Automation and AI
LLM Integration, RAG and Generative AI App Development
Large language models can summarise, search, draft and answer questions, but they need your data and guardrails to be useful. Retrieval-augmented generation (RAG) grounds them in your own content.
Orincore integrates LLMs into products and internal tools: knowledge assistants, document search, summarisation and content workflows, with evaluation and cost control.
What your llm integration and rag can include
We build only the modules you need and add the rest later, so you are never paying for a bloated package.
Knowledge ingestion
Prepare and index your documents and data.
RAG pipeline
Retrieve the right passages before the model answers.
Assistants and search
Chat and semantic search over your content.
Summarisation and drafting
Reports, emails and content with review.
Evaluation
Test answers against real questions to measure quality.
Cost and privacy controls
Model choice, caching and data-handling settings.
Who it is for
- Companies with large document sets
- Products adding AI features
- Support and research teams
What to plan for
Practical points we cover with you before building.
Accuracy
Models can be wrong, so we ground answers in sources, show references and test on your questions.
Data privacy
We choose providers and settings to match your data sensitivity and tell you how your data is handled.
How we build it
A clear, milestone-based process with a written estimate before any work begins.
- 01
Scope
A short call to understand your process, users and priorities, then a written scope and estimate.
- 02
Design
Clickable designs and data flows you can review before development starts.
- 03
Build in phases
Working releases every one to two weeks, starting with the module that matters most.
- 04
Launch and support
Testing, launch, documentation and up to 2 months of free support, maintenance and bug fixes.
Services behind this solution
AI Development and Automation
AI chatbots, LLM integrations and workflow automation that remove repetitive work.
SaaS Development
Multi-tenant SaaS products, from first MVP to production scale.
Custom Software Development
CRMs, internal tools, workflow systems and integrations built around your processes.
Frequently asked questions
What is RAG?
Retrieval-augmented generation finds relevant passages from your content and gives them to the model so its answer is based on them.
Which AI models do you use?
We choose among current provider models to fit quality, cost and privacy needs.
Can it work with our private data?
Yes, with settings that keep data handling in line with your requirements.
Do you provide support after launch?
Yes. Every project includes up to 2 months of free support, maintenance and bug fixes after launch, counted from the day we hand the application over to you to launch. After that period, we do not provide free support: any further support, maintenance or changes to the service are paid, and we agree the price with you in writing before work starts.
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Ready to discuss your project?
Tell us what you want to build. You will get a written estimate range and clear next steps, with no obligation. Every project includes up to 2 months of free support after launch.