The AI Operating System that runs every department — not another AI app, but the platform all your AI agents run on.
Most enterprises don't have an AI strategy problem. They have an AI infrastructure problem. Dozens of disconnected tools, ungoverned models, and shadow AI sprawl across HR, Legal, Finance, and IT — with no central control layer.
ibl.ai is the AI Operating System (Agentic OS) that changes this. Like Windows or Linux for software, ibl.ai is the platform your AI agents run on — providing a unified runtime, memory layer, security model, and orchestration engine across your entire organization.
With 1.6M+ users, 400+ organizations, and partnerships with Google, Microsoft, and AWS, ibl.ai is production-grade infrastructure — not a pilot. Deploy on your own infrastructure with full source code ownership and enterprise compliance built in from day one.
Executes autonomous AI agents with full reasoning loops, tool use, and sandboxed code execution. Agents act, observe, and iterate — not just respond.
Intelligently routes every request to the optimal LLM — Claude, GPT-4, Gemini, Llama, Mistral — based on task complexity, latency requirements, and cost targets.
Connects your SIS, LMS, CRM, and HRIS into a unified, policy-aware data layer. Agents access the right data for the right user — with zero cross-tenant leakage.
A marketplace of 5,700+ community and custom enterprise agent capabilities. Deploy pre-built skills or build your own — all version-controlled and auditable.
Manages agent lifecycles, scheduling, scaling, and inter-agent communication. Run single agents or complex multi-agent workflows across departments simultaneously.
Connects to any enterprise system via MCP servers, REST APIs, webhooks, and LTI. Route AI interactions across web, mobile, Slack, Teams, WhatsApp, email, and SMS.
Deploy agents that handle onboarding workflows, policy Q&A, benefits inquiries, and compliance training — integrated directly with your HRIS and LMS.
Agents triage support tickets, execute runbooks, escalate intelligently, and resolve Tier-1 issues autonomously — connected to your ITSM and identity systems.
Agents review contracts, flag regulatory risks, summarize legal documents, and route approvals — with full audit trails and role-based access controls enforced at the OS level.
Agents query financial systems, generate variance reports, answer budget questions, and surface anomalies — all within SOX-compliant guardrails and data isolation policies.
Power personalized learning paths, coaching agents, and skills gap analysis across your workforce — as proven at scale on learn.nvidia.com, built and operated by ibl.ai.
Centralize all AI activity under one platform — eliminating shadow AI, enforcing usage policies, and providing executives with a single pane of glass for AI spend and risk.
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 interaction is governed by granular RBAC policies. Users only access data and capabilities their role permits — enforced at the OS layer, not the application layer.
Every agent action, tool call, data access, and model invocation is logged with immutable audit records — enabling compliance reviews, incident investigations, and regulatory reporting.
Agent-generated code runs in isolated execution environments. No agent can access host infrastructure, cross tenant boundaries, or execute outside its defined permission scope.
Enterprise credentials, API keys, and integration tokens are stored and rotated securely. Agents never expose secrets in prompts, logs, or responses.
Serve hundreds of organizations on one platform with guaranteed data isolation. No cross-tenant data leakage — by architecture, not just policy.
The ibl.ai Agentic OS is architected to support HIPAA, FERPA, SOX, and FedRAMP requirements — with data residency controls, encryption at rest and in transit, and configurable retention policies.
ibl.ai delivers the complete source code of the AI Operating System to your organization. You own it — no black-box vendor lock-in, no runtime dependencies on ibl.ai infrastructure.
Run on AWS, Azure, GCP, or your own on-premises environment. Your data never leaves your infrastructure boundary unless you explicitly configure it to.
Fork, extend, and modify the platform to meet your organization's unique requirements. Build proprietary agent skills, custom integrations, and bespoke workflows on top of the OS.
Once deployed, your team operates the platform independently. ibl.ai provides support and updates, but your AI infrastructure is never held hostage by a vendor's uptime or pricing decisions.
Because you own the source code, your security and compliance teams can audit every component of the AI OS — satisfying the most stringent enterprise and government procurement requirements.
ibl.ai's enterprise team maps your existing systems — LMS, HRIS, CRM, data warehouses — and designs the Agentic OS deployment architecture. We define data flows, RBAC policies, integration points, and compliance guardrails before a single line of code is deployed.
The AI OS is deployed on your chosen infrastructure. Integration Bus connections are established to your enterprise systems. Initial agent skills are configured from the Skill Registry, and your first department-specific agents are launched and validated.
RBAC policies, audit logging, and compliance controls are activated across all tenants. Your team is trained on the platform. Rollout expands department by department — with ibl.ai providing ongoing support, model routing optimization, and platform updates.
Centralizing AI on one governed platform eliminates the proliferation of ungoverned SaaS AI tools — reducing security risk and consolidating spend.
The Model Router directs simple tasks to cost-efficient models and reserves premium LLMs for complex reasoning — dramatically reducing per-query AI spend at scale.
Autonomous agents handling routine HR, IT, Finance, and Legal tasks free knowledge workers to focus on high-value, judgment-intensive work.
With 5,700+ pre-built skills in the registry and a production-grade runtime already in place, new agent capabilities are deployed in days — not months-long development cycles.
Every AI interaction runs through the OS security layer — eliminating the compliance blind spots created by employees using personal AI accounts for work tasks.
Healthcare organizations must ensure that AI systems handling Protected Health Information (PHI) maintain strict access controls, audit logs, and data residency requirements.
ibl.ai enforces RBAC at the OS layer, logs every data access event, supports on-premises or private cloud deployment to keep PHI within your boundary, and provides BAA-ready infrastructure configuration.
Educational institutions using AI must protect student education records and ensure that AI systems do not expose student data to unauthorized parties — including across multi-tenant deployments.
ibl.ai's federated memory layer enforces per-student data isolation, multi-tenant boundaries prevent cross-institution data access, and all student data interactions are fully auditable — as proven at learn.nvidia.com.
Public companies must maintain integrity and auditability of financial data and systems. AI agents accessing or generating financial information must operate within controlled, auditable environments.
ibl.ai provides immutable audit trails for all agent actions touching financial systems, enforces separation of duties via RBAC, and supports the change management controls required for SOX-compliant AI operations.
Government agencies and their contractors require AI infrastructure that meets federal security standards for cloud services — including continuous monitoring, incident response, and supply chain risk management.
ibl.ai is architected for FedRAMP-aligned deployments with support for GovCloud environments, full source code transparency for security review, sandboxed execution, and the access control frameworks required for federal authorization pathways.
See how ibl.ai deploys autonomous AI agents you own and control — on your infrastructure, integrated with your systems.