IntelicoreAI designs and deploys serious AI systems for industrial and regulated environments. We combine AI implementation, deterministic controls, data sovereignty, auditability and operational engineering so organizations can use AI without surrendering control of their data, systems or decisions.
Companies are connecting AI tools and agents to internal systems while still struggling to answer basic questions about access, data movement, authority and evidence.
Files, databases, applications, APIs, operational systems and internal knowledge.
Storage, processing jurisdictions, external providers, model endpoints and retention paths.
Read, recommend, modify, approve, execute, trigger workflows or interact with other systems.
Technical evidence, audit history, access records, policy enforcement and traceable decisions.
Our work spans governed AI, deterministic regulatory systems, industrial engineering, private enterprise AI and evidence-based decision infrastructure.
A Canadian regulatory technology platform designed to automate building-code compliance without allowing generative AI to become the compliance authority. AI can assist with extraction, search and explanation while deterministic rules, evidence traces and human review preserve control over formal compliance outcomes.
Governance infrastructure designed to control what AI systems can access, which actions they can perform and what evidence must exist before execution. Governance is treated as runtime infrastructure rather than policy documentation.
Geospatial, RF and infrastructure engineering systems combining terrain analysis, design automation, equipment intelligence, scenario comparison and machine-readable engineering outputs.
Private AI architectures that let organizations work with internal documents and operational knowledge while retaining control over source information, permissions, deployment location and model access.
AI agents and workflow systems designed around the principle that automation should be useful without becoming invisible. Access, actions, escalation points and evidence are designed into the workflow from the beginning.
Sovereignty is more than where a server is located. Organizations need visibility into where information is stored, where it is processed, which providers can access it, what AI systems can interact with it and which controls are actually enforceable.
Use generative AI where judgment and assistance are useful. Use deterministic controls where decisions must be repeatable and defensible.
Policies matter, but technical boundaries, permissions and evidence matter more when AI is interacting with operational systems.
Private-looking software can still depend on external models, APIs and infrastructure. The full processing chain matters.
Organizations should be able to demonstrate what happened, what was accessed and which controls were applied.
Identify AI systems, data sources, integrations and operational requirements.
Document access paths, data flows, providers, models and processing locations.
Define permissions, boundaries, approved models, human controls and prohibited actions.
Implement the AI, automation or deterministic system inside those boundaries.
Capture evidence showing what occurred and whether the defined controls were followed.
IntelicoreAI can help map your current environment, identify governance and sovereignty gaps, and design a practical path toward controlled AI deployment.
Start a Conversation