Enterprise AI agents

From Generative AI to autonomous AI agents

Generative AI understands and generates. Agentic AI goes further: it plans, uses tools, acts, observes the result and decides the next step, within the limits you set.

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agentObserveReasonApproveActVerify

What makes an agent different

A chatbot ends when it answers. An agent keeps working on a goal: it checks what changed, decides whether the goal is met, and either stops or takes the next step.

Generative AI
  1. Understands
  2. Generates
Agentic AI
  1. Understands
  2. Plans
  3. Uses tools
  4. Acts
  5. Observes
  6. Evaluates
  7. Continues

Inside a Perixope agent

Planner
Breaks a goal into steps.
Reasoning
Decides which step and which tool comes next, using a foundation model on Amazon Bedrock.
Tools
Approved functions the agent can call: AWS APIs, databases, ticketing, chat and internal systems.
Evaluation
Checks results against the goal and decides whether to continue, ask a person or stop.
  1. 1User
  2. 2AI agent
  3. 3Planner
  4. 4Reasoning
  5. 5Tools
  6. 6AWS APIs / enterprise systems
  7. 7Results
  8. 8Evaluation
  9. 9Next action (back to planner)
Example workflow

Three levels of control

Autonomy is a setting you choose per workflow.

  1. Level 1

    AI recommends

    The agent analyses and recommends. People decide and act.

    Best for: First deployments, high-impact systems

  2. Level 2

    AI assists

    The agent prepares the action, then waits for a person to review and approve it.

    Best for: Remediation, rightsizing, configuration changes

  3. Level 3

    AI automates

    The agent runs predefined low-risk actions under strict policies, and logs and verifies every step.

    Best for: Tagging, reports, stopping known non-production resources

Each workflow gets its own level. The same agent can automate a report while still asking for approval before any change to production.

Specialised agents that collaborate

One agent that does everything is hard to secure and hard to trust. Perixope designs focused agents with narrow permissions, coordinated by a supervisor.

Example: “Why did costs and errors both rise after Tuesday’s release?” The supervisor asks the operations agent to check the deployment and error rates, and the cost agent to compare spend by service. It combines both findings into one explanation and a recommended action for approval.

Supervisor agent

Security agent

  • AWS Security Hub
  • Amazon GuardDuty
  • AWS Config

Cost agent

  • AWS Billing
  • Cost Explorer
  • EC2 / RDS usage

Operations agent

  • Amazon CloudWatch
  • OpenSearch
  • Prometheus · Grafana
Decision / approval
Action executor
AWS APIs / tools
Representative architecture

The right framework for each project

  • Strands Agents
  • LangGraph
  • LangChain
  • CrewAI
  • Model Context Protocol (MCP)
  • Agent-to-Agent (A2A)
  • Amazon Bedrock Agents

Perixope chooses frameworks based on the workflow, the integrations, how the agent will be run and monitored, and your team’s existing stack. Not every project uses every framework.

Have a workflow an agent could own?

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