Will it make things up about my business?

Not if it is built properly. We ground the model in your own documentation and product data rather than letting it answer from general knowledge, constrain it to defined topics, and set explicit fallbacks so it says it does not know and escalates instead of guessing. We also log conversations so you can see exactly what it has been telling people.

Where can the chatbot run?

Your website, WhatsApp, Messenger, Instagram, Slack, or inside your support desk. Most clients start on the website and WhatsApp, since those cover the majority of inbound conversations for service businesses.

Can it do more than answer questions?

Yes. It can qualify a lead against your criteria, book into a calendar, create a CRM record, look up an order, or open a support ticket. Answering questions is the visible part; the value is usually in what it does afterwards.

How much maintenance does it need?

Plan for a short review each month, mainly reading real conversations and closing gaps in the knowledge base. Bots degrade when nobody looks at the transcripts, so we set up the reporting to make that a fifteen-minute job rather than a project.

AI Chatbot Development

AI Chatbot Development That Does the Work, Not Just the Talking

Vedixx builds custom AI chatbots grounded in your own documentation and product data, so they answer questions you never scripted. They run on your website, WhatsApp, Messenger or support desk, and they act: qualifying leads, booking meetings, creating CRM records and opening tickets.

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What is AI chatbot development?

AI chatbot development is the process of building a conversational assistant that answers questions using a company’s own data rather than a pre-written script. It involves assembling a knowledge base from existing documentation, connecting a language model, constraining that model so it cannot invent answers, integrating with business systems so the bot can take actions, and defining when a conversation escalates to a human.

What's included

Knowledge grounding

The bot answers from your documentation, pricing and product data via retrieval rather than general model knowledge. This is the single control that stops it inventing things about your business.

Multi-channel deployment

Website widget, WhatsApp Business API, Messenger, Instagram or Slack — with conversation history shared across channels so a customer is not asked the same question twice.

Lead qualification

Scored against your criteria during the conversation, then written to your CRM with the full transcript attached, so sales opens a record with context rather than just a name and an email.

Actions, not just answers

Book a slot, look up an order, raise a ticket, check delivery status, trigger a workflow — connected to the same systems your team uses, with permissions scoped to what the bot should be able to do.

Guardrails & escalation

Topic boundaries, refusal behaviour, and a defined "I don’t know" path. A bot that guesses to avoid admitting uncertainty destroys more trust than the time it saves.

Transcript review & tuning

Logged conversations, gap reporting and a monthly review loop that takes fifteen minutes rather than a project. Bots degrade when nobody reads the transcripts.

How a grounded chatbot answers a question

The retrieval step is what separates a useful assistant from a plausible liar. A model asked to answer from memory will produce something confident and wrong; a model handed your actual content will quote it.

1
Question
A visitor asks in their own words, on whichever channel they found you — rarely phrased the way your documentation phrases it.
2
Retrieve
Search your indexed content for the passages that actually answer this question, rather than trusting the model to remember.
3
Ground & answer
The model composes a reply constrained to the retrieved material, with instructions to say it does not know rather than fill gaps.
4
Act
If the conversation calls for it: book, look up, qualify, create a ticket or a CRM record through a scoped integration.
5
Escalate or log
Hand to a human with the transcript when confidence is low or the topic is out of bounds. Either way, the conversation is logged for review.

Where it pays for itself

Pre-sales qualification

The problem: Most website enquiries are unqualified. Sales time is spent on discovery calls that end in "we’re not a fit", while genuinely good leads wait in the same queue.
What we build: A bot that asks your qualifying questions conversationally, scores the answers, books a call directly for good-fit prospects, and politely redirects the rest with useful information.
The result: Sales calls are with prospects who already match your criteria, and the transcript arrives before the call does.

Tier-one support deflection

The problem: The same twenty questions — delivery times, password resets, returns policy, opening hours — consume most of the support queue and delay the tickets that genuinely need a person.
What we build: A grounded assistant handling the repeat questions from your live documentation, with order lookups wired in, escalating anything outside its defined scope.
The result: Routine volume is answered instantly and the human queue holds only the tickets that need judgement.

WhatsApp customer service

The problem: Customers message on WhatsApp expecting an immediate reply, but the number is watched by whoever happens to be free, and nothing is recorded in the CRM.
What we build: A WhatsApp Business API assistant that answers instantly, handles order and booking queries, and logs every conversation against the customer record.
The result: A channel your customers already prefer becomes properly staffed and fully recorded.

Internal knowledge assistant

The problem: New staff ask the same process questions in Slack, and the answer is buried in a document nobody can find. Senior people become the search interface.
What we build: An internal assistant indexed on your own handbooks, SOPs and past threads, answering in the channel with a link to the source document.
The result: Onboarding questions get answered without interrupting the person who wrote the process.

How it works

1
Define scope and boundaries
Which questions the bot owns, which it must escalate, and what it is never allowed to discuss — pricing exceptions, legal advice, anything regulated. Written down before anything is built.
2
Assemble and clean the knowledge base
We gather your real content and fix the contradictions, because grounding quality determines answer quality far more than model choice does. Two conflicting policy documents will produce two conflicting answers.
3
Build the retrieval and conversation layer
Indexing, retrieval, prompt architecture and refusal behaviour, plus the tone rules so it sounds like your business rather than a generic assistant.
4
Connect the actions
CRM, calendar, order lookup and ticketing, each with scoped permissions so the bot can do exactly what it should and nothing more.
5
Test against real historic questions
We run it against your actual past enquiries — including the badly worded and the deliberately awkward — and fix failures before launch rather than in front of customers.
6
Launch and review
Live with full transcript logging, watched closely for two weeks, then a monthly review loop that closes knowledge gaps as they appear.

Typical timeline

Phase	Duration	What you get
Scoping	2–4 days	Defined question scope, escalation rules, prohibited topics and success criteria.
Knowledge base build	1–2 weeks	Indexed, de-conflicted content set with retrieval tested against sample questions.
Bot build & integrations	2–3 weeks	Working assistant on your chosen channels, connected to CRM, calendar and ticketing.
Testing & tuning	1 week	Evaluated against real historic enquiries, with failure cases fixed and documented.
Launch & review loop	Ongoing	Transcript logging, gap reporting and a monthly tuning cycle.

AI chatbot vs scripted chatbot

Most "chatbots" businesses have tried are decision trees. They fail the moment a visitor phrases something unexpectedly, which is most of the time. The difference is worth understanding before you buy either.

	Scripted / rule-based bot	Grounded AI chatbot
Handles unexpected phrasing	No. Falls through to "I didn’t understand that".	Yes. Interprets intent rather than matching keywords.
Setup effort	Every path drawn by hand, and every new question needs a new branch.	Knowledge base assembled once; new content improves answers without rebuilding flows.
Risk of wrong answers	Low — it only says what you wrote.	Real, and managed with retrieval grounding, constraints and refusal behaviour.
Maintenance	Editing flows whenever the business changes.	Updating source documents and reviewing transcripts.
Best suited to	Short, fixed processes with few branches.	Open-ended questions across a body of knowledge.

Technologies we build on

Models

OpenAI (GPT)
Anthropic (Claude)
Open-weight models
Embedding models

Retrieval

Vector databases
Hybrid keyword + semantic search
Chunking strategies
Source citation

Channels

Website widget
WhatsApp Business API
Messenger & Instagram
Slack

Operations

Conversation logging
Gap analytics
Evaluation harnesses
Human handoff routing

Systems we connect

HubSpotSalesforcePipedriveZendeskIntercomCalendlyShopifyWooCommerceStripeSlackNotionGoogle Calendar

Who this is for

E-commerce

Order status, returns, sizing and delivery questions — the highest-volume, most repetitive support load there is.

Professional services

Qualifying enquiries and booking consultations without a partner reading every inbound message.

SaaS

Product questions answered from live documentation, with escalation to support for account-specific issues.

Real estate

Availability, viewing scheduling and area questions answered instantly on WhatsApp.

Clinics & healthcare

Appointments, preparation instructions and admin questions, scoped carefully away from clinical advice.

Education & training

Course details, enrolment steps and deadlines, answered around the clock across time zones.

What drives the cost

Chatbot cost is driven far more by the state of your content and the number of actions it must perform than by the model behind it. A bot that answers ten well-documented questions is a fraction of the cost of one that must look up orders across three systems.

State of your documentation

If your policies and product information are written down and consistent, grounding is quick. If they live in people’s heads or contradict each other across three documents, that has to be resolved first.

Number of channels

One website widget is straightforward. Adding WhatsApp brings API approval and template rules; each further channel adds its own constraints and testing surface.

Actions and integrations

Answering is cheap. Booking, order lookup, ticket creation and CRM writes each need integration, permission scoping and failure handling.

Accuracy requirements

A marketing assistant and a bot quoting regulated information need very different levels of evaluation, constraint and review before launch.

Conversation volume

Model usage is per-token, so volume affects running cost directly. High-traffic bots justify caching and smaller models for routine paths.

Ongoing tuning

A bot left unmonitored drifts out of date as the business changes. Budget a small monthly review or accept declining accuracy.

Pilot bot

One channel, a defined question set, no external actions. Proves the concept on real traffic before wider investment.

Full build

Multi-channel, integrated with CRM and ticketing, evaluated against historic enquiries before launch.

Managed

Build plus ongoing transcript review, knowledge updates and accuracy reporting.

What you end up with

Common questions answered instantly, around the clock
Leads qualified and written to your CRM with full context
Support volume reduced without hiding the humans
Meetings booked directly from the conversation
Full transcript logs showing exactly what was said
A defined escalation path instead of confident guessing

Key takeaways

Grounding the bot in your own content — not the model’s general knowledge — is what prevents invented answers.
A chatbot that only answers is worth a fraction of one that also books, looks up and creates records.
Your documentation quality sets the ceiling on answer quality. Contradictory sources produce contradictory replies.
A defined "I don’t know" path protects more trust than a slightly better answer rate.
Bots decay without transcript review. Budget the monthly loop at the start, not after accuracy slips.

Related services

AI Automation

Automations that keep running after the engagement ends.

AI Development

Custom AI features built into your existing product.

AI Integration

Connecting AI models to the systems you already run.

Workflow Automation

Multi-step processes that run without supervision.

Business Process Automation

End-to-end process redesign, then automation.

CRM Automation

Pipeline hygiene and routing that maintains itself.

FAQ

Questions? Answered.

A scripted bot follows a decision tree you draw in advance and fails the moment a visitor phrases something unexpectedly. An AI chatbot works from your actual content and data, so it answers questions you did not explicitly anticipate, in natural language, and hands off to a human when it should.

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