Understanding Agents

Agentic Systems

Autonomous software that observes, decides, and acts within secure, controlled boundaries. Not chatbots with tools—purposeful systems designed for specific outcomes.

Definition

What Is an Agent?

An agent is a software system that can perceive its environment, make decisions, and take actions to achieve specific goals—all with minimal human intervention. Unlike traditional automation, agents handle variability and make contextual decisions.

Observe

Intake data from APIs, databases, events, or unstructured sources. Agents understand context.

Decide

Apply business logic, ML models, and guardrails to determine the appropriate action.

Act

Execute operations with precision—API calls, data transforms, notifications, workflows.

Learn

Improve over time through feedback loops, but only within defined boundaries.

Evaluation

When Do Agents Make Sense?

Agents aren't always the answer. They excel in specific scenarios and can be the wrong choice in others. Honest assessment upfront saves significant time and cost.

Good Fit

  • Repetitive decisions with clear criteria
  • 24/7 operations requiring consistency
  • High-volume processing with nuanced logic
  • Workflows too complex for simple rules
  • Tasks requiring integration of multiple data sources

Not a Good Fit

  • Decisions with legal or ethical ambiguity
  • Situations requiring human empathy
  • One-time or rarely repeated tasks
  • When the cost of errors is catastrophic
  • Tasks without clear success criteria

Architecture

How We Build Agents

Every agent we build follows a consistent architecture designed for reliability, observability, and control. No black boxes.

01

Perception Layer

Data ingestion, normalization, and context assembly

02

Decision Engine

Logic evaluation, model inference, and action planning

03

Action Executor

Operation execution with retry logic and error handling

04

Feedback Collector

Outcome tracking and performance monitoring

05

Guardrail System

Rate limits, permission checks, and safety boundaries

06

Audit Logger

Complete action history with decision traces

Control

Monitoring & Control

Autonomy without control is dangerous. Every agent includes comprehensive monitoring and multiple layers of control mechanisms.

Human-in-the-Loop

Critical decisions route to human reviewers before execution.

Kill Switches

Instant shutdown capability at multiple levels—agent, workflow, or system-wide.

Rate Limiting

Configurable limits on actions per minute, hour, or day to prevent runaway behavior.

Scope Boundaries

Agents only access resources explicitly granted. No implicit permissions.

Ready to Explore Agents?

Let's discuss whether an agentic approach makes sense for your use case. We'll be honest about fit.

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