Service
Bot Development
Who this is for
Support and operations teams automating a defined conversation or task.
Automation needs reliable knowledge, permission boundaries and a clear path to a person when the system cannot help.
Scope the knowledge sources, permissions and tasks a bot may handle. Test representative conversations and failures, then agree escalation, integrations, usage costs and monitoring responsibilities.
Discuss an automation pilotScope and outputs
Use these as a starting point for the engagement. Inclusions, estimates and acceptance criteria are agreed for your project.
Conversation and knowledge-source scope
Evaluation and human-handoff criteria
Integration and monitoring outline
Capabilities to scope
- AI-Powered Chatbots
- Voice Assistants
- Process Automation Bots
- Multi-Platform Integration
- Natural Language Understanding
Tools and timeline
Technology choices depend on fit: Dialogflow · Rasa · Microsoft Bot Framework · GPT APIs.
Estimate agreed after scoping.
A delivery process to agree
- 01
Select a repeatable task and the boundaries of automation.
- 02
Review knowledge freshness, access and data handling.
- 03
Test representative conversations, unsafe responses and escalation.
- 04
Agree integrations, usage cost and ongoing content ownership.
AI can assist suitable drafting, exploration or repetitive work. The agreed process must retain engineering review, meaningful validation and a responsible release owner. Tool and data permissions are agreed before using project material.
Related engineering guides
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Read articleQuestions to resolve before starting
- Which tasks should remain with a person?
- Who owns knowledge updates?
- What happens when an answer is uncertain or an integration fails?
If requirements are still uncertain, start with discovery and scoping.
Discuss a focused software engagement
Tell us the problem, users and constraints. We can discuss whether discovery, a first release or a system improvement is the right next step.
Discuss your project scope