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── Practical answers for teams evaluating, buying, and running AI agents ──
We build and operate AI agents for real businesses. This blog answers the questions we hear on discovery calls: what agents actually cost, how to choose a development partner, where agents work, and where they fail. Written from production experience, not theory.
What AI agent development services actually include: process, architecture, realistic costs, and how to tell a production-grade build from a demo. From a studio that operates agents daily.
A buyer's guide to AI agent development companies: the four provider types, five signals of a production-grade studio, red flags, and the questions to ask on the first call.
Real numbers for custom AI agent development: 3,000 to 5,000 USD for a single agent, 15,000 to 50,000 USD for a fleet, what drives the price up, and when an agent is not worth building.
AI agents are the units. Agentic AI is the property that makes them agents. What the distinction means in architecture, why vendors blur it, and how to tell which one you are being sold.
AI agents in manufacturing belong in the paperwork layer, not the control loop. What they handle, what integration really costs, why the OT boundary is non-negotiable, and how to scope a first deployment.
Where AI agents earn their cost in logistics: quote handling, track and trace, exception management, documentation, and carrier communication. Plus the integration realities nobody quotes for.
RPA is deterministic and repeats one path perfectly. Agents are probabilistic and handle inputs nobody enumerated. Which one your process needs, where each fails, and why the answer is often both.
Where AI agents work in hospitality: the phone that nobody answers during service, reservations, supplier ordering, and review responses. Plus the one thing an agent must never handle alone.
Evaluating an agent project? A 30 minute call will tell you if it is viable.