There are two separate costs to plan for: the one-time cost of building the agent, and the ongoing cost of running it (mostly model API usage). Both matter, and confusing them is the most common budgeting mistake we see.
What Drives the Build Cost
Number of tools the agent needs to use is the biggest driver. An agent that just answers questions from a knowledge base is far simpler than one that needs to call five different internal systems, handle errors from each, and decide what to do when a tool call fails.
How well-defined the task is matters as much as the number of tools. A narrow, well-specified task ("process a refund request following these five rules") is cheaper to build and evaluate than an open-ended one ("help customers with anything").
Evaluation and testing rigor required scales with the stakes of getting it wrong. An internal tool used by five people can launch with lighter testing than a customer-facing agent handling financial transactions.
Human-in-the-loop design, where and how a person reviews or approves agent actions, adds engineering work but is usually worth the cost for anything beyond low-stakes tasks.
Realistic Ranges
A single-purpose agent with one or two tool integrations and moderate testing typically runs $5,000-$15,000. A multi-tool agent handling a full business process, with proper evaluation and human-in-the-loop checkpoints, typically runs $15,000-$40,000. A more ambitious agent system with multiple coordinated agents, custom infrastructure, and enterprise security requirements can exceed that considerably.
The Ongoing Cost People Forget to Budget For
Model API usage is billed per token and scales with volume, an agent processing thousands of interactions a month costs meaningfully more to run than one processing dozens. For most business use cases this lands somewhere between a few hundred and a few thousand dollars a month, but it is worth estimating before launch, not discovering on the first invoice.
Monitoring and maintenance, reviewing agent decisions, retraining prompts as your business changes, updating tool integrations when underlying systems change, is a smaller but real ongoing cost, typically covered under a support retainer.
Start with a scoped proof of concept ($3,000-$8,000, 2-4 weeks) to validate the use case against real data before committing to a full build. This de-risks the larger investment and gives you real usage data to estimate ongoing model costs accurately.
Apa yang Kami Bangun
We scope every AI agent project with a clear breakdown of build cost and estimated ongoing usage cost before you commit, see our AI Development page for our full process and pricing guidance.
