Framework
The Cardim Intelligence Stack
Enterprise AI fails when it is built on top of data and systems that were never made ready for it. The Cardim Intelligence Stack is the six-layer model we use to engineer the path from data to intelligence — Foundation, Capability, Intelligence — with security and governance running through every layer.
Layer 1 — Unified Data Platform
The foundation is one governed data platform, typically on Databricks or Microsoft Fabric: ingestion, a lakehouse, a semantic layer, lineage and access control. AI is only as trustworthy as the data it reads, so this is where ownership, quality and classification are defined.
Layer 2 — API
Stable, versioned APIs expose data and business operations with authentication, authorization and rate limits. APIs make the platform usable by applications — and later by AI — without direct database access.
Layer 3 — MCP
The Model Context Protocol gives AI applications a standard way to discover and call enterprise capabilities. MCP servers wrap existing APIs as tools, resources and prompts, with scoped, identity-aware access. Read more in our guide to MCP for the enterprise.
Layer 4 — Tools Catalog
A curated, allow-listed catalog of the tools AI is permitted to use: owner, description, risk level, required permissions and version. The catalog is how the organization decides — deliberately — what an agent can touch.
Layer 5 — Skills
Skills combine tools, context and instructions into repeatable business tasks: reconcile an invoice, draft a supplier response, triage a ticket. Skills are tested, evaluated and versioned like any other software.
Layer 6 — Loops
At the top, agentic loops observe, reason, act, evaluate and learn. Humans stay in the loop where risk requires it, and every action is traceable to a user or agent identity.
The maturity path
Organizations move up the stack in order. Skipping steps creates fragile AI on top of unreliable data.
- Data Foundation — trusted, governed data
- Data Access — secure APIs
- Standardized Access — MCP
- Capabilities — tools and skills
- Intelligence — agents that reason and act
- Autonomy — supervised, measurable automation
Controls in every layer
Identity & access, security, observability, evaluation and governance are not a final step. They run vertically through the whole stack — from row-level access on the data platform to tool permissions, tracing with PII redaction and evaluation of agent behavior.