SV-23 / SERVICES
AI chatbots that answer accurately and hand over gracefully
A useful chatbot is more than a chat window on a language model. It must answer from your approved information, know what it should not do and pass the conversation to a person when needed.
A useful chatbot is more than a chat window on a language model. It must answer from your approved information, know what it should not do and pass the conversation to a person when needed. We build chatbots for customer support, sales and internal help that are connected to your knowledge and systems, and that you can measure and improve.
What’s included
- Use-case definition: which questions, which users, and what good looks like
- Retrieval-augmented generation (RAG) over your documents, help centre and product data
- Integrations with CRM, ticketing, booking, order and knowledge systems for actions, not only answers
- Guardrails: scope limits, tone, refusal behaviour and handling of sensitive topics
- Smooth escalation to human agents with full conversation context
- Channels such as website, WhatsApp, email and internal tools such as Slack or Teams
- Evaluation sets, analytics and a feedback loop for continuous improvement
Best for
Support teams handling repetitive enquiries, businesses wanting out-of-hours response, and internal teams needing quick answers from policies and documentation.
How we work
- Identify and rank use cases. 2) Prepare knowledge and design the conversation. 3) Build, test against real questions and tune. 4) Launch with monitoring and iterate.
What you receive
Deployed chatbot, knowledge pipeline, evaluation results, analytics dashboard and operating guide.
The result
Faster, more consistent answers for customers and staff, with people free for work that needs judgement.
Frequently asked questions
How do you stop it making things up?
We ground answers in your content, test against real questions, set clear boundaries and design fallbacks. No system is perfect, so we also put monitoring and review in place.
Is our data used to train public models?
We select providers and settings that fit your data requirements and explain data handling clearly before build.