Compliance-first delivery
Assistants your customers and teams trust
Most people have met the frustrating chatbot: rigid menus, confident wrong answers, and no way to reach a person. Old-style decision-tree bots break on anything unexpected, while a large language model with no grounding will happily invent policies and prices. Either way, customers leave and the support queue does not shrink.
We build assistants that answer from your own content and systems. Help-centre articles, policies, product data and past tickets are indexed for retrieval so answers come with sources, and the bot can look up order status, book appointments or create tickets through your APIs. Guardrails keep responses on topic and protect personal data; confidence checks and clear triggers route conversations to a human agent with full context. The same assistant can run on your website, WhatsApp, Slack or Microsoft Teams, and over voice. Under the hood we use the retrieval, evaluation and guardrail patterns from our generative AI practice and our article on RAG in production.
You get an assistant with measured answer quality, analytics on what people ask and where the bot falls short, and a process for improving it. We also build and run our own conversational products — including Clinic Answering Service, an AI receptionist for medical practices, and Appointment Reminder App for WhatsApp and SMS — so we know what it takes to operate them in production. Integrations with CRMs and ticketing systems come from our systems integration team.
- Answers grounded in your knowledge base, with sources
- Actions through your APIs: look-ups, bookings, tickets
- Web, WhatsApp, Slack, Teams and voice channels
- Human handoff with full conversation context
- Guardrails, PII protection and conversation analytics
What's Included
Everything you need, delivered by a senior, security-first team.
Customer Support Bots
Answer common questions, look up account details and create tickets when needed.
Sales Assistants
Qualify leads, recommend products and book demos or appointments.
Omnichannel Deployment
One assistant across website widget, WhatsApp, Slack, Teams and SMS.
Voice Assistants
Phone and IVR assistants with speech recognition and natural responses.
Guardrails & Privacy
Topic limits, PII redaction, consent handling and safe fallbacks.
Analytics & Tuning
Intent reports, unanswered questions and evaluation runs to keep improving.
Chatbots that resolve questions, not frustrate customers
Older chatbots relied on rigid decision trees and keyword matching, and most customers learned to type “agent” immediately. Modern virtual assistants built on large language models can understand natural questions, answer from your own knowledge base, take actions through your systems and hand over to a human with full context when they should. We design and build AI chatbots and voice assistants for customer support, sales, patient engagement and internal help desks.
Where chatbots work well
- Customer support — order status, account questions, troubleshooting and policy answers around the clock.
- Lead qualification — answering product questions, capturing details and booking meetings.
- Healthcare front desk — appointment booking, reminders, directions and routine queries, with clinical questions routed to staff.
- Internal help desks — HR, IT and policy questions answered from internal documentation.
Rule-based vs AI-powered chatbots
| Criteria | Rule-based / decision tree | LLM-powered assistant |
|---|---|---|
| Understands free text | Limited to expected phrases | Yes, including varied wording and languages |
| Knowledge | Hand-written answers | Grounded in your documents via retrieval (RAG) |
| Predictability | Very high | High with guardrails and evaluation |
| Best for | Strict, regulated flows (payments, consent) | Open-ended questions and support |
Most production assistants combine both: deterministic flows for sensitive steps and AI for understanding and answering.
Channels
Website chat widgets, WhatsApp Business, SMS, Facebook Messenger, Microsoft Teams and Slack, and voice through telephony and IVR platforms. One conversation engine can serve several channels so answers stay consistent.
How we build a chatbot
1. Define scope and hand-off rules
We analyse your most common enquiries, decide which the bot should resolve, which it should route, and exactly when to hand over to a human.
2. Ground it in your content
Help-centre articles, policies and product data are indexed for retrieval and kept in sync, so answers reflect your current information. The architecture is described in Taking RAG From Prototype to Production.
3. Connect to your systems
Secure integrations with CRM, ticketing, booking or order systems let the assistant look up and update records with proper authentication. Our systems and API integration team builds these connections.
4. Guardrails and testing
Topic restrictions, prompt-injection protection, PII handling, tested answers on a set of real questions and a clear refusal style for out-of-scope requests.
5. Launch, measure, improve
Analytics on resolution rate, hand-offs, unanswered questions and customer feedback drive regular improvements to content and flows.
See it in our own products
We run conversational products ourselves: Clinic Answering Service, an AI receptionist for US medical practices, the Appointment Reminder App for WhatsApp and SMS reminders, and Insight OS, which combines live chat, analytics and lead capture in one script.
Common pitfalls
- Hiding the route to a human, which damages trust.
- Launching without a test set of real customer questions.
- Letting the bot answer from stale or contradictory content.
- Collecting personal or health data without consent and retention rules — see HIPAA, GDPR and SOC 2 compliance.
For broader LLM applications beyond conversation, see generative AI and agents.
How We Build Your Assistant
Define
Pick the conversations worth automating and the systems the bot needs to reach.
Ground
Prepare and index knowledge sources; build integrations and an evaluation set.
Pilot
Launch on one channel with human handoff, review transcripts and tune.
Expand
Add channels, actions and languages based on what the data shows.
Frequently Asked Questions
Typical tasks include answering FAQs and policy questions, checking order or appointment status, booking meetings, qualifying leads and collecting details before a human takes over. We start with your most frequent enquiries and expand from there.
We minimise this by grounding answers in your approved content, restricting topics, testing against real questions and instructing the assistant to hand over or say it does not know rather than guess. Conversations are reviewed to improve content over time.
Website chat, WhatsApp Business, SMS, Facebook Messenger, Microsoft Teams, Slack and voice/IVR. One assistant can serve several channels.
Yes. We integrate with CRMs, ticketing, booking and order systems through their APIs so the assistant can look up information, create tickets and pass full context to your team on hand-off.
Usually a fixed-price build for the agreed scope and channels, plus a monthly fee for hosting, monitoring and improvements. AI model and messaging-channel usage costs depend on conversation volume.
Book a free consultation. Share a sample of your common customer questions and we will propose scope, channels and a plan for a first version.
Ready to get started with Chatbots & Virtual Assistants?
Book a free consultation — we'll map a secure, practical path forward.