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AI Chatbots

AI chatbots trained on your business, not a generic FAQ

A chatbot that answers three questions and then says contact us is worse than no chatbot. We build assistants grounded in your actual pricing, policies, catalogue, and process, so the answer a visitor gets is the answer your team would give.

The bottleneck

Why most business chatbots get switched off

Two failure modes kill chatbot projects. The first is the decision-tree bot that only handles the paths someone thought to build, so any real question dead-ends into a contact form. The second is a raw language model bolted onto a website with no grounding, which confidently invents prices and policies. Both erode trust faster than they save time, and both end up disabled within a quarter.

What we build
  • Ground it in your real content. We index your site, pricing, policies, product data, and past support tickets into a retrieval layer. The assistant answers from your documents and cites where the answer came from.
  • Constrain what it is allowed to say. Guardrails on pricing, medical, legal, and refund topics. Where a confident answer would be risky, the bot collects the question and routes it instead of guessing.
  • Qualify while it helps. The same conversation that answers a question captures the details your sales team needs: budget, timeline, use case, contact. No separate form.
  • Deploy where customers already are. Website widget, WhatsApp Business API, Instagram DMs, and in-app. One knowledge base, consistent answers across every channel.
  • Hand off cleanly. Live-agent handover carries the full transcript into your helpdesk or CRM, with the visitor's intent already tagged.
What it plugs into

WhatsApp Business API via Meta, retrieval-augmented generation, your CMS or product catalogue, HubSpot or Zoho CRM, Slack alerts.

How Sciquire ships it

Live in under three weeks, not two quarters.

Every deployment follows the same path. We do not sell a demo and disappear. We map the workflow, wire the integrations, and stay on the line while the agent learns from real traffic.

01 / Map

Call audit

We listen to your actual inbound mix and pick the bounded, high-volume intents where an agent wins fastest.

02 / Build

Script and wire

Conversation logic, objection handling, and write-back into your CRM, ATS, AMS, or TMS. No rip-and-replace.

03 / Launch

Live traffic

The agent goes live on real calls with human escalation paths in place from day one. Nothing gets dropped.

04 / Tune

Feedback loop

We watch transcripts, sentiment, and resolution rates, then refine. The agent gets sharper every week.

Questions

AI Chatbots: the questions clients ask first

How do you stop the chatbot from making things up?

Retrieval grounding plus refusal rules. The assistant answers from indexed source documents rather than from general model knowledge, and topics we flag as sensitive get routed to a human instead of answered. We test this adversarially before launch and monitor transcripts weekly after.

Can it work on WhatsApp?

Yes, through the official WhatsApp Business API. That covers automated first response, template messages, catalogue browsing, and follow-up sequences, all within Meta's policy limits on session and template messaging.

What content do you need from us to start?

Whatever you already have: website copy, price lists, service descriptions, refund and shipping policy, and ideally an export of past support conversations. The ticket history is the most valuable input, because it shows what people actually ask.

Will it replace our support team?

It absorbs the repetitive tier of questions so your team handles the ones that need judgement. In practice, teams keep the same headcount and reassign it to escalations, retention, and outbound work.

Ready to see the numbers on your volume?

Send us your busiest inbound intent and current staffing. We come back with the deflection maths and a two-week pilot scoped against your real traffic.