Manual re-entry disappears
Work somebody is currently copying between two tools becomes a trigger, and that person gets the hours back.
AI chatbot integration for your website
Visitors ask questions across product pages, help articles and service information. We connect a website chat interface to an approved content collection and an AI answer service, with a clear route for questions the content cannot answer. Your team controls the material, enquiry destination and limits of the conversation.
A few clients we’ve worked with
What we do
Add a website chatbot that uses approved content, links to its sources and hands unanswered enquiries to your team.
What happens after the successful test.
Most connections work on the first submission. The cost shows up months later, in duplicate records, silent failures and numbers nobody trusts.
Your data stays trustworthy
One agreed source of truth per field means two systems cannot both be right and disagree.
Failures announce themselves
Validation, duplicates, retries and failure behaviour are defined, so a broken connection is visible instead of quietly losing enquiries.
A chatbot grounded in your website
The starting implementation uses a Claude API connection behind your website. We define the answerable topics and source collection before adding the interface to public pages.
- Solution
- Integrations
- Connected systems
- Claude + REST API
- Data flow
- Approved public content is prepared for retrieval. A visitor’s question selects relevant passages for the AI service, which returns an answer and source links to the website. Enquiry details go to the agreed destination only through a separate, explicit handoff.
Prepare the answer sources
Choose authoritative pages and documents, remove conflicting versions and preserve their URLs. Content updates need an agreed refresh process so the assistant does not keep answering with a retired policy or product description.
Build the conversation and fallback
Connect the chat interface, retrieval and answer generation. Responses should cite supporting material where available. Missing evidence, restricted topics and requests outside the defined scope receive a helpful fallback or contact route.
Connect the enquiry handoff
Agree on the fields visitors can submit and where staff receive them. Keep an unsuccessful CRM or email delivery visible in the interface and operating logs; a chat response alone does not prove the enquiry arrived.
Client reviews
Read our reviews on Clutch ↗“Norml Studio's professionalism and responsiveness were impressive.”
“They were proactive in suggesting improvements we hadn't considered.”
“They delivered what they said they would, on time.”
“They focused on how to make our daily operations easier, not just on building features for the sake of it.”
“They understood that the app needed to be practical for someone sitting in a car, not just look good on a desktop.”
“Their level of dedication to the success of the project and GoPetZen's business as a whole is unique.”
What we need before building
Approved public information
Provide the website and source pages the assistant may use. Private customer records, account-specific answers and internal documents require a separate authenticated design.
API account and data policy
Confirm the model account, available quota and approved handling of questions and chat history. Usage charges, retention settings and logging access are agreed for the chosen account.
A content and enquiry owner
Name the person who approves source material, reviews unanswered questions and checks handoff delivery. Supply examples of questions the chatbot should answer and those it should decline.
How we build and test it
Define the question set
Review typical visitor questions alongside the published source content. Identify missing facts before relying on the assistant to answer them.
Test answers and handoff
Check supported answers, conflicting passages, unsupported claims and enquiry delivery. Include instructions embedded in retrieved content to test that they cannot expand the assistant’s permissions.
Release with a review process
Verify the interface on the live website, document source refresh and provide a way to disable chat while retaining the normal contact route.
The people who do this work.
No account layer between you and them. These are the Norml specialists this work runs through.
Artur Tsitou
DevOps & Backend Developer
Petr Savenok
Full-Stack Developer
Max Tymoshyn
Founder & Architect
Let's chat
“I've spent 10 years working across development and marketing. I started as a developer, but design, SEO and advertising were already part of the job. That taught me to treat a website as one system: the business, the content, the design and the code have to work together. At Norml, I lead the architecture behind our work and stay involved wherever strategy, design, development and search meet.”
Max TymoshynFounder & Architect
Get startedRelated services.
Questions about this implementation
Can the chatbot answer anything about our business?
Its useful scope is the approved information supplied to it. We define unsupported topics and a fallback. Source retrieval and citations help review an answer, but they do not guarantee that every generated statement is correct.
Will it train a new model on our website?
The proposed scope retrieves relevant content when a question arrives and supplies it as context. Training or fine-tuning a model is separate work and is not required by this design.
Can it show customer order details?
That requires authenticated customer identity and record-level access checks. The public content chatbot does not receive private order data by default.
Does it replace the website search box?
Chat answers a visitor’s question conversationally. On-site search returns a browsable list of pages or products with filters. We scope those interfaces separately so each serves its intended job.
Share your website and a few recurring visitor questions. We will identify the source material, answer boundaries and handoff your team needs.