What is Agentic OS and how does it differ from a traditional data warehouse?

Agentic OS is an AI operating system that creates a secure, per-user memory layer by unifying data from your systems of record — SIS/LMS, HRIS, CRM, ERP, EHR/EMR, and case or document management. Unlike traditional data warehouses, it provides policy-aware retrieval with fine-grained consent controls, so AI agents reach contextual data about a specific record — a learner, an employee, a citizen, a client, a matter, or a patient — under the regime that governs it.

Can we deploy Agentic OS in our own infrastructure?

Yes. Agentic OS can be deployed on-premise or in your cloud (AWS, Azure, GCP) using your VPC, KMS, and IAM. You receive full source code access to connectors, policy engine, and agent interfaces—no vendor lock-in.

What systems does Agentic OS integrate with?

Agentic OS connects to the systems of record an organization already runs: HRIS and ERP (Workday, Oracle, SAP, Dynamics), CRM and service desks (Salesforce, HubSpot, ServiceNow, Zendesk), EHR/EMR (Epic, Cerner, Meditech), document and case management (iManage, NetDocuments, SharePoint, Clio), SIS and LMS (Banner, PeopleSoft, Canvas, Blackboard, Brightspace, Moodle), and identity providers (Azure AD/Entra, Okta, Google Workspace). Connectors run over the Model Context Protocol, so data is read in place rather than extracted into another store.

How does Agentic OS handle privacy and regulatory compliance?

Agentic OS includes privacy by design with field-level permissions, PII redaction, consent receipts, and selective disclosure. Each user controls what data is shared with AI agents, and all access is logged for audit purposes. Because the platform runs inside your own perimeter, the evidence stays with you — supporting FERPA, HIPAA/HITECH, SOX, PCI DSS, GDPR, and NIST 800-53 obligations rather than asking you to trust a vendor's attestation.

What AI agents can run on Agentic OS?

Agentic OS powers three primary agent types, whatever the industry: front-line agents for the people your organization serves, operations agents that run the work behind them, and administrative agents for oversight and reporting. In practice that means knowledge search, IT help desk, and customer support in the enterprise; citizen services, compliance, and procurement in government; case research, contract review, and discovery in legal; KYC/AML, fraud detection, and risk in financial services; clinical support, documentation, and prior authorization in healthcare; and enrollment, advising, and tutoring in education. All agents are LLM-agnostic and can use OpenAI, Claude, Gemini, or local models.

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Agentic OS (Operating System)

Unify HRIS, CRM, ERP, and ticketing data into a secure employee memory layer—powering knowledge search, IT help desk, sales enablement, and customer support agents. On ibl.ai you own all the code and the data, run it model-agnostic across any LLM, and pay with no per-seat pricing — so you can deploy anywhere, from your own cloud to a fully air-gapped network. No need to choose build vs. buy — you get both.

Sector:Higher Education Corporate Small Business K-12 Government Legal Financial Services Healthcare

Your Code. Your Data.Full ownership, zero vendor lock-in

Any LLM, Your ChoiceAir-gapped or any cloud provider's

85% Lower CostSignificantly cheaper at scale

AI TransformationPre-existing and custom agents

Want to read the source?View the code on GitHub →

1.6M+Platform Users

400+Organizations

MCP Architecture Guide for Enterprise

How to connect your corporate systems (HRIS, LMS, CRM, ticketing, knowledge base) to AI agents — step by step.

Read the Guide

Runs on

Air-Gapped AI Anthropic Claude Google Gemini Microsoft Copilot Amazon Bedrock OpenAI GPT NVIDIA NemoClaw OpenClaw

1 / 5

Live

Knowledge AgentEnterprise search and institutional knowledge Live

IT Help Desk AgentIssue resolution and ticket management Live

Sales Enablement AgentCompetitive briefs, deal strategy, outreach Live

Customer Support AgentTicket resolution and follow-ups Live

Onboarding AgentNew hire orientation and ramp-up Live

HR AgentPolicy, benefits, and people operations Live

Marketing AgentContent, campaigns, and SEO Live

Engineering AgentCode review, docs, project onboarding Live

Meeting AgentRecaps, action items, and follow-ups Live

Training AgentEmployee development and compliance Live

Data Analysis AgentReports, trends, and insights Live

Operations AgentWorkflow automation and process optimization

How ibl.ai compares

ibl.ai

Model choice

Any LLM — Claude, GPT, Gemini, Llama or open-source. Switch anytime.

Locked to Anthropic Claude models

Autonomous agents

Production-ready agents out of the box — plus the tools to build your own.

Chat assistant — you build & host your own agents

Privacy & ownership

100% self-hosted — private LLMs included. You own all the code, data & models.

Runs on Anthropic's cloud — your data leaves your walls

Cost at scale

Up to 85% lower — intelligent routing across providers, no per-seat lock-in.

Per-seat & per-token SaaS pricing

Delivery & services

Our engineers work with you to connect your data sources and build your agents.

Self-serve docs & standard support tiers

Want the full breakdown?Self-hosted & private LLM →See build vs. buy →Book a 30-min demo →

OS (Operating System) — Unify enterprise data into a secure employee memory layer

An Ownable AI Operating System for the Enterprise.

OS by ibl.ai connects HRIS, CRM, ERP, and ticketing systems over an MCP-based interoperability layer to assemble a secure, per-employee memory.

That memory gives your AI agents the right context—so every employee gets instant answers from institutional knowledge, every team a help desk, sales, support, and operations agent that knows the account, and every IT leader a compliance-ready platform.

Deployed in your infrastructure with your keys and your controls—including full code access.

For Employees: Answers Grounded in Your Own Systems

Unified Employee MemoryRole, team, entitlements, open tickets, owned accounts, and prior conversations—federated from your HRIS/CRM/ERP/ticketing and made available (with policy guardrails) to the employee's agent.

The Agents Employees Use DailyKnowledge search across every internal system, IT help desk for access and issue resolution, HR for policy and benefits, and meeting recaps with action items—each citing the source it used.

Privacy by DesignFine-grained consent and selective disclosure (e.g., hide compensation/health fields), so an agent answers only from what that employee may already see.

ResultFewer tickets, faster answers, and less time lost hunting across systems.

For Team Leads & Operations: Agents That Run the Work

Operational Context, Not GuessworkPulls CRM pipeline, ticket queues, project trackers, and system logs to draft competitive briefs, customer responses, campaign copy, and status reports.

Workflow AutomationsSales enablement briefs, support ticket triage, marketing campaigns, and reconciliation workflows—always citing approved company sources.

Operational ControlDepartment-level policies, versioned prompts, and cost and usage dashboards.

ResultMore time on strategy, less on repetitive coordination and manual reporting.

For IT & CISO: Own the Stack, Control the Risk

Runs in Your EnvironmentDeploy on-prem or in your cloud (AWS, Azure, GCP). Your VPC, your KMS, your IAM—no external data dependencies.

Full Code Access (No One Else Offers This)You receive source access to connectors, policy engine, and agent interfaces—no vendor lock-in.

Governance & ComplianceSOC 2/SOX/HIPAA support, RBAC, audit logs, retention policies, and data residency options.

Observability & Cost ControlUsage telemetry, model costs, performance traces, and red-team/replay tools for safe iteration.

ResultMaximum privacy, predictable cost, and accelerated AI roadmaps—under your control.

What OS Connects (Examples)

HRISWorkday, SAP SuccessFactors, BambooHR, ADP

LMSCornerstone, Docebo, Absorb, Degreed

CRMSalesforce, HubSpot, Microsoft Dynamics 365

ERP/FinanceSAP, Oracle, NetSuite

Identity & StorageAzure AD/Entra, Okta, Google Workspace, OneDrive/SharePoint, S3, GCS

What's Inside OS (Architecture Highlights)

MCP Integration LayerNormalizes access to HRIS/LMS/CRM/ERP via secure adapters

Employee Memory LayerPer-employee knowledge graph + vector index with policy-aware retrieval

Policy & Guardrails EngineField-level permissions, PII redaction, consent, rate/usage limits

Agent InterfacesCoach (employee), Training Assistant (L&D manager), Compliance Agent (IT/CISO)

Model Hub (LLM-Agnostic)OpenAI, Gemini, Anthropic, Llama, local/NPU options—hot-swappable

Event Bus & AutomationsTriggers for compliance deadlines, certification expirations, onboarding milestones

Audit & TelemetryEnd-to-end logs, prompt/response archives, cost and latency meters

Admin ConsoleConnectors, schemas, dataset scopes, memory visibility, and policy editing

Why OS Outperforms Typical Integration Hubs

Employee Memory LayerOS: Policy-aware, per-employee context | Typical: No unified memory

Runs in Your InfraOS: Your VPC, keys, IAM | Typical: Vendor cloud only

Full Code AccessOS: Source delivered, extensible | Typical: Black box / SDK limits

LLM-AgnosticOS: Swap models freely (incl. local) | Typical: Single-model dependency

Enterprise GovernanceOS: SOC 2/SOX-ready, selective disclosure | Typical: Generic role gates

Agent-ReadyOS: Standard coach/assistant/compliance interfaces | Typical: DIY agent plumbing

Benefits That Drive Impact

EmployeesTimely, contextual coaching across roles and departments.

L&D TeamsA dependable training assistant informed by real competency and performance data.

Leadership & ITA private, ownable AI foundation—no lock-in, full auditability, rapid innovation.

ibl.ai

The ibl.ai platform supplies secure memory and connectors, AI coaching experiences, and training delivery with analytics.

It designs competency-aligned curricula and issues portable, verifiable proof of skills — an ownable AI operating system for workforce development.

Experience OS Today

Architecture ReviewMap your HRIS/LMS/CRM/ERP and security requirements

Private PilotDeploy in your cloud with your datasets and policies

Schedule a DemoSee how OS unifies workforce data, safeguards privacy, and powers agents—with code you own.

What our partners say about us

Case Studies

Chris Gabriel | Google

Case Studies

Lorena Barba | George Washington University

Case Studies

Dr. Juana Mendenhall | Morehouse College

Juile Diop | MIT

Adam Tetelman | Nvidia

Jason Dom | American Public University System

Benjamin Breyer | Columbia University

Ken Fujiuchi | SUNY

Erika Digirolamo | Monroe College

David Flaten | SUNY

David Vise | Modern States Education Alliance

Linda Wood | ARM Institute (U.S. Department of Defense)

Case Studies

Chris Gabriel | Google

Case Studies

Lorena Barba | George Washington University

Case Studies

Dr. Juana Mendenhall | Morehouse College

Juile Diop | MIT

Adam Tetelman | Nvidia

Jason Dom | American Public University System

Benjamin Breyer | Columbia University

Ken Fujiuchi | SUNY

Erika Digirolamo | Monroe College

David Flaten | SUNY

David Vise | Modern States Education Alliance

Linda Wood | ARM Institute (U.S. Department of Defense)

Frequently Asked Questions

Unify your data first — then deploy agents

Agentic OS reasons over a unified knowledge layer. Here's why that ontology comes first, and how it's built.