Customer service assistant
It searches approved product and process information. It can prepare a response and show its source. Where a request needs special handling or information is insufficient, it refers to a person under the agreed rules.
All servicesCAPABILITY / 03
ASSISTANTS / EXECUTIONAI Agents
An assistant with a real job to do.
We design AI assistants with a specific remit, access to appropriate information and clear limits on their actions.
THE CHALLENGECONTEXT BEFORE TECHNOLOGY
A chatbot giving generic answers is not enough.
A useful agent understands its remit, uses approved sources and recognises when a person is needed. We start with a focused task and expand only after testing in practice.
WHAT WE DELIVERA clear scope.
A clear scope.
Specific deliverables.
- 01Defining the task, sources and permitted actions
- 02Connecting approved company knowledge and tools
- 03Evaluation and human handoff scenarios
- 04Operational monitoring and gradual improvements
IN PRACTICE / ILLUSTRATIVE SCENARIO
What it could look like in practice.
A support assistant searches an approved product catalogue for an answer. If it cannot find documented information, it passes the request to the team instead of inventing a response.
What we evaluate
Answer accuracy, supporting sources and handoff quality.
A CLOSER LOOK / AI AGENTS
What it means
for your business.
An AI agent combines instructions, information and tools to support a specific task. Its value depends on how well that task is defined, its sources and the controls around its actions. We design assistants that fit real working processes.
Sales preparation assistant
It organises a new enquiry, identifies questions requiring clarification and prepares an internal brief. The team uses that output to continue the conversation. Prices, commitments and final proposals remain subject to the agreed approval level.
Internal team assistant
It helps search procedures, manuals and onboarding material. Access follows the user's role. Where the implementation supports it, answers reference the original document for checking and further reading.
THE WORK / STEP BY STEP
From our first conversation
to everyday use.
Each collaboration is built around your specific task. These phases help establish expectations, deliverables and responsibilities before we move forward.
Understanding and defining the scope
We discuss the goal, examine the current process and define the scope. We document sources, tools, owners and constraints. Before implementation, you know what will be examined, what will be delivered and what your team needs to provide.
Preparation and design
We organise the necessary information and design the application's workflow. We define quality checks, approval levels and how to handle missing information. The rules must be understandable and consistently applicable.
A focused test
We test an agreed set of cases. Alongside typical examples, we examine ambiguous requests, incomplete data and exceptions. We record what works, what needs improvement and where human intervention is required.
Evaluation and handover
We compare the result with the agreed criteria. We deliver the planned materials and explain how to use them. Your team understands the necessary checks and how to report problems.
Support and development
Where ongoing collaboration is agreed, we monitor operations and adapt the application as needs change. Expansion depends on test results and support capacity, rather than the volume of work alone.
BEFORE WE START
What we will need from you.
For the first conversation, simply describe your need. The required information and access are identified once the scope is defined.
- A clear task and a list of excluded activities.
- Approved sources with an accountable owner for updates.
- Tool permissions and human approval points.
- Real evaluation scenarios, including challenging cases.
QUESTIONS / ANSWERSUNDERSTAND BEFORE YOU DECIDE
How does an agent differ from a chatbot?
A chatbot typically provides a conversation. Depending on its implementation, an agent can use tools and carry out steps towards a task. The real distinction lies in the system's capabilities and controls, rather than its name.
Can it operate without human review?
Autonomy is designed around each task. Drafting and information retrieval may allow more freedom. Actions that create commitments or change important data need suitable limits and approval levels.
How does it learn about our business?
We give it specific instructions and access to approved sources. We do not assume it already knows your products, policies or procedures. Organising and updating those sources is an essential part of implementation.
Can it give an incorrect answer?
Yes. We therefore include evaluation, source references, uncertainty handling and human escalation. These checks reduce failures without guaranteeing zero errors. Suitable use depends on the requirements of the particular task.
Can it be added to our website?
If the platform and design allow it, an assistant can be integrated into a website or another environment. Before integration, we define the audience, sources, required logging and route to human support.
How do we define when it should hand off to a person?
We document request categories, source gaps and actions it must not perform. We test these scenarios before release. A handoff should transfer useful context so the person does not need to start from scratch.
How is an agent evaluated?
We use a set of questions and expected criteria: accuracy, supporting evidence, appropriate escalation and compliance with limits. If it uses tools, we evaluate its actions too. We also monitor response time and operating costs.
What happens after handover?
We establish a process for updating sources and reviewing problems. New questions can be added to the evaluation set. We define who monitors operations and how changes are approved so the assistant remains useful.
Let's start
with what you need.
Tell us which task you want to improve. We will discuss the possibilities, data and boundaries before recommending a solution.
Talk to DIGITALNOW ✳