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Core-AI

Core-AI

Private AI Systems for Enterprise

Core-AI designs and deploys enterprise AI systems powered by modern LLMs, running directly on your infrastructure.

Your data stays under your control.

Talk to an engineer See the live demo →

Why Choose Core-AI
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Private AI First

Your data never leaves your infrastructure unless you explicitly choose to use external APIs.

Production Systems

We build AI systems designed for real business workflows, not just prototypes.

Flexible Model Strategy

Use open models locally or connect to commercial APIs when your use case demands it.

Full System Ownership

Clients receive fully deployable infrastructure, code, and comprehensive documentation.

Live AI Experience
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Interested in seeing our technology in action? Our demo allows you to interact with an AI assistant, see how company knowledge can be queried, and understand RAG (Retrieval-Augmented Generation) capabilities.

Visit the Core-AI Demo →

How We Work
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graph LR
  A((Discovery)) --> B((Design))
  B --> C((Prototype))
  C --> D((Production))

  classDef n1 fill:#3b82f6,stroke:#333,stroke-width:2px,color:#fff,font-size:22px;
  classDef n2 fill:#6366f1,stroke:#333,stroke-width:2px,color:#fff,font-size:22px;
  classDef n3 fill:#8b5cf6,stroke:#333,stroke-width:2px,color:#fff,font-size:22px;
  classDef n4 fill:#a855f7,stroke:#333,stroke-width:2px,color:#fff,font-size:22px;

  class A n1;
  class B n2;
  class C n3;
  class D n4;

Step 1: AI Opportunity Discovery — Identify high-value AI use cases.

Step 2: Architecture Design — Design an AI system tailored to the organization.

Step 3: Prototype Deployment — Build a working system for evaluation.

Step 4: Production Deployment — Deploy a scalable AI system in the client infrastructure.

Frequently Asked Questions
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What is private AI and how does it differ from services like OpenAI or ChatGPT?
Private AI refers to AI systems that run entirely on your own infrastructure rather than sending data to external cloud services. Unlike OpenAI or Azure AI, private AI keeps your data, queries, and documents inside your network — critical for regulated industries and organizations with sensitive intellectual property.
What industries does Core-AI serve?
We work with organizations in finance, healthcare, legal, insurance, public sector, and any business where data privacy, compliance, or confidentiality is a business requirement. Our clients share one common need: powerful AI capabilities without surrendering data sovereignty.
How long does a private AI deployment take from start to production?
A typical engagement runs 8–16 weeks from Discovery to Production deployment. Simpler systems — such as an internal chatbot over a defined knowledge base — can reach production in 6 weeks; complex multi-agent or infrastructure-heavy projects take longer. We follow a four-step process (Discovery, Design, Prototype, Production) so you can validate fit at each stage before committing to the next.
Do we need in-house AI expertise to work with Core-AI?
No. We handle design, build, and deployment end-to-end. After handoff, we provide full documentation and hands-on training so your team can operate the system independently. Ongoing support arrangements are available.
What open-weight LLMs do you work with?
We work with the leading open-weight models — Llama 3, Mistral, Mixtral, Qwen, Phi, Gemma, and others. Model selection depends on your use case, latency requirements, and hardware budget. We benchmark options during the Design phase and recommend the best fit for your workload.

Ready to Start?
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Schedule an AI Consultation