Foundation
an intent map and conversation scenarios
Conversational workflows
AI chatbots for consistent answers and controlled enquiry routing
We design AI chatbot workflows that help answer routine questions and route enquiries using approved information, clear scenarios, and defined quality controls.
Who this is for
This service is for teams that receive repeated questions about services, documents, products, or next steps and need a consistent route from the first message to a responsible person.
How we work
We review the audience, channel, real questions, available source material, and the decisions the bot must not make. The knowledge base and conversation map are approved before a prototype is tested on successful, ambiguous, and unsupported requests. Escalation to a person remains part of the design.
What you receive
The final configuration follows the approved brief, channels, source materials, schedule, and rights framework.
Production
an approved knowledge-base structure and update rules
Delivery
a chatbot prototype for the selected channel
Launch
quality checks, fallback behavior, and human escalation criteria
Typical projects
Use these examples as a starting point. A producer will confirm the actual production route after reviewing the brief.
service and document navigation
Scope, inputs, timeline, approvals, and usage rights are confirmed for the actual project.
initial enquiry qualification
Scope, inputs, timeline, approvals, and usage rights are confirmed for the actual project.
routing unsupported or sensitive questions to a person
Scope, inputs, timeline, approvals, and usage rights are confirmed for the actual project.
Scope and limitations. The bot must not invent prices, deadlines, links, or outcomes. Personal data, message retention, integrations, free-form conversation, and server-side processing require a separately approved technical and legal design. The final scope depends on the source materials, channels, test coverage, and ongoing ownership of the knowledge base.
Questions before you start
Open a question to review the production boundary before briefing the team.
What can AI chatbot production cover?
We design AI chatbot workflows that help answer routine questions and route enquiries using approved information, clear scenarios, and defined quality controls.
What deliverables might be included in AI chatbot production?
Depending on the brief, deliverables can include an intent map and conversation scenarios; an approved knowledge-base structure and update rules; a chatbot prototype for the selected channel; and quality checks, fallback behavior, and human escalation criteria.
What scope boundaries should be confirmed for AI chatbot production?
The bot must not invent prices, deadlines, links, or outcomes. Personal data, message retention, integrations, free-form conversation, and server-side processing require a separately approved technical and legal design. The final scope depends on the source materials, channels, test coverage, and ongoing ownership of the knowledge base.
A chatbot governed by knowledge, intent, and safe escalation
A useful assistant knows its scope, relies on approved sources, and hands risky questions to a person. Conversation design follows real user tasks instead of showcasing unrestricted model output.
Purpose
Common requests, permitted actions, prohibited promises, and mandatory human-escalation cases are mapped before implementation.
Inputs
Current copy, services, prices, links, policies, and content owners form the knowledge set; conflicting sources remain separate until resolved.
Production cycle
Intents, answers, clarification paths, routes, and tests cover greetings, misspellings, ambiguity, and attempts to bypass the rules.
Delivery
The handoff includes the working configuration, knowledge map, control scenarios, and limitations; integrations require an approved technical boundary.
Scope boundary. The bot does not make legally significant decisions or invent prices and facts. Personal data, external APIs, server storage, and actions on a user's behalf require separate approval and implementation.
Related pathways
Move from the current task to production, evidence, estimation, or project launch without losing context.
AI chatbots for consistent answers and controlled enquiry routing
From a question to a verifiable answer
Inputs
Define users, recurring questions and the actions the assistant is permitted to take. Assign a source and an update owner to each answer. Public information, internal documents and personal data need different access rules.
Working review
Test precise and ambiguous questions, stale sources and missing answers using examples without unnecessary personal data. The assistant should state its limits and route unresolved cases to the responsible person.
Handoff
Agree a change log, source-review schedule and a way to disable faulty scenarios. Test search and navigation first, then external actions separately. A chat response alone is not evidence that an operation was completed.