Capability 05 — AI Agents

AI that acts, not just answers.

Chatbots answer questions. Agents execute tasks. They search, decide, use tools, iterate, and hand off to humans when they hit their limits. From customer service automation to IT diagnostics to financial reconciliation — we build agents that work.

Overview

What is an AI agent?

An AI agent is a system that completes multi-step tasks autonomously. It doesn't just respond to a prompt — it plans, uses tools, evaluates its own work, and decides what to do next.

A chatbot says

“Here's how to reset your password.”

An agent does

Looks up the account, verifies identity, sends the reset link, logs the request in the ticketing system, and follows up if the user doesn't complete the reset.

Impact

Before and after.

	Before agents	After agents
Team	5 support engineers	2 engineers + agents
Tickets/day	200	300 (growth)
Auto-resolved	0	220 (73%)
Escalated to humans	200	80
Avg. resolution time	4 hours	12 minutes (auto) / 2 hours (escalated)
Team focus	Password resets, account unlocks, "how do I..."	Complex incidents, infrastructure improvements

Illustrative scenario — IT support at a midsize enterprise

The agents handle the routine. Your people handle the hard problems. Both get better over time.

Architecture

How agents work.

User goal
    ↓
Planning agent — breaks goal into sub-tasks
    ↓
Execution agents — each handles one sub-task
    ├── Search tool — query documents
    ├── API tool — call internal systems
    ├── Decision tool — evaluate options
    └── Human handoff — escalate when needed
    ↓
Critic agent — validates the result
    ↓
Response to user

The loop continues until the goal is met or a human is needed. State persists across steps. Every decision is logged for audit.

Tools

Frameworks we use.

We are framework-agnostic. We pick the right tool for your stack.

Framework	Best for
LangGraph	Stateful, long-running agent workflows. Graph-based execution with checkpoints. Enterprise adoption documented in LangChain's published case studies.
CrewAI	Multi-agent teams with role-based coordination. Fastest time-to-prototype.
Claude Agent SDK	Code-first agents with strong reasoning. Best for software engineering and complex logic.
Microsoft Agent Framework	.NET/Python shops on Azure. Unified SDK with OpenTelemetry observability.

Applications

Use cases.

Customer Service Automation

An agent handles tier-1 support: looks up account, searches knowledge base, processes returns, escalates complex cases to human agents with full context. 24/7, in English and Spanish.

IT Operations

An agent monitors infrastructure, diagnoses incidents, searches runbooks, executes approved fixes.

Financial Operations

Invoice reconciliation across multiple systems. Agent extracts data from PDFs, matches against ERP records, flags discrepancies, generates reconciliation reports.

Legal & Compliance

Agent reviews contracts against policy requirements, flags non-standard clauses, generates compliance summaries. Every decision traced to specific policy references.

HR & Onboarding

Agent guides new hires through onboarding: provisions accounts, schedules training, answers policy questions from the handbook, collects signed documents.

Integration

Agents + RAG = the enterprise stack.

Agents reason and act. RAG grounds them in your data. Together, they form the enterprise AI stack:

Knowledge (RAG)

Gives the agent access to your documents and knowledge.

Agents

Use that knowledge to make decisions and take action.

Fine-tuning

Shapes agent behavior to your organization's standards.

Managed Services

Keeps it all running, 24/7.

Contact

What workflow do you want to automate?

Describe one process your team does manually. We'll tell you if an agent can handle it.

Automate a workflow →