Deploy secure, institution-owned AI agents that integrate with your existing stack — without sacrificing compliance, control, or your team's sanity.
Reviewing overnight monitoring alerts — three separate SaaS AI tools flagged authentication errors. Each vendor requires a separate support ticket.
Fragmented AI vendor ecosystem creates multiple failure points and no unified visibility across tools.
Emergency meeting with CISO: a faculty member used a consumer AI tool to process student data, triggering a potential FERPA incident review.
Shadow AI usage is uncontrollable when no sanctioned, easy-to-use institutional AI exists for faculty.
Help desk ticket backlog review — 140+ open tickets, 30% are repetitive password resets and LMS access questions that tier-1 staff handle manually.
High-volume, low-complexity tickets consume staff capacity that should go toward research infrastructure support.
Call with Canvas admin team about a new AI tutoring vendor. Their integration requires storing student data on third-party servers outside institutional control.
Vendor data residency requirements conflict with university data governance policy and research data agreements.
Preparing a budget justification for the Provost — struggling to quantify ROI on three separate AI pilot tools with no unified reporting.
Siloed AI tools produce siloed metrics, making institutional ROI nearly impossible to demonstrate clearly.
Responding to a researcher's complaint that the AI writing assistant the library licensed doesn't connect to the university's research data repository.
Point solutions don't integrate with research workflows, reducing adoption and creating frustrated stakeholders.
Single-pane dashboard review of all deployed AI agents across the institution — all systems nominal, usage metrics up 12% week-over-week.
Agentic OS provides unified monitoring, logging, and alerting across all deployed agents running on university infrastructure.
CISO check-in is a standing 15-minute sync. All AI interactions are logged, auditable, and processed on-premises — no external data exposure.
ibl.ai's architecture keeps all student and research data within institutional infrastructure, eliminating shadow AI risk by providing a sanctioned alternative.
Help desk ticket review — volume down 45%. An AI support agent handles tier-1 queries autonomously, escalating only complex issues to staff.
A purpose-built IT support agent resolves password resets, LMS access issues, and software requests without human intervention, 24/7.
Brief sync with Canvas admin — MentorAI is live inside Canvas via LTI. Student data never leaves the university's own cloud environment.
Native integrations with Canvas, Blackboard, Banner, and PeopleSoft mean AI capabilities extend existing systems rather than replacing them.
Presenting a clean AI ROI dashboard to the Provost — unified metrics across tutoring, help desk, and content tools from a single platform.
Agentic OS aggregates usage, engagement, and outcome data across all agents, enabling institution-wide AI reporting in one place.
Approving a researcher's request to deploy a custom AI agent for their lab's data analysis workflow — provisioned in under 2 hours.
Agentic OS lets IT provision, configure, and govern custom AI agents for research teams without bespoke development or new vendor contracts.
Research universities handle sensitive student records, grant data, and PII across dozens of systems. Most AI vendors require data to leave institutional infrastructure, creating compliance exposure.
A single FERPA violation can cost $100K+ in remediation, legal fees, and reputational damage. Research data breaches can jeopardize federal grant eligibility.
ibl.ai deploys all agents on customer-owned infrastructure. Student and research data never touches ibl.ai servers. SOC 2, FERPA, and HIPAA compliance is built into the architecture, not bolted on.
IT teams are managing 5-10 separate AI point solutions — each with its own contract, API, support channel, and data silo — making governance and cost control nearly impossible.
Fragmented tools increase total cost of ownership by 40-60%, create integration debt, and make it impossible to build a coherent institutional AI strategy.
Agentic OS is a single platform for building, deploying, and governing all AI agents. Institutions own the code and infrastructure. Switching costs drop to zero because you own everything.
Research universities have complex, high-volume IT support needs spanning students, faculty, researchers, and administrative staff — often 24/7 across global time zones.
Tier-1 tickets consume 50-60% of help desk staff time. After-hours coverage gaps frustrate researchers on deadline and reduce institutional productivity.
A purpose-built IT support agent handles tier-1 queries autonomously around the clock — password resets, software access, LMS troubleshooting — escalating only when needed.
When faculty and students can't access sanctioned AI tools easily, they use consumer tools like ChatGPT with institutional data, creating uncontrolled compliance and security risk.
Shadow AI incidents are rising 3x year-over-year in higher education. Each incident requires investigation, remediation, and policy enforcement that strains IT and legal teams.
ibl.ai provides a compelling, easy-to-use institutional AI experience that reduces the incentive for shadow tool usage — while giving IT full governance and audit capability.
IT Directors are under pressure to justify AI investments to Provosts, CFOs, and Boards — but siloed tools produce siloed metrics that don't tell a coherent institutional story.
Without clear ROI data, AI budgets are vulnerable to cuts. IT leaders lose credibility and strategic influence over the university's AI direction.
Agentic OS provides unified analytics across all deployed agents — usage, engagement, cost savings, and learning outcomes — enabling compelling, data-driven ROI reporting.
Vendors should clearly state that data stays on your infrastructure. Vague answers about 'encryption' or 'compliance certifications' without data residency guarantees are red flags.
Look for pre-built, maintained integrations — not 'we can build that' promises. LTI 1.3 certification for LMS integration and standard OAuth/SAML for SSO are baseline requirements.
Institutions should own 100% of agents, data, and configurations. Any vendor claiming ownership of your customizations or making export difficult is a lock-in risk.
SOC 2 Type II certification is the minimum bar. Look for AI-specific security controls, not just general cloud security. Verify incident response SLAs are contractually binding.
ibl.ai eliminates institutional AI liability by keeping all data on university-owned infrastructure.
Unlike SaaS AI vendors that process data on their servers, ibl.ai deploys entirely within our environment — satisfying FERPA, HIPAA, and research data governance requirements by design.
Zero third-party data exposure events since deploymentThe university owns its AI assets permanently — no vendor dependency, no lock-in risk.
We own the agent code, training data, and infrastructure. If we ever change platforms, we take everything with us. This is a strategic institutional asset, not a subscription service.
100% institutional ownership of all AI agents and dataA unified AI platform reduces total cost of ownership versus managing multiple point solutions.
Consolidating five separate AI tool contracts onto one platform is projected to reduce AI-related licensing and integration costs by 35-50% annually.
$400K–$800K estimated annual savings for a mid-size research universityFaculty and researchers get purpose-built AI tools that fit their workflows — not generic chatbots.
ibl.ai's Agentic OS lets us deploy specialized agents for research support, course design, and student advising — each with defined roles, knowledge bases, and guardrails.
Purpose-built agents show 3x higher adoption rates than generic AI toolsMentorAI delivers personalized student support at scale, improving retention without adding headcount.
AI tutoring agents provide 24/7 personalized learning support, identifying at-risk students early and connecting them to resources — all within our existing LMS environment.
Early adopters report 15-20% improvement in course completion ratesAgentic Content and Agentic Video accelerate course development while maintaining academic quality standards.
Faculty can produce, adapt, and localize course content in hours rather than weeks, with AI handling production while instructors maintain full editorial control.
Content production time reduced by up to 70%ibl.ai's architecture eliminates the most common AI security risk: data leaving institutional control.
All model inference, data processing, and agent interactions occur within our infrastructure perimeter. There is no data pathway to ibl.ai or any third-party AI provider.
Meets or exceeds NIST AI RMF, FERPA, HIPAA, and SOC 2 requirementsFull audit logging and explainability for every AI interaction supports compliance and incident response.
Every agent interaction is logged with user identity, timestamp, input, and output — enabling complete forensic reconstruction for compliance audits or security investigations.
Complete audit trail for 100% of AI interactionsProviding a sanctioned, governed AI platform is the most effective shadow AI mitigation strategy.
When faculty and students have access to a capable, easy-to-use institutional AI, the incentive to use ungoverned consumer tools drops dramatically — reducing our attack surface.
Shadow AI incidents reduced by 60-80% at comparable institutionsAn AI support agent resolving 45% of tier-1 tickets autonomously saves approximately 4,200 staff hours annually at a research university with 25,000+ users — equivalent to 2 FTE positions.
Replacing 5-7 separate AI point solutions with a single Agentic OS platform eliminates redundant licensing, integration maintenance, and vendor management overhead.
Preventing 2-3 FERPA incidents annually through governed AI deployment avoids an estimated $50K-$75K per incident in legal, remediation, and compliance costs.
A 1% improvement in retention at a 20,000-student research university with $6,000 average net tuition revenue per student generates approximately $1.2M in preserved annual revenue.
AI agents handling routine researcher IT requests — software provisioning, data access, compute allocation — free senior IT staff to focus on high-value research infrastructure projects.
Audit your current AI tool landscape, data governance policies, and infrastructure capacity. Identify FERPA/HIPAA touchpoints and map existing integrations with Canvas, Banner, and other core systems.
Work with ibl.ai's implementation team to deploy the Agentic OS platform within your cloud or on-premises environment. Configure SSO, establish audit logging, and validate security controls with your CISO.
Deploy a purpose-built IT support agent as your first use case. This delivers immediate, measurable ROI, builds team confidence, and creates a governance template for future agent deployments.
Connect MentorAI to Canvas or Blackboard via LTI 1.3. Configure agent personas, knowledge bases, and escalation rules in collaboration with academic IT and faculty stakeholders.
Formalize your AI agent governance policy — covering provisioning, access control, audit review, and acceptable use. Use this framework to onboard additional departments and research teams systematically.
See how ibl.ai deploys AI agents you own and control—on your infrastructure, integrated with your systems.