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Useful conversations

Design an assistant that knows its boundaries.

We develop conversational interfaces for scoped support, discovery and information tasks. A useful chatbot retrieves approved information, explains uncertainty and hands off to a person when necessary.

Let’s discuss your project

What this service helps you solve

A chatbot that answers everything confidently can damage trust. We design the knowledge scope, conversation flow and escalation path before the visual interface.

What we deliver

Conversation flows, an approved knowledge scope, application implementation, evaluation examples and update instructions.

Knowledge design

Prepare approved sources, ownership and update rules.

Conversation delivery

Build the interface and connect retrieval or business APIs within the agreed permissions.

Quality evaluation

Test common questions, missing information, unsafe requests and human handoff.

Technology and implementation choices

Retrieval-augmented approaches can connect language models to controlled sources. Citations and confidence handling depend on the application and must be tested with real questions.

How the work moves forward

01 / Define what the assistant can and cannot do

Define what the assistant can and cannot do.

02 / Build responses around approved knowledge

Build responses around approved knowledge.

03 / Evaluate failure cases and prepare human support

Evaluate failure cases and prepare human support.

Who this is for

Customer service, education, product support and internal knowledge teams.

Define the proof your project needs

Your project plan should state the acceptance criteria before work begins: the journeys that must function, the information that must be editable and the evidence used to check the result. Explore our published work for a view of the company’s documented projects.

Questions before you start

Will a chatbot replace our support team?

It can assist with suitable repetitive questions. Complex, sensitive or unresolved cases still need a clear human path.

Can it invent an answer?

Language models can produce incorrect output. Source restrictions, evaluation and uncertainty handling reduce risk but do not justify a guarantee of perfect accuracy.

Let’s define the right next step.

Tell us what your business needs to achieve, what you already have and where the current experience falls short.