AI Chatbots

AI Chatbot Development Grounded in Your Own Content

We build customer support and sales chatbots that answer from your documentation, product catalog and policies, not from guesswork. Each assistant runs on retrieval-augmented generation, connects to your business systems through tool calling, and hands the conversation to a person when it should. You get one assistant that works across your website, WhatsApp and other channels.

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Grounded answers

Responses are generated from your approved content and cite the source they came from.

Clean human handoff

The assistant recognizes when to step aside and passes the full conversation to your team.

One brain, many channels

A single knowledge base and policy layer serves your website, WhatsApp and messaging channels.

What you get

AI Chatbots: what is included

Knowledge Base Ingestion

We ingest your help center, product pages, PDFs and policy documents, split them into clean passages, and index them for retrieval with scheduled re-syncs as content changes.

Retrieval-Augmented Answers

Each question triggers a hybrid keyword and vector search with reranking, so the model writes its reply from the most relevant passages instead of from memory.

Live System Actions

Through tool calling, the chatbot can look up an order, check availability, book an appointment or create a support ticket in your CRM or helpdesk.

Human Handoff

Clear escalation rules route sensitive, complex or frustrated conversations to a person, with the transcript and a short summary attached so nobody repeats themselves.

Guardrails and Scope Control

Topic boundaries, prompt injection defenses and refusal rules keep the assistant on your business, and it says it does not know rather than inventing an answer.

Conversation Analytics

You see which questions are asked, which go unanswered, where handoffs happen and which content gaps to close, with transcripts available for review.

How AI chatbot development works when accuracy matters

A language model on its own knows nothing about your return policy, your pricing rules or last week's product update. That is why we build every chatbot on retrieval-augmented generation. Your content is cleaned, split into passages, embedded and stored in a vector index. When a customer asks a question, the system retrieves the most relevant passages and instructs the model to answer only from them. If nothing relevant is found, the assistant says so and offers a handoff.

Accuracy is then tested, not assumed. Before launch we assemble an evaluation set of real customer questions with known correct answers, and we score the chatbot on groundedness, completeness and tone. The same set runs again whenever we change a prompt, a model or the knowledge base, so a fix in one area does not quietly break another. After launch, flagged conversations feed back into the evaluation set and the content backlog.

Answers drawn from your approved content
Source citations on every factual reply
Regression tests before each release
Defined behavior when no answer is found
Escalation rules agreed with your team

Website, WhatsApp and messaging channels from one assistant

Customers do not stay in one place, so the assistant should not either. We build a single conversation engine and connect it to each channel through a thin adapter: an embeddable widget for your website, the WhatsApp Business Platform, and other messaging or helpdesk channels your team already uses. Knowledge, policies and guardrails live in one place. Update a shipping policy once and every channel answers correctly from that moment on.

Model choice follows your requirements. Hosted APIs from providers such as OpenAI and Anthropic offer strong reasoning with little infrastructure to manage. Open-weight models such as Llama can run on servers you control when conversations contain data that must stay inside your environment. We keep the model behind an abstraction layer, so it can be swapped as quality, cost and privacy needs change, and we mask personal data in logs by default.

How we work

A clear process from first call to launch

01
Discover

We review your support transcripts, content sources and systems to define scope, escalation rules and what a good answer looks like.
02
Build

We ingest your content, configure retrieval, write the system instructions and connect the tools the assistant needs to act.
03
Evaluate

We test against real customer questions, tune retrieval and prompts, and run adversarial checks before any customer sees it.
04
Launch and Improve

We release channel by channel, monitor conversations, and refine content and behavior based on what customers actually ask.

Use cases

Where AI Chatbots delivers value

Customer Support Deflection

Answer routine questions about orders, accounts, policies and troubleshooting instantly, leaving your agents free for the complex cases.

Sales Qualification

Engage website visitors, answer product questions, capture requirements and pass qualified leads to your sales team with full context.

Appointment Booking

Let customers check availability, book, reschedule and get reminders through chat or WhatsApp without waiting for office hours.

Internal Help Desk

Give employees one place to ask about HR policies, IT procedures and internal documentation, with access controls respected.

FAQ

AI Chatbots — frequently asked questions

How is an AI chatbot trained on my business content?

In most cases the model is not retrained at all. We index your documents, help articles and product data in a search layer, and the chatbot retrieves the relevant passages for each question before answering. This approach, called retrieval-augmented generation, means updates to your content take effect quickly and answers can cite their sources.

Will the chatbot make things up?

No system can promise zero errors, but the risk is controlled by design. The assistant is instructed to answer only from retrieved content, to cite it, and to say when it does not know. We verify this with an evaluation set of real questions before launch and keep testing after every change.

Can the chatbot work on WhatsApp as well as my website?

Yes. We connect the same assistant to your website widget and to the WhatsApp Business Platform, and can add other messaging or helpdesk channels. All channels share one knowledge base and one set of rules, so customers get consistent answers wherever they start the conversation.

What happens when the chatbot cannot answer a question?

It hands off. We define escalation rules with your team, covering unanswered questions, sensitive topics, explicit requests for a person and signs of frustration. The conversation moves to your helpdesk or inbox with the transcript and a summary, and outside staffed hours the assistant collects contact details for follow-up.

Is customer data safe with an AI chatbot?

We design for data minimization. The assistant only accesses the systems and fields it needs, personal data is masked in logs, and we use provider settings that exclude your data from model training where available. For stricter requirements, the chatbot can run on open-weight models hosted on infrastructure you control.

Related services

Tell us what you want to build

Share your goals and we will reply with a clear plan, timeline and quote — usually within one business day.

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