AI chatbots that handle real conversations —not just planned ones.

LLM-powered chatbots connected to your actual business data and systems. Not rule-based decision trees that break on unexpected questions. Conversational AI that understands context, retrieves accurate information, and hands off to humans intelligently.

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50+

Chatbots built

Since 2022

Building LLM chatbots

ISO 9001 & 27001

Certified

Clutch

Trusted by

Six chatbot types
we build and deploy

Each type is purpose-built for its domain — with the right integrations, compliance requirements, and handoff logic from day one.

Customer Service Chatbots

Handle tier-1 support at scale — order status, returns, account queries, product questions, booking changes. Connected to your CRM, order management and knowledge base. Human handoff when complexity exceeds threshold. Typical containment rate 65–80% on first deployment.

Sales & Lead Qualification

Engage inbound leads 24/7, qualify intent and budget, answer product questions, book demos directly into your calendar, push qualified leads to CRM.

Internal HR & IT Helpdesk

Answer employee questions about policies, payroll, leave, onboarding, and IT procedures. Connected to your HRIS and IT ticketing system. Available 24/7, consistent, auditable.

Healthcare & Clinical

Patient-facing chatbots for appointment booking, pre-consultation questionnaires, medication reminders, and health information. Built with Australian Privacy Act, ADHA, and My Health Records Act compliance from day one.

E-Learning & Education

Tutoring chatbots that explain concepts, answer curriculum questions, provide worked examples, track understanding gaps, and adapt difficulty. Built for education platforms, universities, and corporate L&D.

Financial Services Chatbots

Compliant chatbots for banking, insurance, and wealth management — product questions, applications, statement explanations, and advisor routing. Fully auditable conversation logs.

Who hires us to
build AI chatbots

Customer experience leaders with repetitive support volume

65–80% of your tickets are the same 20 questions. An AI chatbot connected to your real systems resolves those without a human — consistently, at any hour, on any channel.

Marketing and sales teams losing leads after hours

Inbound leads arrive at 11pm and get a follow-up 18 hours later. A sales chatbot qualifies intent, answers product questions, and books the demo — while your team sleeps.

Healthcare and financial services with compliance requirements

Data residency in Australia, ADHA or ASIC compliance obligations, PII handling requirements. We build chatbots that comply from day one — not as an afterthought.

Enterprises replacing rule-based chatbots that have hit their ceiling

Your existing chatbot breaks on anything outside its decision tree. You're maintaining hundreds of intents. An LLM-powered RAG chatbot handles the long tail of real conversations without constant intent maintenance.

RAG-first.
Data stays in Australia.
Handoffis a feature.

Four things that separate an EB Pearls AI chatbot from a generic LLM wrapper.

RAG-first — chatbots that know your business

We index your product documentation, FAQs, policies, and knowledge base into a vector database. The chatbot retrieves relevant context before generating every response. Accurate, grounded answers about your specific products — not generic LLM outputs that hallucinate.

Data stays in Australia, on your infrastructure

We deploy on AWS ap-southeast-2 (Sydney) by default. Your conversation data, customer information, and business knowledge never leave Australian infrastructure. Essential for healthcare, financial services, and any business with Australian Privacy Act obligations.

Human handoff is a feature, not a failure

We design the handoff experience from the start — when to escalate, how to pass context, how to warm-transfer conversation history. The chatbot knowing its limits and escalating gracefully is a sign of good engineering, not inadequacy.

Multi-channel from a single backend

One AI backend, deployed across website, WhatsApp, Slack, Teams, mobile app and SMS. Consistent responses, centralised knowledge updates, unified analytics. We build the channel abstraction layer so you're not maintaining separate chatbots for each channel.

Already have a chatbot?
Here's what's missing.

Rule-based chatbots work for narrow, unchanging flows. They hit a hard ceiling the moment users go off-script.

Capability	Rule-Based Chatbot	EB Pearls AI Chatbot
Handles unexpected questions	✗ Falls back to "I don't understand"	✓ Reasons through novel questions with context
Answers questions about your specific products	✗ Only hardcoded responses	✓ RAG retrieval from your actual knowledge base
Maintains conversation context	✗ No memory between turns	✓ Full conversation history in context
Updates when your content changes	✗ Manual intent re-training required	✓ Re-ingest documents; knowledge updates automatically
Integrates with live business systems	Limited — static data only	✓ Real-time API calls to CRM, orders, inventory
Typical containment rate	30–45% for narrow flows	65–80% with comprehensive knowledge base

Our AI chatbot stack

★ marks our preferred production choice for Australian deployments.

AI & LLM Layer

★ AWS Bedrock
★ Claude 3.5 Sonnet / Haiku
OpenAI GPT-4o / mini
Amazon Lex (voice)

RAG & Knowledge

★ LangChain
★ pgvector / Pinecone
LlamaIndex
AWS OpenSearch
SharePoint / Notion ingestion

Channels

★ Web widget (React)
★ WhatsApp Business API
Slack / MS Teams
SMS via Twilio
iOS & Android SDK

Analytics & Ops

★ LangSmith
★ Custom containment dashboard
FastAPI backend
DynamoDB (session state)
AWS CloudWatch

Real chatbots.
Measurable outcomes.

Two recent deployments. Numbers from the first 90 days in production.

We’re extremely impressed with EB Pearls’ work, technical skill, and ability to adapt, iterate, and learn new skills. Their high attention to detail and eternally positive attitude make working with EB Pearls a wonderful experience.

Sarah Scaife

Product owner, BAXTA

We were very happy with all of the work undertaken during each phase of our new website production. All EB Pearls personnel were knowledgeable, approachable and helpful – we were also most impressed with the professionalism and responsiveness they demonstrated throughout the process.

Coral Funnell

Marketing Manager, Rotech

The website that EBPearls developed for Gondwana Link does everything we asked for. It is very easy to use in the backend and the design is fresh and clean which is what we wanted. EBPearls build customised ‘modules' and they all work well and are very intuitive to use. I needed very little training to be able to use the back end.

Amanda Keesing

Director, Gondwana link

The client is delighted with EB Pearls’ ability to deliver within the established deadlines through a professional approach. They use various communication tools to ensure a solid project management experience. The team also praises their overall good service and constant commitment to learning new things.

John Walton

EB Pearls provided great clarity on the scope, timeline, design, and stages of developing our app, which gives users access to a database of more than 1,000 roles. They stuck rigidly to our production schedule and delivered as promised.

Mike Fields

Director, Care Careers

I’m a solo entrepreneur and not very good with tech. EB Pearls made it easy, mentoring me through everything. Highly recommend!

Charmaine Hilario

Founder, Whitebow Gift registry

After sharing my ideas and concept with EB Pearls, they formulated a design plan and implementation roadmap. They considered the software's functionality within our target market's dynamics and proceeded to develop a comprehensive product using Flutter.

John Olapurath

From knowledge audit
to live chatbot

Stage 01

Discovery & Knowledge Audit

Map conversation flows. Audit your existing knowledge base. Identify integration requirements. Define containment targets. Establish handoff criteria and compliance requirements.
Weeks 1–2

Stage 02

Knowledge Indexing & RAG

Ingest and structure your content. Build the vector index. Configure retrieval. Test accuracy on representative questions. Identify knowledge gaps before launch.
Weeks 3-4

Stage 03

Integration & Channel Build

Wire live system integrations. Build channel implementations. Implement analytics. Build and test human handoff flows. Train on edge cases and failure modes.
Weeks 5-10

Stage 04

Deployment & Optimisation

Staged rollout — low-traffic channels first. Monitor containment rate and satisfaction. Update knowledge base based on conversation analysis. Full deployment and handover.
Final 2 weeks

How to work with us

Fixed-Price Project

Defined scope, price and timeline. Best for well-scoped chatbot builds where the knowledge base, channels, and integrations are clear upfront.

AUD $25,000–$120,000+

Build + Optimise Retainer

We build the chatbot, then stay on for 3 months post-launch to optimise containment rate, expand the knowledge base, and add channels as you scale.

From AUD $8,000/month

Knowledge Base Audit

We assess your existing chatbot or knowledge base, identify gaps, and produce a remediation plan before any rebuild. Fixed fee, 2-week turnaround.

From AUD $8,500

Every question answered

Can't find what you need?

A rule-based chatbot follows a decision tree — it can only handle questions it was programmed to anticipate. An AI chatbot uses an LLM to understand natural language, handle unexpected questions, maintain context, and generate human-quality responses. AI chatbots handle the long tail of real conversations that rule-based systems fail on.

Focused customer service chatbot with RAG: 6–10 weeks. Multi-channel with live integrations and handoff: 10–16 weeks. Timeline is largely driven by the state of your existing knowledge base.

Website, mobile apps (iOS and Android), WhatsApp Business, Facebook Messenger, Slack, Microsoft Teams, SMS, and voice. Multi-channel from a single AI backend is standard in our architecture.

Yes — we design handoff logic that detects when confidence is low, when the user requests a human, or when the topic is outside scope. Handoffs pass full conversation context so the human agent has everything they need from the moment they pick up.

Yes. One AI backend, deployed across website, WhatsApp, Slack, Teams, mobile app and SMS. Consistent responses, centralised knowledge updates, unified analytics — you're not maintaining separate chatbots for each channel.

We build document re-ingestion pipelines that automatically update the vector index when your source documentation changes. For live system data (orders, inventory, accounts), the chatbot queries APIs in real time — so that data is always current.

Single-channel RAG chatbot: AUD $25,000–$55,000. Multi-channel with live integrations: $55,000–$120,000. Enterprise with voice, multi-language and compliance: from $120,000. Fixed-scope quotes after a free consultation.

For well-scoped customer service chatbots with comprehensive knowledge bases, we typically achieve 65–80% containment rate in production. The rate depends on knowledge base quality, scope definition, and how well edge cases are handled. We'll project your specific rate during the discovery phase.

We use RAG (Retrieval-Augmented Generation): your documentation, FAQs, and policies are indexed into a vector database. The chatbot retrieves relevant context before generating every response — grounded, accurate answers. We also integrate with live systems via API tool calls for real-time data like orders and accounts

We deploy on AWS Sydney (ap-southeast-2) so data stays onshore. We implement retention policies, opt-out mechanisms, and PII redaction from logs. For healthcare we apply additional controls aligned with ADHA standards and the My Health Records Act.

We design confidence thresholds that trigger specific responses when the chatbot is uncertain — not hallucinated answers. Below threshold, the chatbot either says it doesn't know and offers alternatives, or escalates to a human agent with full conversation context.

Yes. We have specific experience with Australian Privacy Act, ADHA standards, and My Health Records Act compliance for healthcare. For financial services we build fully auditable conversation logs for regulatory compliance and stay within ASIC guidance on digital advice.

1 Your Information

2 Book Meeting

3 Confirmation

Build your AI chatbot.

45 minutes. We'll review your use case, assess your knowledge base readiness, and give you a realistic view of what a chatbot can and can't do for your business. No sales deck.

What to expect on your call

What to expect

1 Share a few details
Complete the form with your contact details and what you need help with.
2 Book your free discovery call
Once you submit the form, choose a time that suits you for your discovery call.
3 Privacy comes first
Sign an optional NDA to ensure the highest privacy level and protection of your idea.
4 Discovery call
We’ll discuss your goals, the support you need and answer your questions. If we’re a good fit, we’ll outline the next steps.

What to expect

1 Share a few details
Complete the form with your contact details and what you need help with.
2 Book your free discovery call
Once you submit the form, choose a time that suits you for your discovery call.
3 Privacy comes first
Sign an optional NDA to ensure the highest privacy level and protection of your idea.
4 Discovery call
We’ll discuss your goals, the support you need and answer your questions. If we’re a good fit, we’ll outline the next steps.

AI chatbots that handle real conversations —not just planned ones.