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AI knowledge baseBLACKOPS SOFTWARE / INTEGRATIONS & DATA OPERATIONS
RAG system development.
Build a RAG system that adds relevant business information to AI answers.
Discuss your projectManage knowledge, chat with documents or build RAG?
Staff need to ask questions about a bounded document collection.
Chat with business documentsYou need custom source selection, integration and evaluation.
RAG system development (this service)UNDERSTAND THE SERVICE
What is a RAG system?
RAG stands for retrieval-augmented generation. It retrieves relevant information from selected sources and supplies it to a language model to formulate an answer. Quality depends on both finding the right information and using it correctly. BLACKOPS Software tests those stages separately.
When it is a good fit
RAG suits questions about your documents or frequently changing information when answers must be traceable to sources.
When to take a different approach
RAG cannot repair missing knowledge or solve every calculation or reporting task. Exact figures may be better served by a controlled database query or conventional report.
Compare your options
Choose based on the task, the people involved and what you can maintain.
| Approach | Useful when | What to consider |
|---|---|---|
| Document search | The goal is to find relevant sources. | Users combine and interpret the results. |
| RAG | The goal is an answer based on retrieved sources. | Retrieval and formulation can each introduce errors. |
| Model adaptation | The intended change concerns behaviour, style or task execution. | Not a substitute for current, verifiable document access. |
What we need to start
- Readable documents and version, owner and access metadata.
- Questions with known correct answers and sources.
- Rules for updates, deletion and access restrictions.
How to assess the result
- Measure whether relevant passages appear in retrieval results.
- Check that the cited source actually supports the answer.
- Test unanswerable questions, conflicting sources and access restrictions.
SCOPE & INVESTMENT
What determines the cost?
A useful estimate starts with the scope. We distinguish development work from recurring usage and operating costs. These are the main drivers:
- Document volume, formats and preprocessing.
- Search methods, permissions and refresh frequency.
- Indexing, model usage, hosting and maintaining evaluations.
01 / PROBLEM & POSSIBILITIES
Your challenge.
A practical application.
A language model does not adequately know your products, procedures or documentation.
Build a RAG system that adds relevant business information to AI answers. We agree what the solution should do, which information it needs and how the result will be assessed.
THE QUESTION WE ASK FIRST
How will we measure whether the right source is found and used correctly?
02 / FROM QUESTION TO SOLUTION
An approach with
clear steps.
You stay informed about decisions, progress and delivery. We adapt the scope to your organisation.
Map sources and data flows
How will we measure whether the right source is found and used correctly?
Connect and test exceptions
We use representative examples and discuss the results, making assumptions and limitations visible before proceeding.
Monitor and document
We document the agreed outcomes, responsibilities and next steps.
03 / A PRACTICAL FOUNDATION
Designed for your
systems and requirements.
Technology that fits
CRM, ERP, accounting systems, databases and analytics platforms. Available APIs, limits and licences determine what is possible.
Security and control
Integrations receive limited permissions and protected access. We implement validation, error reporting and repeatable processing.
A possible application
A language model does not adequately know your products, procedures or documentation. The project can start with one focused component. Together we assess whether expanding it makes sense.
Illustrative scenario; not a published client case.04 / WHAT TO EXPECT
Your questions.
Clear answers.
Does RAG always produce correct answers?
No. It may retrieve the wrong passage or misinterpret a good source. We assess source selection and answer quality separately and design for uncertainty.
Do I always need a vector database?
No. The appropriate search method depends on your documents, questions and infrastructure. Keyword search, semantic search or a combination may fit.
Where do we start with rag system development?
How will we measure whether the right source is found and used correctly? We discuss this together, define the scope and establish what is needed for an informed proposal.
What does the project cost?
The investment depends on scope, existing systems, data quality and required integrations. Your proposal separates the work, assumptions and any recurring usage or operating costs. A useful estimate requires an understanding of your situation.
How long does delivery take?
We agree a schedule once the scope and dependencies are known. System access, team availability and acceptance testing are included in the plan. Where possible, we start with a focused first step.
Can we keep our existing systems?
CRM, ERP, accounting systems, databases and analytics platforms. Available APIs, limits and licences determine what is possible. We investigate the possibilities and limitations before proposing a technical approach.
What happens after delivery?
You receive a handover explaining the solution and its documentation. Maintenance, support and further development are agreed separately, including responsibilities and how errors will be handled.