What an AI agent can do for you
An agent receives a goal, decides what to do next, uses tools and reports back. Typical uses:
- Look up and update records through your APIs
- Query databases and summarise results
- Triage emails, tickets or documents
- Run multi-step workflows with approval points
- Answer questions using your own knowledge base
How I build agents
- Tools: each tool has a clear contract, validated input and limited permissions.
- Memory and context: only the context the task needs, kept within cost limits.
- Guardrails: output validation, rate limits and human approval for sensitive actions.
- Observability: logs of every step so failures can be diagnosed.
- Deployment: background jobs, retries and monitoring, packaged with Docker.
Agents often combine with RAG for knowledge and with AI automation for scheduled work. The overall service is described under AI app development.
Pricing depends on scope. Tell me about your project.