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Get your governance assessment

Tell us your stack and your first use case. We will map the guardrails it needs.

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ENTERPRISE RISK CONTROL & COMPLIANCE

Deploy custom AI systems without operational or regulatory risk

Guardrails are built into your existing infrastructure from Day 1. Your data stays in your tenant, your team keeps full control, and you own every line of code.

Get My Governance Assessment

Download Security Specs (PDF) for IT, SecOps and legal review

30-minute call. No pitch deck.

SECURITY ARCHITECTURE

Core Pillars of Security & Architecture

Zero Data Retention: your data stays in your tenant

All custom agents run inside your company-owned tenant (Azure, AWS, M365, Google Workspace or OpenAI Enterprise). Enterprise API protocols are configured for zero retention by model providers, so your proprietary data is not used to train third-party models. Client data is never used to train foundation models. Audit logs of agent activity stay in your environment.

Role-Based Access Control (RBAC) & Active Directory

Agents inherit your existing directory privileges, SSO and permission rules. An agent can only read or process files that the employee using it is authorized to view, which reduces the risk of internal data leakage.

Human-in-the-Loop Approval Checkpoints

High-risk workflows (financial movements, legal outreach, external communications) require mandatory human sign-off. Your team retains full kill-switch authority and audit oversight.

Complete IP Ownership & Zero Vendor Lock-In

You own 100% of the IP. All custom code, workflows, prompt pipelines and UI documentation are transferred into your code repositories at hand-off.

COMPLIANCE

Compliance & Framework Compatibility

STANDARD / FRAMEWORK

HOW WE DELIVER IT

WHAT THAT MEANS

SOC 2 Type II and ISO 27001 alignment

Tenant-isolated processing

Agents run inside your own tenant with tenant-isolated API processing, automated audit logging and token encryption.

HIPAA and GDPR support

Zero-retention APIs

Built on BAA-eligible infrastructure, with no persistent data logging on public models.

WCAG 2.1 AA

Accessible interfaces

Custom agent dashboards and co-building interfaces are built to meet WCAG 2.1 AA.

OAuth 2.0, SAML and SSO

Directory integration

Works with Okta, Microsoft Entra ID and Google Cloud Identity.

SELF-ASSESSMENT

What’s Your Governance Level?

Select the execution tier that matches your use case to see the exact guardrail stack required.

1. What will the AI system do?
2. How much can it change without a person approving it?
3. Which requirements apply to this use case?

Optional. Select any that your legal or security team will ask about.

Level 1 · Low risk

Internal Productivity

Your answers describe read-only work where a person acts on the output.

Required guardrail stack

  • Standard RBAC
  • Read-only access
  • Usage logging

30-minute call. No pitch deck. This self-assessment is a starting point, not a compliance determination.

Level 1 · Low risk

Internal Productivity

Summaries, drafting, internal search.

Required guardrail stack: Standard RBAC, read-only access, and usage logging.

Level 2 · Medium risk

Workflow Automation

CRM updates, report generation, routine customer comms.

Required guardrail stack: RBAC, human-in-the-loop review, audit trails, and rate limiting.

Level 3 · High risk

Autonomous Agent Execution

Direct database writes, payment triggers, and regulatory filings.

Required guardrail stack: Full RBAC, mandatory human sign-off, kill-switch authority, real-time audit logging, and tenant isolation.

Ready to map your use cases to a guardrail stack?

Tell us which tier your first use case falls into and we will walk through the guardrails it needs.

Get My Governance Assessment

30-minute call. No pitch deck.

HAND-OFF PACKAGE

Technical Deliverables Included With Every Implementation

Data flow and architecture diagrams, mapped for IT and SecOps review.

System prompt and guardrail audits that enforce brand and compliance boundaries.

API log and audit trails with full transparency into token utilization and user actions.

Incident response and kill-switch protocols.

Questions From Your Legal & Security Teams

Will our proprietary business data be used to train LLMs?

No. Every agent runs through zero-data-retention API connections inside your own tenant. Your proprietary data, prompts, and outputs are never logged, stored, or used to train third-party foundation models.

How do custom agents handle sensitive PII (Personally Identifiable Information)?

PII is processed only within the access boundaries already defined by your directory permissions and RBAC policies. Sensitive fields can be masked, redacted, or excluded entirely from agent context depending on the workflow's risk tier.

What happens if an external LLM API experiences downtime?

Workflows are built with fallback logic and human-in-the-loop checkpoints so they degrade gracefully instead of failing silently. High-risk autonomous workflows are configured to automatically pause and alert your team rather than take action while an API is unavailable.

Can we run custom workflows completely on-premise or within a private cloud (AWS/Azure)?

Yes. Custom agents can be deployed entirely within your private AWS or Azure environment, including private endpoints and VPC-isolated model access, depending on your existing infrastructure and compliance requirements.

Ready to Deploy AI With Complete Risk Control?

Schedule a 30-Minute Governance Review →