Back office
Collect data, read requests, prepare responses, update systems and create tasks.
AI agents for business
An AI agent becomes useful when it can work inside a process, not just answer in a chat.
I build agents connected to data, APIs and business tools so they can retrieve information, prepare actions, update systems and handle tasks within defined rules and approvals.
Use cases
Agents work best on bounded tasks, with clear tools and a verifiable outcome.
Sales and customer ops
Qualify requests, retrieve CRM context and suggest or prepare the next step.
Knowledge and support
Search internal documentation and company data while citing sources and staying inside the correct scope.
Control
Autonomy does not mean unrestricted freedom.
The agent should know what it can read, which actions it can execute and when it must stop for human confirmation.
Human in the loop
Sensitive, irreversible or high-impact actions can require approval before execution.
Least privilege
Access is limited to the tools and data required for the task, avoiding generic permissions.
Traceability
Inputs, tools, outputs and actions are logged so it is possible to understand what happened and why.
Fallback
When information is missing or confidence is insufficient, the flow should degrade safely.
Method
Job first. Agent second.
Task
Define exactly what the agent must achieve.
Tools
Choose the data and actions it is allowed to use.
Guardrails
Permissions, confirmations, limits and fallback paths.
Measure
Accuracy, time, cost and errors avoided.
Use case
If a task needs context and multiple tools, it may be a good candidate.
Describe what the agent should do, which systems it should use and what result it should produce.
Tell me about the projectExplore further