We build AI products — not features bolted on.
Trusted by
AI products and systems we build
LLM-Powered Applications
Applications where an LLM is the core product engine — document Q&A, AI writing tools, intelligent search, contract analysis, code review tools, research assistants. Full stack: LLM integration, RAG layer, UI, and operational infrastructure.
AI Agents
Autonomous systems that use tools, maintain memory, and complete multi-step tasks without human direction. Customer service, sales, document processing, and ops agents.
Agentic AI Pipelines
Multi-agent orchestrated systems — specialist agents coordinated by an orchestrator for complex workflows that exceed what a single agent can handle.
AI Chatbots
LLM-powered conversational interfaces — customer service, sales, internal ops, healthcare. RAG-grounded, multi-channel, intelligent handoff.
RAG Systems & Knowledge Bases
Connect your LLM to private data — product documentation, contracts, case history, technical manuals. Semantic retrieval, hybrid search, context-aware response generation.
Machine Learning Models
Custom models for prediction, classification, recommendation, computer vision. Trained on your data, deployed on SageMaker, monitored continuously.
AI Product Integration
AI Infrastructure & LLMOps
Who hires us
CTOs building AI-native products, not AI features
Enterprises adding AI to existing systems
Startups building their first AI product MVP
Regulated industries with data residency requirements
Not sure which AI product type is right for your use case?
45 minutes. We'll review your concept, recommend the right architecture — RAG, agent, fine-tuned model, or something simpler — and give you a clear view of cost and risk.
Platform-agnostic.
Evaluation-first.
Full-stack delivery.
Platform-agnostic, deployed in your cloud
We've been doing this since the technology was new
Evaluation frameworks, not just vibes
We cover the full stack
Building an AI productor adding an AI feature?
| Dimension | AI Feature Add-On | AI Product (EB Pearls) |
|---|---|---|
| Core value proposition | Feature within existing product |
✓ AI capability is the product itself
|
| Evaluation framework | Ad-hoc, manual review |
✓ Automated test suites, regression on every deploy
|
| LLMOps requirements | Minimal — single API call |
✓ Prompt versioning, output monitoring, cost controls
|
| Model selection | One model for all tasks |
✓ Right model per task — cost, latency, capability
|
| Data residency | Shared cloud infrastructure |
✓ Your AWS VPC — no data leaves your environment
|
| Typical investment | AUD $25K–$60K |
AUD $60K–$400K+ depending on complexity
|
Our AI platform stack
★ marks our preferred production choice for Australian enterprise AI deployments.
LLM Platforms
- ★ AWS Bedrock
- ★AWS SageMaker
- ★Anthropic Claude 3.5
- OpenAI GPT-4o / o1
- Meta Llama 3.3
- Google Gemini 2.0
AI Frameworks
- ★ LangGraph
- ★LangChain
- LlamaIndex
- Hugging Face
Vector & Knowledge
- ★pgvector / Pinecone
- AWS OpenSearch
- ★LangSmith
- Weaviate
AI Backend
- ★ Python / FastAPI
- Docker + AWS ECS
- AWS Lambda
- Redis + DynamoDB
Real AI products.
Production metrics.
Product Manager, Coposit
Director, Care Careers
Marketing Manager, Rotech
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.
Product owner, BAXTA
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.
Director, Gondwana link
Founder, Whitebow Gift registry
Your project is 100% protected
EB Pearls signs an NDA before any technical discussion begins. Your code, architecture, and data remain entirely yours.
✓ ISO 27001
✓ ISO 9001
✓ NDA First
From discovery
to production AI
AI Discovery & Architecture
Define the AI problem precisely. Select models and deployment architecture. Design evaluation framework. Assess data readiness. Architecture document with fixed-price quote.
Weeks 1–3
Prototype & Evaluation
Working prototype against representative inputs. Initial evaluation suite. Validate the approach before full investment. Identify model and architecture risks early.
Weeks 4-6
Product Development
Build the full product — AI layer, integrations, UI, backend, monitoring. Continuous evaluation. Weekly demos. Staging deployment for client review.
Weeks 7-16+
Production & LLMOps
Deploy to your cloud. Set up monitoring, alerting, cost controls. Evaluation cadence. Handover documentation and operational runbooks.
Final 3 weeks
How to work with us
Fixed-Price AI Project
Defined scope, price, and timeline. Best for well-scoped AI products where the use case, data, and success metrics are clear before we start.AI Product Retainer
Dedicated AI engineering team on your roadmap continuously. Best for products iterating on live AI systems, expanding to new use cases, or managing ongoing LLMOps.AI Discovery Sprint
2-week fixed engagement to define your AI architecture, select models, design your evaluation framework, and produce a costed build plan before you commit.Every question answered.
LLM-powered applications, AI agents, agentic AI pipelines, RAG systems, ML models, computer vision, voice AI, and document intelligence. Full AI product stack — not just API wrappers.
The operational practice for AI products — prompt versioning, output monitoring, evaluation frameworks, cost management, and incident response. AI products degrade differently than traditional software.
Build your AI product right.
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.