01
Agent workflows
Multi-step reasoning and action toward a defined goal.
Automate
AI agents that complete real tasks, not just chat.
An AI agent uses tools, calls APIs, retrieves knowledge and takes multiple steps to accomplish a goal. That is different from a simple chatbot. We build agents with the parts that make them dependable in production: clear boundaries, human approval, monitoring and evaluation.
Outcomes
What this is for
The kinds of problems teams bring to us for this work.
Automate multi-step tasks that span several tools
Qualify leads or triage requests before a human steps in
Give staff an assistant grounded in internal knowledge
Keep oversight with approvals, logging and evaluation
Capabilities
What we deliver
Concrete capabilities included in this practice.
02
Tool calling
Agents that use your APIs and functions to act.
03
Knowledge retrieval
Grounding responses in your documents and data.
04
Human approval
Checkpoints before consequential actions run.
05
Monitoring & evaluation
Traces, metrics and tests for agent behavior.
06
Security & deployment
Scoped access and safe, observable deployment.
How we work
A process built for visibility
Small, reviewable increments — so you always know where things stand.
- 1
Discover
Define the goal, tools and acceptable actions.
- 2
Design
Plan the agent's tools, memory and guardrails.
- 3
Build
Implement tool calling, retrieval and approvals.
- 4
Launch
Deploy with tracing and evaluation.
- 5
Evolve
Tune based on real outcomes and failures.
FAQ
Questions we hear often
How is an AI agent different from a chatbot?
A chatbot answers questions. An agent takes actions — it calls tools and APIs, retrieves information and completes multi-step tasks, often with approval steps for anything important.
What are good use cases for AI agents?
Customer support, lead qualification, internal knowledge assistants, research, reporting, document processing and sales operations are common starting points.
How do you keep agents safe and reliable?
We scope what an agent can access, add human approval for consequential actions, and use monitoring and evaluation so behavior is observable and testable rather than a black box.
Keep exploring
Related solutions & industries
Get started
Ready to talk about ai agents?
An AI agent uses tools, calls APIs, retrieves knowledge and takes multiple steps to accomplish a goal. That is different from a simple chatbot. We build agents with the parts that make them dependable in production: clear boundaries, human approval, monitoring and evaluation.
