Generative AI Development

Generative AI Development Services in Melbourne & Sydney

OpenMalo builds custom generative AI applications powered by GPT-4o, Claude 3.5 Sonnet, Gemini 1.5, and open-source LLMs — grounded in your proprietary data through RAG pipelines and fine-tuning. Our Melbourne AI engineering team has delivered 60+ GenAI projects for Australian enterprises, including intelligent document processors, AI writing assistants, autonomous agents, and multi-modal applications.

60+GenAI Projects Delivered
13+Years Experience
10×Avg Productivity Gain
98%Output Accuracy Rate
9:41 Dashboard Good morning, OpenMalo AU Projects 300+ Clients 180+ Rating 4.9 Weekly Activity Active Projects iOS Banking App AI Dashboard Tech Stack React Flutter AI Node.js Python Swift Kotlin Client Satisfaction 99% 🚀 On-time Delivery 13+ yrs exp 🔒 NDA Protected Your IP is safe always ✓
GPT-4o & Claude 3.5
RAG & Fine-Tuning
Data Sovereign Deployment

What You Get With Our Generative AI Development Services

🤖

Which AI model should we use — GPT-4o, Claude, or Gemini?

We evaluate every major model against your specific use case, latency requirements, context window needs, cost profile, and data privacy constraints. We are not tied to any single vendor — we recommend the model that genuinely fits your requirements best.

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How do we get the AI to use our own company knowledge?

We build RAG (Retrieval-Augmented Generation) systems that retrieve relevant context from your documents, databases, and knowledge bases before generating a response — dramatically reducing hallucinations and ensuring answers are grounded in your actual business information.

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Can the AI be trained on our proprietary data and tone of voice?

Yes — we design fine-tuning pipelines on your labelled datasets and Supervised Fine-Tuning (SFT) workflows for open-source models (LLaMA 3, Mistral, Phi-3). This produces domain-specific accuracy and a brand-consistent tone that generic models cannot replicate.

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How do we keep our business data off third-party AI servers?

We deploy open-source LLMs (LLaMA 3, Mistral, Phi-3) on your own AWS, Azure, or on-premise GPU infrastructure via vLLM or Ollama. No data leaves your environment. For API-based models, we review data retention policies and implement PII scrubbing before any data leaves your systems.

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How do you prevent the AI from giving wrong or harmful answers?

We implement constitutional AI guardrails, source citation with confidence scoring, output validation layers, semantic similarity thresholds for RAG retrieval, and human-in-the-loop review queues for high-stakes decisions. Hallucination rates are measured and reported in pre-production evaluation.

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Can you integrate generative AI into our existing software?

Yes — we specialise in adding GenAI capabilities to existing systems: smart search to your website, an AI assistant to your CRM, document summarisation to your DMS, or intelligent drafting to your ERP. Integration is handled via clean, versioned APIs with no disruption to existing workflows.

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How do we monitor AI output quality in production?

We configure LangSmith, Arize AI, or Weights & Biases for real-time output quality scoring, latency tracking, token cost monitoring, and anomaly detection. You receive weekly dashboards showing accuracy trends, user feedback signals, and cost-per-query metrics.

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How do you ensure GenAI apps comply with Australian regulations?

All GenAI solutions comply with the Australian Privacy Act 1988, the CSIRO Data61 AI Ethics Framework, and relevant sector regulations (APRA CPG 234, TGA where applicable). We conduct bias audits, implement explainability layers, and document model decisions for regulated industries.

Australia's Trusted Generative AI Development Partner

OpenMalo has delivered 60+ production generative AI projects for Australian enterprises, government agencies, and scale-ups — ranging from intelligent document processors that extract structured data from unstructured legal contracts, to autonomous AI agents that research, draft, validate, and submit regulatory reports without human intervention. Our Melbourne AI engineering team includes former research scientists who have published in top ML venues and engineers with production experience deploying LLMs at scale.

We go significantly beyond simple API integration. We architect multi-stage RAG pipelines with hybrid semantic-lexical retrieval, design fine-tuning workflows on proprietary datasets, build robust prompt engineering systems with automated regression testing, and deploy production-ready GenAI applications with the data sovereignty controls Australian businesses operating under the Privacy Act 1988 require. Every engagement includes a model evaluation report, hallucination rate baseline, and cost projection before development begins.

OpenAI, Anthropic, Google & AWS Bedrock certified partners
RAG architecture with pgvector, Pinecone & Weaviate
Fine-tuning pipelines for LLaMA 3, Mistral & Phi-3
On-premise vLLM & Ollama deployment for data sovereignty
LangSmith & Arize AI production monitoring configured
Privacy Act 1988 & AI Ethics Framework compliant builds

Get a Free Generative AI Consultation

Tell us about your project and we'll respond within 24 hours.

Full-Spectrum Generative AI Development Services

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Intelligent Document AI & RAG Systems

AI-powered document extraction, classification, summarisation, and Q&A for enterprise document workflows — contracts, invoices, compliance reports, and technical manuals processed at scale.

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Autonomous AI Agent Development

Multi-step autonomous agents completing complex business tasks — research, drafting, validation, approval routing, and reporting — with human-in-the-loop checkpoints where required.

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AI Content Generation Platforms

Automated content creation systems for marketing copy, product descriptions, compliance reports, and personalised customer communications — trained on your brand voice and style guide.

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Semantic Search & AI-Powered Discovery

Enterprise search using vector embeddings and RAG that understands meaning and intent, not just keywords — replacing legacy full-text search with contextually intelligent retrieval.

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Multi-Modal AI Application Development

Applications combining text, image, audio, and video AI capabilities using GPT-4o Vision, DALL-E 3, Whisper, and Sora — for quality control, content creation, and accessibility tools.

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LLM Integration & API Development

Add generative AI capabilities to your existing software, mobile app, or website via clean, versioned API integrations — with rate limiting, cost controls, and output caching built in.

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Technologies We Use

Industry-leading tools and frameworks chosen for performance, scalability, and long-term maintainability.

LLMs
GPT-4o Claude 3.5 Sonnet Gemini 1.5 Pro LLaMA 3
Frameworks
LangChain LlamaIndex Haystack
Vector DBs
Pinecone Weaviate pgvector
Deployment
AWS Bedrock Azure OpenAI GCP Vertex AI
On-Premise
vLLM Ollama Hugging Face TGI
Monitoring
LangSmith Arize AI Weights & Biases

Our Generative AI Development Process

01

Use Case Discovery & Model Evaluation

We run a structured AI discovery workshop to define the GenAI use case, data sources, privacy requirements, and success metrics — then evaluate and benchmark candidate models against your specific data before selecting the architecture.

02

RAG Architecture or Fine-Tuning Design

We design and prototype the retrieval pipeline, vector store schema, embedding strategy, or fine-tuning dataset — building a working proof of concept that demonstrates measurable accuracy before full development begins.

03

Production Development & Output Evaluation

Iterative development with rigorous automated evaluation measuring accuracy, relevance, hallucination rate, and latency against baseline benchmarks. Every sprint includes an output quality report showing measurable progress.

04

Deployment, Monitoring & Retraining Plan

Production deployment with real-time output quality monitoring via LangSmith or Arize AI. We deliver a documented retraining schedule and model version management plan so the system improves over time rather than degrading.

Why We're the Right Partner for Generative AI Development

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Proven Track Record

Consistently rated as a top technology company in Australia — backed by verified client reviews on Clutch and GoodFirms.

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NDA & IP Protection

We sign an NDA before any discussion. All IP belongs to you — no shared code, no reuse on completion.

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Full Transparency

Access to project management tools, weekly progress reports, and live sprint demos throughout delivery.

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Australian Based

Melbourne and Sydney offices with real people you can meet in your time zone. Invoiced in AUD.

Fast Delivery

Agile delivery with fortnightly demos so you see progress, give feedback, and stay in control at every sprint.

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Long-Term Partnership

We don't just deliver and disappear. Structured post-launch support and ongoing development partnerships available.

What Our Clients Say

★★★★★

"OpenMalo delivered exactly what we needed — on time, on budget, and with a level of quality that exceeded our expectations. The team communicated brilliantly throughout."

James Mitchell
CEO, HealthTrack Australia
★★★★★

"The technical quality and attention to detail from the OpenMalo team is outstanding. Our users love the end product and our business metrics improved significantly post-launch."

Sarah Robertson
Founder, Digital Ventures Melbourne
★★★★★

"Fast, reliable, and professional. OpenMalo understood our requirements immediately and delivered a solution that has genuinely transformed how we operate. Highly recommended."

David Kumar
CTO, TechForward Sydney

Recognised as a Top Technology Company in Australia

Clutch
Top Developer
Trustpilot
Verified Reviews
GoodFirms
Top Company
Google
Top Rated Agency

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Generative AI Development FAQs

Common questions about our generative ai development services.

Ask Us Anything →
What is Retrieval-Augmented Generation (RAG) and do I need it?
RAG combines a large language model with a retrieval system that searches your documents and databases before generating a response. This grounds the AI in your specific knowledge base, reducing hallucinations dramatically compared to a general-purpose LLM. Most Australian businesses with proprietary data — legal, compliance, product documentation, or customer records — benefit significantly from a RAG architecture.
How much does a generative AI project cost in Australia?
A simple LLM API integration (e.g., adding AI drafting to an existing app) starts from AUD $8,000. A custom RAG system with document ingestion, vector store, and chat interface ranges from AUD $25,000–$80,000. A full autonomous agent platform starts from AUD $60,000. We provide fixed-price proposals after a free scoping session.
How long does it take to build a generative AI application?
A simple LLM integration takes 2–4 weeks. A custom RAG system with document processing, embedding pipelines, and a production interface takes 6–14 weeks. A full autonomous multi-agent platform takes 3–6 months depending on complexity and the number of integrations required.
Can you train the AI on our company's private documents and data?
Yes — two approaches: RAG (indexing your documents into a vector store for real-time retrieval at inference time) or fine-tuning (training a model on your labelled examples to absorb domain knowledge and tone). We recommend RAG for most Australian businesses as it is faster, cheaper, and the knowledge base is easier to update.
How do you prevent generative AI from making up incorrect information?
We implement source citation with confidence thresholds, semantic similarity filters on RAG retrieval, constitutional AI guardrails using self-critique prompting, output validation layers, and human-in-the-loop queues for high-stakes decisions. Hallucination rates are benchmarked and reported before any system goes to production.
Can we deploy the AI on our own servers to keep data private?
Yes. We deploy open-source models (LLaMA 3 70B, Mistral 7B, Phi-3 Medium) on your own AWS, Azure, or on-premise GPU servers using vLLM for high-throughput inference. No data leaves your environment, making this ideal for organisations with strict data sovereignty or PROTECTED-level compliance requirements.
What Australian industries use generative AI in 2026?
Legal (contract review, matter summarisation), financial services (regulatory report generation, client communications), healthcare (clinical documentation, discharge summaries), retail (product description generation, personalised recommendations), government (document processing, constituent communications), and construction (specification extraction from technical drawings).
How do we keep the AI system accurate as our data changes over time?
For RAG systems, we design incremental indexing pipelines that automatically re-embed and re-index documents when they are updated or added. For fine-tuned models, we deliver a documented retraining schedule triggered by data drift metrics or accuracy degradation benchmarks. Model monitoring via Arize AI or LangSmith flags quality regressions before users notice.
Does your generative AI development comply with Australian privacy laws?
Yes. All GenAI applications are built to comply with the Australian Privacy Act 1988 and APP guidelines. We implement data minimisation, purpose limitation, and consent management. We review the data retention and training policies of every third-party API before use, and can deploy fully on-premise for maximum privacy compliance.
What does it cost to run a generative AI application once it is live?
Ongoing costs include API token usage fees (typically AUD $0.001–$0.03 per 1,000 tokens depending on model), vector database hosting (from AUD $70/month), and infrastructure. We build cost optimisation into every architecture using prompt caching, response caching, model routing (cheaper models for simpler queries), and prompt compression to minimise token spend.

Start Your Generative AI Development Project Today

Get a free GenAI consultation from our Melbourne team — we respond within 24 hours with a model recommendation and architecture proposal for your use case.

📧hello@openmalo.com
📞+61 3 9999 0000
📍Melbourne & Sydney, Australia
Mon–Fri, 9am–6pm AEST

Our Presence in Multiple Locations

Local teams across Australia backed by a global delivery centre — giving you the best of both worlds.

Generative AI Development Insights

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July 25, 2026

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