The AI Operating System built compliance-first — so regulated organizations deploy with confidence, pass audits without retrofitting, and maintain full data sovereignty.
Regulated industries don't get a second chance on compliance. ibl.ai is not an AI app — it is the AI Operating System your organization deploys on its own infrastructure, giving you complete control over data, models, and access policies from day one.
Like Windows or Linux for software, ibl.ai is the platform layer that all your AI agents, workflows, and applications run on. Every component — from the Agent Runtime to the Memory Layer — is engineered with HIPAA, SOX, FISMA, FedRAMP, and GDPR requirements built in, not bolted on.
With 1.6M+ users across 400+ organizations and partnerships with Google, Microsoft, and AWS, ibl.ai delivers production-grade AI infrastructure that satisfies your compliance team, your security team, and your auditors — without slowing down your AI roadmap.
Executes autonomous AI agents in isolated, policy-enforced sandboxes. Every reasoning loop, tool call, and code execution is contained, logged, and auditable — meeting the strictest regulated-industry requirements.
A federated data layer that connects SIS, LMS, CRM, EHR, and HRIS systems with role-based, policy-aware access controls. Data never leaves its authorized boundary, ensuring HIPAA and FERPA compliance at the infrastructure level.
Intelligently routes requests to the optimal LLM — Claude, GPT, Gemini, Llama, or Mistral — while enforcing model-level data isolation. Sensitive data can be restricted to on-premise or air-gapped models only.
Enterprise-grade security with role-based access control, immutable audit trails, and encrypted credential management. Every agent action is logged with full provenance — ready for SOX, FedRAMP, and FISMA audits.
Connects to enterprise systems via MCP servers, REST APIs, webhooks, and LTI — with data-handling policies enforced at the integration layer. No uncontrolled data egress, no shadow IT risk.
Manages agent lifecycles, scheduling, and inter-agent communication across hundreds of organizations — with hard tenant boundaries that satisfy multi-entity compliance requirements and data sovereignty mandates.
Continuously monitors internal systems, documents, and workflows for policy violations, flagging anomalies in real time. Integrates with GRC platforms and generates audit-ready reports automatically.
Deploys a HIPAA-compliant AI assistant for healthcare staff that answers clinical and administrative queries using only authorized, role-scoped data — with zero PHI exposure to external models.
Automates evidence collection, control testing, and documentation for SOX audits. Agents pull data from ERP and financial systems, generate control narratives, and flag exceptions for human review.
Orchestrates onboarding workflows across HRIS, IT provisioning, and training systems — with RBAC-enforced data access ensuring employees only see information appropriate to their role and clearance level.
Ingests, classifies, and extracts insights from regulatory filings, policy documents, and contracts — running entirely within your air-gapped or private cloud environment with no data leaving your perimeter.
Detects potential data incidents, triggers response workflows, notifies the appropriate stakeholders, and generates breach notification documentation — all within the timelines required by HIPAA, GDPR, and state regulations.
Traditional chatbots answer questions. Autonomous AI agents take action, reason over context, and deliver measurable outcomes.
ibl.ai deploys autonomous AI agents that go beyond simple Q&A. Our agents reason, plan, and execute multi-step workflows while you retain full code ownership and infrastructure control.
Every agent action, data access event, model call, and user interaction is logged with full provenance and tamper-evident storage. Audit logs are structured for direct export to SIEM platforms and compliance reporting tools.
Granular RBAC is enforced at every layer — agent execution, memory access, skill invocation, and integration calls. Access policies are defined once and propagated across the entire AI OS, eliminating policy drift.
Every agent runs in an isolated execution environment. Code execution, tool use, and external API calls are sandboxed and policy-gated, preventing lateral movement and containing the blast radius of any misconfiguration.
ibl.ai deploys entirely within your infrastructure — on-premise, private cloud, or air-gapped environments. No data transits external networks. Meets the deployment requirements of FedRAMP High, FISMA, and classified environments.
All integration credentials, API keys, and secrets are stored in an encrypted credential vault with rotation policies and access logging. No credentials are exposed to agent code or stored in plaintext.
The Model Router enforces data sovereignty policies — routing sensitive workloads exclusively to on-premise or approved models. PHI, PII, and classified data never reach external LLM APIs unless explicitly authorized.
ibl.ai delivers complete source code to your organization. You own the codebase, can inspect every line, and are never dependent on a vendor's continued operation. Critical for regulated industries requiring software escrow or code review.
Run ibl.ai on your AWS, Azure, GCP, or on-premise environment. Your data never touches ibl.ai's servers in production. You control the runtime, the storage, and the network perimeter — satisfying data residency and sovereignty requirements.
Model-agnostic architecture means you are never locked to a single LLM provider. Swap, add, or restrict models at the router level without rewriting applications — protecting your investment as the model landscape evolves.
Security policies, data handling rules, and access controls are configurable at the infrastructure level. Adapt ibl.ai to your specific regulatory framework without waiting for a vendor to ship a compliance update.
ibl.ai provides full architecture documentation, data flow diagrams, and security control mappings aligned to NIST, HIPAA, and FedRAMP control families — accelerating your ATO, HITRUST, or SOC 2 certification process.
ibl.ai's solutions team maps your regulatory requirements — HIPAA, SOX, FedRAMP, GDPR, or FISMA — to the AI OS architecture. We identify deployment topology, data flow boundaries, model restrictions, and RBAC policies before a single line of code is deployed.
ibl.ai is deployed within your infrastructure boundary — private cloud, on-premise, or air-gapped. Integration Bus connectors are configured for your EHR, ERP, HRIS, or LMS systems with policy-enforced data access. Full source code is transferred to your team.
Compliance-specific agents are activated from the Skill Registry and customized for your workflows. Audit trail outputs are validated against your reporting requirements. Your compliance and security teams receive full documentation for audit submission.
Automated evidence collection, control testing, and audit trail generation dramatically reduce the manual effort required for SOX, HIPAA, and FedRAMP audits — freeing compliance staff for higher-value work.
Continuous monitoring agents detect policy violations and anomalies in real time, compared to periodic manual reviews — reducing the window of exposure and potential regulatory penalties.
Because compliance is built into the infrastructure layer, regulated organizations skip the lengthy retrofitting process that delays AI adoption — deploying production-grade agents in weeks with audit-ready documentation from day one.
Automated evidence packaging, pre-mapped control documentation, and structured audit logs reduce the billable hours required from external auditors — directly lowering compliance program costs.
Automated incident detection and breach notification workflows compress response timelines from days to hours — minimizing regulatory exposure under HIPAA's 60-day and GDPR's 72-hour notification requirements.
The Health Insurance Portability and Accountability Act requires covered entities and business associates to implement administrative, physical, and technical safeguards for PHI — including access controls, audit controls, and transmission security.
ibl.ai enforces HIPAA technical safeguards at the infrastructure layer: RBAC restricts PHI access by role, the Memory Layer enforces minimum necessary access, model isolation prevents PHI from reaching external APIs, and immutable audit logs satisfy the audit control requirement. Air-gapped deployment eliminates transmission risk entirely.
FedRAMP and FISMA require federal agencies and their cloud service providers to implement NIST SP 800-53 security controls, obtain an Authority to Operate (ATO), and maintain continuous monitoring of their systems.
ibl.ai's architecture documentation maps directly to NIST SP 800-53 control families. Air-gapped and GovCloud deployment options satisfy FedRAMP High boundary requirements. Immutable audit trails and continuous monitoring agent capabilities support ongoing ATO maintenance and FISMA annual reporting.
SOX Section 404 requires public companies to maintain and assess the effectiveness of internal controls over financial reporting — with external auditor attestation and documented evidence of control operation.
ibl.ai's Compliance Monitoring and Audit agents automate SOX control testing, evidence collection, and exception reporting. Full audit trails provide the documentation required for external auditor review. RBAC ensures segregation of duties is enforced and auditable across financial systems.
The General Data Protection Regulation requires organizations processing EU personal data to implement data minimization, purpose limitation, right to erasure, and 72-hour breach notification — with demonstrable technical and organizational measures.
ibl.ai's policy-aware Memory Layer enforces data minimization and purpose limitation at the infrastructure level. Data sovereignty deployment ensures EU personal data remains within approved geographic boundaries. Incident Response agents automate breach detection and notification workflows to meet the 72-hour requirement.
See how ibl.ai deploys autonomous AI agents you own and control — on your infrastructure, integrated with your systems.