Control Core Product Guide
🛡️ Welcome to the access controls command center guide
Control Core is the intelligent "permissions bouncer" for the AI era. We let you decouple complex security, business, and regulatory logic from your code, moving it into a single, central engine that governs every interaction across your legacy systems, APIs, Data services, and AI agents. — one place to author, test, audit and enforce rules with real-time context.
📌 Introduction
Control Core helps you apply your context driven access control rules, compliance requirements, business rules, and security policies across interactions involving data, applications, APIs, and AI, using real-time context rather than static role checks alone.
What you can do with Control Core
Externalize access control from application code
Move authorization logic into centrally managed policies so legacy systems stay stable while rules evolve without redeploying every service.
Example: Update a permission model once and enforce it consistently across APIs and integrations.
Decide access using live context
Combine identity, device, location, time, risk, approvals, and business state. Policies can change as conditions change.
Example: Restrict high-risk actions to approved windows, trusted devices, and verified approval state.
Govern APIs, data paths, infrastructure, and AI from one model
Use one policy workflow across REST and gRPC, gateways and data services, and AI-related flows including tool and retrieval paths where you apply policy.
Example: Align API, RAG retrieval, and tool-invocation rules under the same policy intent.
Support compliance and audit evidence
Encode residency, purpose limitation, least privilege, and segregation patterns; retain consistent decision and administrative evidence for review.
Example: Enforce purpose and residency checks with records tied to policy versions and decisions.
Reduce sensitive exposure in AI workflows
Combine prompt and context controls with masking and tiered access so only approved data reaches models or tools.
Example: Block disallowed field classes from outbound prompts while allowing approved non-sensitive use.
Accelerate policy authoring with guided assistance
Describe intent in natural language to produce explainable drafts; humans retain review, test, and promotion steps.
Example: “Finance managers may approve payments only from managed devices with step-up authentication” becomes a testable draft with clear conditions.
So What?
Using a system like Control Core to externalize access controls delivers a strong foundation for secure operations—especially as AI tools interface with APIs, data, apps, and legacy systems. Key benefits include:
- Consistent enforcement of policy across diverse entry points (AI, integrations, legacy, cloud), reducing gaps and silos in access logic.
- Rapid adaptation to new use cases, letting organizations introduce AI capabilities or update business rules without rewriting core application code.
- Centralized, explainable decisions and audit trails, which simplify compliance, security investigations, and regulatory review.
- Granular, context-aware controls that dynamically factor in risk, identity, approvals, and environment—crucial as AI agents and humans act on sensitive workloads.
- Minimized data and privilege exposure, since policies govern exactly what information and actions are reachable, even in automated or complex multi-system workflows.
Explore by goal
Onboard and first policy
Architecture, prerequisites, first policy flow, and verification patterns.
View guideOperationsDeploy and operate
Self-hosted, hybrid, and enterprise runbooks with readiness checklists.
View guidePolicyAuthor and validate policies
Authoring, templates, simulator-backed testing, and promotion workflows.
View guideDataContext and integrations
Connect sources for context-aware decisions (PIP) and related guides.
View guideOnboarding checklist
Recommended first path
1 — Orientation
2 — Environment
3 — Policy lifecycle
📌 Documentation library
Use this index to jump to the right guide. Every link is relative to this site.
| Topic | Primary guides |
|---|---|
| Foundations | Getting Started, Installation, Architecture |
| Deployment | Overview, Kickstart, Pro, Enterprise, Scaling, Multiple bouncers, Network bouncer |
| Administration | Administrator, License management, DevOps, Security, Policy hardening |
| Policy authoring | User Guide, Rego Guidelines, Policy templates, PBAC Best Practices, Policy testing |
| Data & PIP | PIP Getting Started, PIP Admin, PIP Developer |
| AI & pilots | AI Pilot, AI Gateway, Control Map |
| APIs | API Reference, Policies as Code API, IDE Integration API, Multi-tenant API |
| Observability | Observability & Trust, Audit vs diagnostic logs |
| Help | Troubleshooting, FAQ, Abbreviations |
📌 Platform overview
| Component | Role |
|---|---|
| Policy Administration | Console and APIs for policy CRUD, identity and resource metadata, testing, and audit-oriented logging. |
| Policy Enforcement (Bouncer) | Edge enforcement with low-latency evaluation; can adapt responses (including content controls where configured). |
| Policy synchronization | Keeps policy bundles and related configuration aligned across environments. |
| Policy language support | Editor and language services for Rego authoring, validation, and developer workflows. |
For diagrams and deeper detail, see Architecture.
🚀 Deployment models (summary)
| Model | Best for | Notes |
|---|---|---|
| Kickstart | Teams bringing the full stack on their own infrastructure | Guide |
| Pro | Hosted control plane with customer-operated enforcement at the edge | Guide |
| Enterprise | Large scale, HA, and Kubernetes-oriented operations | Guide |
📘 Guides by audience
| Audience | Start here |
|---|---|
| Platform & security | Administrator, Security, Observability |
| Policy authors | User Guide, Rego Guidelines, PBAC Best Practices |
| Integration engineers | API Reference, Integrations, Bouncer deployment |
| SRE / DevOps | Deployment, DevOps, Troubleshooting |
💡 Use cases
Control Core is suited to AI-first scenarios (guardrails, retrieval and tool governance) and the same policy model extends to APIs, data access, and operational workflows.
- AI workloads: Guardrails for prompts and outputs, retrieval and tool invocation controls, rate and budget limits, and audit-oriented evidence where required.
- APIs and data: Centralized authorization at the edge, masking and residency-style rules when encoded in policy, consistent decisions across services.
- Regulated environments: Patterns for financial and healthcare-style controls appear in templates and best-practice guides—adapt to your jurisdiction and counsel.
Browse sample use cases for narrative scenarios.
🔧 APIs and developer tooling
- Policies as Code API — programmatic policy lifecycle where supported.
- IDE Integration API — editor and tooling integration.
- Full API reference — endpoints, auth patterns, and examples.
IDE-oriented features (validation, synchronization patterns) are described in product documentation and the API guides above.
📞 Contact and support
- General inquiries: info@controlcore.io
- Technical and customer support: support@controlcore.io
Self-service: Troubleshooting, FAQ, Getting Started.
🔒 Security and compliance posture
Control Core is designed for strong defaults: encryption in transit, modern authentication patterns (including SAML/OIDC where configured), comprehensive audit logging options, and hardening guides. See Security and Policy and control plane hardening for operational detail.
📌 Recent documentation updates
March 2026
- Consolidated welcome page structure and documentation index for faster navigation.
- AI-first positioning aligned with use-case and pilot guides.
- Expanded cross-links to deployment, security, and API references without duplicating long bullet lists on this page.
Next step: Getting Started or pick a row in the documentation library above.