A custom AI assistant trained on your internal data, running entirely on your infrastructure. Built for firms that need accurate, context-aware conversational AI without sending sensitive data to third-party APIs.
What We Build #
Core-AI develops private assistants powered by modern AI models, grounded in your own documents. These assistants integrate with your existing systems and knowledge base — allowing your team to query complex documentation through a natural conversational interface.
Unlike commercial chatbot APIs, our deployments run on your hardware or private cloud. Your conversations, documents, and their index never leave your network.
Key Capabilities #
- Document Search — Instantly find information across large document collections, regardless of format (PDF, Confluence, SharePoint, databases).
- Contextual Conversation — Maintain multi-turn reasoning and problem-solving context across long sessions.
- Role-based Access Control — Ensure users only see information they are authorized to access, integrated with your existing SSO/IAM.
- Multilingual Support — Communicate effectively across languages and regions using locally-deployed models.
- Analytics Dashboard — Monitor usage patterns, query quality, and system performance over time.
- Audit Trail — Every query and response is logged for compliance review — Law 25, PIPEDA, or whatever your clients impose on you by contract.
Architecture #
User
Interface
Retrieval
Local Model
Answer
Common Use Cases #
- Internal knowledge assistant — Engineering, legal, and HR teams query company documentation in natural language.
- Customer support augmentation — First-line agents get instant access to product manuals, policies, and resolution playbooks.
- Compliance lookup — Regulated teams query regulations, contracts, and audit records with full traceability.
- Onboarding assistant — New hires ramp up faster by querying institutional knowledge directly.
Related Services #
- Document Intelligence — power your assistant with a well-structured knowledge base.
- AI Infrastructure Deployment — the foundation your assistant runs on.
- AI Agents — for cases that need information pulled across more than one system, not just a single answer.
Frequently Asked Questions #
How do you connect the assistant to our existing documents and knowledge base?
We build custom connectors for the systems where your content lives — SharePoint, Confluence, Notion, PDF repositories, SQL databases, and more. Documents are ingested, processed, and indexed privately. The assistant retrieves relevant content in real time using search by meaning, not keyword matching.
Can the assistant enforce our existing role-based access controls?
Yes. Access controls are a first-class design requirement. We integrate with your existing SSO and identity system (Azure AD, Okta, and others) and apply document-level permissions so users only receive answers drawn from content they are authorized to see.
Does conversation data leave our infrastructure?
No. Both the language model and the document index run on your infrastructure. Queries, responses, and retrieved content are processed entirely within your network. You control all logs and configure retention policies.
What languages does the assistant support?
Modern models natively support dozens of languages. We benchmark the model on your specific languages during Prototype to confirm accuracy. Retrieving relevant content across languages from a single question requires additional configuration, which we include for bilingual deployments.
How do you measure the assistant's quality and accuracy?
We set up a structured evaluation before launch: a reference set of questions and expected answers, precision and recall metrics, and a feedback loop so your team can flag incorrect answers. Evaluation is part of every delivery so you can monitor quality continuously.