Control CoreDocs

💡 Sample Use Cases

See what's possible with Control Core: security, governance, optimization, and audits. Control Core is AI-first—these use cases start with governing AI traffic and tool use, then show how the same PBAC layer extends to APIs and data.

📌 Who It's For

Control Core helps financial institutions, large and medium enterprises, and organizations deploying AI and RAG tools, planning external authorization over their API Gateway, or needing to optimize AI token usage, protect sensitive data from LLMs, or prevent data from being shared across users via AI. The sample use cases below illustrate outcomes—no implementation or internal architecture details.

📌 Use Case Categories

AI Access Controls

Apply PBAC to AI systems: control who can use which AI capabilities, what data can be sent to models, and how usage is governed and audited. Covers generative AI, RAG (retrieval-augmented generation), agent tooling (e.g. MCP), and enterprise AI applications—with brief compliance references and prospect-oriented examples.

Typical AI-first scenarios:

  • AI Pilot guardrails: sanitize prompts, filter outputs, enforce token budgets/rate limits, and block prompt injection.
  • RAG governance: restrict retrieval and prompt inclusion by tenant, classification, purpose, and role.
  • Agent tool controls (MCP/A2A): trusted tool allowlists, user identity propagation, and injection defenses with audit trails.

Regulatory Compliance

Use Control Core policies and audit to enforce and demonstrate compliance with regulations and standards. Includes data residency, consent and purpose limitation, access logging, and role- or attribute-based restrictions. Regional compliance and certifications (Canada, USA, South America, EU, UK, Asia) are summarized with links to deeper guidance.

Centralized Authorization on Cloud Assets

Define and update who can access what across APIs, gateways, and cloud services in one place, and enforce at the edge (e.g. API Gateway). Covers external authorization at the gateway, consistent rules across services, and faster policy updates—ideal for enterprises planning centralized auth over their API Gateway.

Dynamic Context Management

Use real-time context (user, time, location, risk, business state) from Policy Information Points (PIPs) to make allow/deny and filtering decisions. Covers time- and location-based access, risk- or approval-based access, data masking by context, and AI-related context (e.g. which data can be used in which AI flow).

📌 Next Steps