RAG Development Services
for Perth, Melbourne, Sydney, Brisbane businesses.
We build retrieval augmented generation systems for Australian businesses. Your AI stops guessing and starts answering from your actual documents. Policies, contracts, manuals, client records.
Custom RAG development. Deployed in your environment. Every answer cites the source. Your data never leaves your network.
Retrieval augmented generation services — AI that reads your documents and answers with proof
Retrieval Augmented Generation (RAG) is the technology that makes AI actually useful for business. Instead of generating answers from its general training, the AI searches your specific documents first, then constructs an answer grounded in your actual data.
Every answer comes with source citations: the document, the page, the section. Your team can verify any answer in seconds. When the information is not in your documents, the AI says so instead of making something up.
We build these systems for Australian businesses. Deployed within your environment, connected to your document sources, secured with proper access controls. Your data never leaves your network.
Why custom RAG development changes how your team works
AI that answers from your data, not its imagination
Standard AI models generate answers from their training data. That is fine for general questions, but dangerous for business ones. When your staff ask about a specific policy, contract clause, or product specification, approximate or invented answers are worse than no answer.
RAG systems solve this. Before the AI generates a response, it searches your actual documents and data. It finds the relevant sections, then constructs an answer grounded in those specific sources. Every answer cites where it came from.
If the information is not in your documents, the system says so. No confident fabrication. That is the difference between AI you can trust and AI you have to double-check. Learn more about <a href="/knowledge/preventing-ai-hallucinations">how RAG prevents AI hallucinations</a>.
Search thousands of documents in seconds
Your business has years of accumulated knowledge. Policies, procedures, manuals, contracts, proposals, specs, meeting notes, compliance documents. Staff spend 20 minutes searching when the answer exists on page 47 of a document nobody remembers. A RAG system indexes all of it and searches semantically, not just by keywords. So "What is our refund policy for late cancellations?" finds the right answer even if the document says "cancellation fee" instead of "refund."
Average retrieval time: under 5 seconds. That is 5 seconds versus 20 minutes. Multiply that across every question, every day, every team member.
Every answer comes with proof
The best thing about a RAG system is traceability. Every answer includes the source document, page number, and relevant section. Your team can verify any answer in seconds.
This is critical for compliance, legal, and regulated industries. When the AI says "Our policy requires 30 days notice", your team can click through to the exact clause in the exact document. Auditors and compliance officers can see exactly where information came from.
Source citations also build trust with your team. People use AI tools they can verify. They abandon tools they cannot.
Your knowledge base updates automatically
Documents change. Policies get updated. New contracts are signed. Old procedures are replaced. If your AI is working from a static snapshot, it gives stale answers.
Our RAG systems include automatic re-indexing. When a document is updated in your SharePoint, Google Drive, or internal system, the knowledge base re-indexes it. The AI always works from the latest versions.
You can also see what is in the index, when each document was last processed, and flag documents for review. Full visibility into what the AI knows and does not know.
Your documents never leave your environment
Your business documents contain sensitive information. Contracts, financial data, client details, internal policies. Uploading them to a public AI service is not an option for most businesses.
We deploy RAG systems within your environment. Documents are indexed and stored in your infrastructure: Azure, AWS, or on-premise. The AI model processes queries without exporting your data. Access controls ensure users only see documents they are authorised to see.
For Australian businesses with data residency requirements, we deploy entirely within Australian data centres. Your data stays in Australia. See our <a href="/knowledge/secure-rag-on-aws">guide to secure RAG on AWS</a>.
Get Started
Want to see custom RAG development in action with your documents?
Send us a sample of your documents and we will show you what our retrieval augmented generation services can do with them. Free assessment, no commitment.
RAG Systems by Use Case
For small and medium businesses, RAG usually means different ways of structuring how an AI system finds company information and uses it in answers. In plain English: the AI does not rely only on its training. It first searches your business documents or systems, then uses that retrieved information to answer.
Basic Document RAG
Best for: PDFs, policies, manuals, FAQs, contracts, internal docs.
How it works: Upload documents → split into chunks → store in a vector database → user asks a question → system retrieves relevant chunks → LLM answers from those chunks.
Good when: You want a simple internal knowledge assistant. Content changes regularly. Low to moderate complexity. If your team just needs to chat with their documents, that is exactly what we build.
Document chatbots →Website + Document RAG
Best for: Customer support, sales FAQ, service information, proposal support.
How it works: Combines website content and uploaded files. Useful for a public-facing chatbot plus internal docs.
Good when: Your business has both public info and internal reference docs. Sales and support teams need one assistant that covers both. We build internal knowledge assistants that pull from every source your team relies on.
Internal knowledge assistants →Structured Data + Document RAG
Best for: ERP, CRM, bookings, invoices, jobs, client records.
How it works: Retrieves from documents and business systems. Some answers come from a database or API, not just text chunks. For example: "What is the latest invoice status for client X?" or "Show project notes and related contract terms."
Good when: Answers need live business data. Not everything is in PDF files. When your knowledge lives across multiple systems, a unified search changes the game.
Multi-source knowledge search →Hybrid RAG
Best for: Better search quality, larger document sets, fewer missed answers.
How it works: Combines vector search with keyword search. Sometimes adds metadata filters. For example: search by meaning plus exact terms like invoice number, suburb, project code, or customer name.
Good when: Documents contain exact business terms. Users search using abbreviations, codes, product names. This is often the best practical option for SMEs. Want a chatbot that actually finds what your team is looking for? Hybrid search is usually how we get there.
Document chatbots →Agentic RAG
Best for: Multi-step tasks, workflow support, more advanced assistants.
How it works: AI decides what to retrieve. May search multiple sources, call APIs or tools, summarise and then take action. For example: read email → check CRM → read quote template → draft response → create follow-up task.
Good when: You want more than Q&A. The assistant needs to do work, not just answer. Learn how agentic RAG works, or see our AI agents service.
AI agents for business →Permission-Aware RAG
Best for: Teams with sensitive data: HR, finance, legal, client-specific records.
How it works: Retrieval respects user roles. Staff only see what they are allowed to see.
Good when: Not all employees should access all data. Privacy matters. Very important for real business use. If policies and compliance are the main concern, we have a dedicated solution for that.
Policy & procedure AI →Multi-Source Enterprise-Style RAG
Best for: Growing businesses with multiple systems and messy data.
Sources may include: SharePoint, Google Drive, Dropbox, CRM, ERP, email, helpdesk, SQL databases, internal web apps.
Good when: Knowledge is spread everywhere. One source alone is not enough. We build systems that search across all of them at once.
Multi-source knowledge search →
AI-powered document search across 4,000+ mining procedures
We built a RAG-powered search system for a mining company. Workers ask questions in plain English and get accurate answers from thousands of safety and procedure documents.
Read the full case study →Custom RAG development by industry
Our retrieval augmented generation services are most valuable in document-heavy industries where staff need fast, accurate answers from large knowledge bases.
Professional Services
Lawyers, consultants, and accountants searching contracts, proposals, and compliance documents. Staff find answers in seconds instead of hours, and every answer cites the exact clause or section.
Mining & Resources
Safety procedures, geological specs, compliance requirements, and equipment manuals. All searchable in seconds. Field teams get accurate answers on-site without calling the office.
Healthcare
Clinical guidelines, treatment protocols, drug information, and administrative policies, all accessible through natural language questions. Staff get sourced, verifiable answers for patient care decisions.
Government & NFPs
Policy documents, grant guidelines, regulatory frameworks, and operational procedures. Staff and field workers get instant answers instead of searching through document archives.
Education & Training
Course materials, assessment criteria, institutional policies, and research resources. Students and staff search with natural language and get accurate answers with source references.
Manufacturing
Equipment manuals, quality standards, safety procedures, and supplier specs. Production teams get instant answers during shifts instead of waiting for engineering or quality staff.
From documents to answers in weeks
Our RAG development process is structured to get your system live. Real data, tested accuracy, and proper security.
What changes when your team has instant answers
Custom RAG development transforms how your business accesses and uses its own knowledge.
Minutes → Seconds
Questions that take 20 minutes of searching get answered in under 5 seconds. Multiply that across every team member, every day.
Verified Accuracy
Every answer comes with source citations. Your team verifies information in clicks, not hours. Auditors can trace any answer to the source document.
Data Stays Internal
Deployed within your environment. Documents are indexed and stored in your infrastructure. Nothing is shared with public AI services.
Faster Onboarding
New staff ask the AI instead of interrupting colleagues. Consistent, accurate answers from day one, regardless of who is training them.
Always Current
Automatic re-indexing when documents change. The AI always works from the latest version of your policies, procedures, and data.
Usage Insights
See what questions your team asks most. Identify documentation gaps. Track which departments use the system most and where the biggest time savings are.
Our compliance team used to spend half their day searching through policy documents. The RAG system answers those questions in seconds — with exact citations. We estimate it saves 15 hours a week across the team.
Why HELLO PEOPLE
We build, not just advise
We write the code, design the interface, deploy the systems, and support them long-term. No subcontracting, no offshore handoffs.
Fixed-price quoting
You get a clear price before we start. No hourly billing that spirals, no surprise invoices at the end of the month.
Built for Australian business
We understand BAS, super, award rates, Australian privacy law, and the tools local businesses actually use. Xero, MYOB, ServiceM8, Tradify.
Senior team, direct access
You talk to the people building your software. No account managers, no project managers relaying messages, no ticket queues.
Full code ownership
You own everything. The code, the data, the hosting. No lock-in. No proprietary platforms you cannot leave.
Common questions about RAG development services
What is RAG and how does it work?
RAG stands for Retrieval-Augmented Generation. When someone asks a question, the system first searches your documents to find relevant information (retrieval). It then uses that information to generate an accurate, contextual answer (generation). Every answer is grounded in your actual data, with citations back to the source documents. Our retrieval augmented generation services build this entire pipeline for your business. For a deeper explanation, see our <a href="/knowledge/rag-systems-explained">complete guide to RAG systems</a>.
What types of documents can a RAG system handle?
PDFs, Word documents, Excel spreadsheets, PowerPoint presentations, text files, HTML pages, Confluence pages, SharePoint documents, Google Docs, and more. We can also index structured data from databases and APIs. If your business has it, we can almost certainly index it.
How accurate are the answers?
RAG systems are significantly more accurate than standard AI for business-specific questions because every answer is grounded in your actual documents. We tune the system for your specific use case and test against real questions from your team. Typical accuracy rates are 85-95% depending on document quality and complexity.
Is our data safe?
Yes. We deploy RAG systems within your own environment: Azure, AWS, or on-premise. Your documents are indexed and stored in your infrastructure. Access controls ensure users only see documents they are authorised to access. Data never leaves your network. For Australian data residency requirements, we deploy within Australian data centres.
How much does custom RAG development cost?
A focused RAG system (single document source, internal team use) typically starts from $15,000 to $30,000. Enterprise RAG systems with multiple document sources, complex access controls, and customer-facing deployment range from $30,000 to $80,000+. We start with a scoped proof of concept so you see it working before committing to the full build.
How long does it take to set up?
A proof of concept with your actual documents takes 3 to 4 weeks. A full production deployment takes 6 to 10 weeks depending on the volume and variety of documents, access control requirements, and deployment platform.
What happens when a document is updated?
The system automatically re-indexes updated documents. When a file changes in your SharePoint, Google Drive, or other connected source, the knowledge base reflects the latest version. You can also trigger manual re-indexing and see the status of every document in the index.
Can users see which document an answer came from?
Yes. Every answer includes source citations showing the document name, section, and page number. Users can click through to the original document to verify or read more. This is a core feature, not an optional extra.
Get Started
Stop searching. Start asking.
Tell us about your documents and knowledge management challenges. We will show you what a RAG system can do with your data, with a realistic scope and clear price.
Tell Us About Your Documents
What documents does your team search through? What questions do they need answered? We will come back with an honest assessment and realistic scope.
Prefer a quick chat? Call 0425 531 127 – we're Perth-based and we answer the phone.