Grounded answering
Responses drawn from approved content with abstention when the answer is not there.
Conversation that resolves
AI Chatbots & Conversational AI
Conversational systems that answer from approved content, take real actions and hand over cleanly.
What this is
The failure mode of older chatbots was the dead end: a decision tree that could not answer and could not escalate. We build conversational systems on retrieval and tool calling, so they answer from your approved content, perform account actions where permitted, and hand to a human with a written summary when they should.
The problem
What this service addresses
If more than one of these is familiar, there is usually a case worth scoping.
- The existing bot answers three questions and funnels everything else into a ticket.
- Customers wait hours for a first response outside business hours.
- The bot cannot see order, account or booking state, so it cannot actually help.
- Handover loses the conversation, and the customer repeats everything to an agent.
Scope
What we deliver
Every item below is a deliverable you receive, not an activity we perform.
- Conversational agent grounded in your help content, policies and catalogue
- Deployment on the channels you use: web, WhatsApp, email and in-app
- Tool access for real actions such as order status, bookings and account updates, within permissions
- Human handover carrying a written summary and the full transcript
- CRM and helpdesk integration so conversations land where your team works
- Intent, deflection and gap analytics showing what it could not answer
- Tone of voice and escalation policy configured with your team
Capabilities
What the system does
Multi-channel deployment
One agent, consistent behaviour, across web chat, WhatsApp, email and in-app surfaces.
Action taking
Looks up orders, reschedules bookings and updates details through your APIs under scoped access.
Human handover
Escalation on request, on sentiment or on confidence, with a summary the agent can act on.
Multilingual conversation
Handles the languages you sell in without maintaining a separate bot per language.
Analytics and gap reporting
Intent volumes, deflection rate and a ranked list of unanswered questions to fix.
Applied
Where it is used
Each of these is a bounded job with a measurable result, which is how we prefer to scope a first build.
01
Tier-1 support resolution
Resolves the repetitive majority from approved content and escalates the rest with context.
02
Order and booking self-service
Status, changes and cancellations handled in conversation, without a ticket.
03
Pre-sales questions
Answers specification, pricing and availability questions and routes genuine intent to sales.
04
Onboarding guidance
Walks new users through setup, answering in context instead of linking to a manual.
05
After-hours cover
Handles nights and weekends, resolving what it can and queueing the rest with full context.
Architecture
How it is put together
An indicative architecture. The final design follows your systems, data boundary and constraints.
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01
Channels
Web widget, WhatsApp Business API, email, in-app and social inboxes.
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02
Knowledge layer
Retrieval over help content, policies, product data and documentation.
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03
Action layer
Typed tools over your order, booking, account and CRM APIs with scoped credentials.
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04
Conversation management
State, context retention, clarification handling and escalation triggers.
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05
Handover
Routing into your helpdesk with transcript, summary and suggested next action.
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06
Analytics
Intent classification, deflection measurement, satisfaction signals and content gap reports.
Security & governance
Controls we build in
Access, privacy and oversight are part of the build rather than a later hardening phase.
- Answers limited to approved content; the agent escalates rather than improvising policy.
- Account actions require identity verification appropriate to the action risk.
- Clear disclosure that the customer is talking to an automated agent.
- Transcript retention and personal-data handling aligned to your privacy policy.
- Escalation always available on request, with no forced containment.
Delivery
Our approach
How we run the engagement
Discovery
Process walkthroughs, data review, constraints and a written scope you sign off before build.
Architecture
Data model, integration boundaries, hosting and the security model, agreed up front.
Proof of concept
A narrow build on your real data against an agreed quality bar, so the go-ahead is evidence-based.
Development
Two-week increments, each ending in a working deployment and a review.
Testing
Automated coverage on critical paths, evaluation sets for AI behaviour, acceptance testing with your users.
Deployment
Staged rollout into your infrastructure with monitoring and a tested rollback path.
Monitoring & support
Quality, cost and latency tracking after launch, with handover documentation or an ongoing retainer.
Proven work
Products we have built and sold
We are product builders as well as a services team. These are our own commercial platforms, not client references.
Digital sales & support agent
SIZH Virtual Agent
A virtual digital agent for sales, support and reception — trained on your business, live on WhatsApp, web, voice and email.
View product Mobility platformRideOn
A ride-hailing and fleet management platform, now with agentic dispatch, driver support and demand intelligence.
View product Multivendor marketplaceUniBooker
A configurable multivendor service-booking marketplace with agentic onboarding, matching and support.
View product
Questions
AI Chatbots & Conversational AI — FAQs
The questions we are asked most often about this service.
How is this different from the chatbot we already have?
Two things: it answers from your actual content through retrieval rather than a scripted tree, and it can call your systems to take action. It also escalates properly instead of dead-ending.
What deflection rate is realistic?
It depends on your ticket mix, so we measure before promising. We analyse a sample of historical conversations and estimate from that, then report actual deflection once live.
Will customers know it is AI?
Yes. We disclose it, and we keep escalation to a human available at any point. Hiding it damages trust and tends to backfire.
Can it handle our languages?
Generally yes for widely supported languages. We test quality per language against your content before committing, since performance varies.
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