Give customers or employees a simpler way to ask questions about your business. We build AI assistants around your approved information and, where appropriate, connect them to clearly defined tasks.
Discuss an assistantAn AI assistant lets someone ask a question in everyday language and receive a response. An agent can also carry out agreed actions through connected software.
For example, a visitor could ask what a service includes, or an employee could ask how a documented procedure works. We configure the assistant to use the information approved for its role and test how it responds to questions it cannot answer.
An agent might create a support ticket after gathering the required details. It needs a connection to the relevant system and permission to perform that action. We specify what it can do, which actions need approval, and how failures are handled.
An assistant cannot compensate for missing or outdated business information. It also needs a route to a person for unresolved questions and situations requiring judgement. Preparing the source content and handover process is part of the work.
Illustrative use cases. Scope and feasibility depend on your systems and information.
A website visitor asks what a service includes or how to get started. The assistant responds using approved service information. When the request needs individual advice or is not covered, it offers the agreed route to your team.
An employee asks how to follow a company procedure. The assistant uses the relevant documents available to that employee. Where supported and included in scope, it can point to source material so the user can check the guidance.
A customer describes a problem. A task-focused agent gathers the required details and creates a ticket in the connected support system. Staff handle the request through their normal process; the agent’s permissions are limited to the agreed task.
The build is scoped around an audience, a body of information, and a clear job to do. It can include:
We identify the documents or pages the assistant will use, highlight gaps, and agree which source is authoritative when information conflicts. You approve the content and decide who keeps it current.
We specify the questions it should handle, the details it should ask for, and the requests it should pass to a person. For agents, the scope also lists the actions they are allowed to take.
Build the agreed place for users to interact, such as a website chat interface or internal workspace. Where tasks or private information are involved, we configure supported connections and access restrictions.
Evaluate typical questions, ambiguous requests, missing information, and attempts to go beyond the intended role. Your team receives guidance on maintaining content, reviewing problems, and managing the handover to a person.
Scope, responsibilities, and success measures are agreed before implementation.
Choose the users, questions, source content, allowed actions, and route to human help. Check that the required information is available.
Configure the assistant and test it with questions your users are likely to ask. Review incorrect answers and requests outside its role.
Prepare your team to use and oversee it. Agree how content is updated, issues are reviewed, and any ongoing support is provided.
Start with the questions people ask most often and the information your team uses to answer them.
Provide suitable service descriptions, procedures, or other documents. A named content owner should resolve gaps and approve changes so the assistant has a reliable source to work from.
Decide whether it serves the public, customers, or employees. Specify information each group may access and any actions that require approval. Platform suitability is checked against these requirements.
Involve someone who can judge whether answers are useful and correct. Agree where unresolved questions go and who maintains the assistant after launch. Ongoing content work and support are scoped explicitly.
What to consider before you choose your next step.
A chat window is one possible interface, but it is only part of the solution. The work also includes choosing the business information the assistant can use, deciding which questions it should handle, testing the responses, and defining when it should pass a request to your team.
An assistant mainly helps people find or understand information. An agent can also carry out a defined task, such as creating a support ticket through a connected system. Those actions require agreed permissions and checks. We scope the solution around the job you need it to do rather than the appearance of the chat interface.
It can where the selected platform supports your information and access requirements. We first identify which documents are suitable, who is allowed to access them, and how the service provider processes that information. Employee-only content needs to be separated from information available to the public.
The project also considers document quality and ownership. Outdated or conflicting instructions can lead to unreliable answers, so an authorised person should approve the source content and resolve gaps. Access permissions, provider settings, and the update process are agreed before implementation; private information should not be added simply because a tool accepts document uploads.
Yes. An AI assistant can produce an inaccurate or incomplete answer, including when the source information is unclear, missing, or out of date. It should not be treated as a replacement for professional judgement or as a guarantee that every response is correct.
We evaluate typical questions, ambiguous requests, and questions outside its intended role. Depending on the scope, the assistant can show source information, ask for clarification, or direct the user to a person. After launch, reviewing reported mistakes and updating approved content helps improve its usefulness. These checks manage the limitation; they do not eliminate it.
A content owner is agreed during the project. This person or team is responsible for keeping the approved documents, service details, or procedures current. The handover explains which sources the assistant uses and how changes should be introduced and checked.
The update method depends on the platform and scope: some solutions can read changes from a connected source, while others require a refresh or upload. Important changes should be tested with relevant questions before users rely on them. If you want help maintaining content, connections, or answer quality, that work can be included in a separately defined support arrangement.
Before launch, we agree the assistant’s job and test questions that reflect real user needs. We review whether answers are accurate, understandable, and supported by the approved information. We also check whether it recognises requests it cannot handle and provides the agreed route to a person.
In use, suitable measures might include task completion, answer corrections, and the quality of enquiries passed to staff. For an agent, we also check whether the intended action was completed correctly. A high number of conversations alone is not enough to show value; the evaluation should reflect whether people get useful help.
Share the recurring questions or tasks you want to support. We can help define a useful role for an assistant.