Build · Practical intelligence
Software & Applied AI
Not every business needs an AI strategy. Sometimes you need a better way to search information, automate repetitive work, connect systems, or add useful intelligence to an existing application. CoreNet builds practical AI systems around real business problems.
Talk to CoreNetPrivate AI infrastructure
A private AI environment is configured for an organization’s use and document access needs. We can help scope private or local model deployment, infrastructure, and integration. Hosting location, permissions, and data handling need to be decided for the particular system; the word private alone is not a security guarantee.
RAG & internal knowledge systems
Retrieval-augmented generation (RAG) brings relevant material from a document library into a model’s context when answering a question. It can support internal document Q&A and knowledge search. PDF contents must first be readable or extracted; answers still need checking against their source material.
- Company document search
- Internal knowledge retrieval
- Document Q&A
- Private/local LLM integration
AI-assisted workflows
Useful features can include summarization, classification, information retrieval, and workflow assistance. We consider what the team needs to review, which systems must connect, and where automation can reduce repetitive work.
Choose the tool around the problem
Sometimes the right answer is a large language model. Sometimes it's an API, an automation, a database, or better software. We care more about solving the problem than attaching a label to it.
Private knowledge search in practice
A real estate organization needed an easier way to work with hundreds of pages of internal and legal/reference information. CoreNet deployed a private RAG environment so staff could ask natural-language questions against the document library. This was knowledge assistance, not legal advice.
Questions about working together
What is private AI for business?
Private AI refers to deploying language models within an environment controlled by your business, rather than sending confidential data to public consumer services. Access permissions, hosting, and data handling are scoped around your security requirements.
What is retrieval-augmented generation (RAG)?
RAG connects an AI model to your organization's document library. When a question is asked, the system retrieves relevant excerpts from your documents and provides them to the model to generate an answer based on source material.
Can AI search internal PDFs and documentation?
Yes, provided the documents are readable text or can be extracted. RAG systems can index internal policies, manuals, reference materials, and contracts to answer questions with citations back to the source pages.
Can a company host or run models on private infrastructure?
Yes. Depending on performance and privacy needs, models can be hosted in private cloud instances or on-premises servers so data does not leave your designated boundary.
When is an API or automation better than an AI model?
When the task requires predictable logic, structured data transfer, or calculations, traditional software, APIs, and automations are usually faster, cheaper, and more reliable. We use AI only where language understanding or text synthesis is genuinely required.