AI Agent Development for Business Automation

What does an AI agent do?

An AI agent connects an AI model to information sources and tools to complete a sequence of tasks. For example, it can read an internal request, retrieve the relevant procedure, draft an action, and ask a staff member for approval before updating a system. KODE designs this workflow around your business processes.

When should you use an agent, a chatbot, or rule-based automation?

A chatbot fits conversations and answer retrieval. Rule-based automation fits fixed processes with structured inputs. An AI agent may help when a workflow needs contextual reasoning across multiple tools. During assessment, we choose the simplest approach that meets the need and keeps costs and risks manageable.

An implementation process you can evaluate

Choose one process and name its owner. Map approved data sources and integrations, define test scenarios, and run a limited pilot. Test failure cases, out-of-scope requests, and actions requiring approval. Launch follows a joint review against agreed acceptance criteria.

Integrations and action boundaries

Access to ERP, CRM, spreadsheets, or APIs follows permissions agreed with IT. Start with read-only access when it meets the pilot need. Data changes, message sending, and other consequential actions need clear authorization rules. Activity logs and escalation paths are part of the technical scope.

What determines cost?

Process count, input variability, integrations, model usage, hosting, and support determine cost. A proposal should separate development, testing, usage charges, and operations. Measure completion time, error rates, and human interventions before deciding to expand.

Deliverables discussed during scoping

• Process map, responsibilities, and agent action boundaries
• Scoped integrations and approval rules
• Evaluation scenarios, documentation, and operating guidance

Common questions