent turns each question into a validated query and explains the answer with a chart.

How the agent works

  1. Understand the question
  2. Determine the data needed
  3. Generate SQL
  4. Validate the SQL
  5. Execute the query
  6. Analyse the results
  7. Generate an explanation
  8. Create a visualisation

AWS services

  • React
  • TypeScript
  • CloudFront
  • ALB
  • ECS Fargate
  • Amazon Bedrock
  • Amazon Nova
  • Aurora PostgreSQL
  • RDS
  • DynamoDB

Representative architecture

AI-Powered Enterprise Knowledge Assistant

Generative AI + RAG

Capabilities

Document ingestion, knowledge retrieval, semantic search, context-aware responses, access control and guardrails.

AWS services

  • Amazon Bedrock
  • Knowledge Bases
  • S3
  • Aurora PostgreSQL
  • Lambda
  • ECS
  • CloudFront

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