AI Agents
Building, deploying, and managing autonomous AI agents for workflow automation, customer support, internal operations, and more.
AI agents represent the next evolution in enterprise automation—intelligent systems that can reason, plan, and take action autonomously. Unlike simple chatbots, AI agents handle complex multi-step tasks across customer support, internal operations, data analysis, and specialized workflows. Discover how agentic AI is transforming how organizations operate.
464 articles in this category

Grow Without the Bloat: The AI Playbook for Expanding Your Institution
A practical guide to using a governed, model-agnostic AI layer to expand enrollment, advising capacity, and credential offerings—while keeping costs predictable and data inside your institution.

Clearing The Inbox: Advising & Admissions Triage With ibl.ai
How to deploy an agentic triage layer across your website and LMS that resolves routine admissions/advising questions 24/7, routes edge cases with context, and gives leaders first-party analytics—so staff spend time on pathways, not copy-paste replies.

A Biased Way to Pick an Agentic AI Platform for Your University
A candid (and cheerfully biased) field guide for campus leaders to evaluate agentic AI platforms—covering cost realism, on-prem governance, education-native plumbing (LTI/xAPI), governed memory, analytics, and the developer experience needed to actually ship.

Standards That Matter (LTI, xAPI): Why Education-Native Plumbing Beats Generic Chat
A practical look at how LTI and xAPI turn AI from “just a chatbot” into a campus-ready mentoring platform—and why ibl.ai’s education-native plumbing outperforms general-purpose chat tools.

How ibl.ai Fits (Beautifully) Into Any University AI Action Plan
This article shows how ibl.ai—an on-prem/your-cloud AI operating system for educators—maps directly to university AI Action Plans by delivering course-aware mentoring, faculty-controlled safety, and first-party analytics that tie AI usage to outcomes and cost.

Weekly Platform Updates — October 6, 2025
Weekly platform update for October 6, 2025, featuring In-Chat Uploads, Instructor Safety Controls, and the Instructor History Panel—plus a spotlight on the Italian-Speaking Community Mentor and the ibl.ai × Morehouse College partnership.

Build vs. Buy vs. “Build on a Base”: The Third Way for Campus AI
A practical framework for higher-ed teams choosing between buying an AI tool, building from scratch, or building on a campus-owned base—covering governance, costs, LMS integration, analytics, and why a unified API + SDKs unlock faster, safer agentic apps.

ibl.ai On Thinkific: Investling’s AI Mentor
How Investling embedded ibl.ai directly into Thinkific to deliver a goal-aware, risk-profiled investing mentor—with in-video chat, mobile access, and persistent learner memory that turns passive lessons into personalized coaching.

AI That Moves the Needle on Learning Outcomes — and Proves It
How on-prem (or university-cloud) ibl.ai turns AI mentoring into measurable learning gains with first-party, privacy-safe analytics that reveal engagement, understanding, equity, and cost—aligned to your curriculum.

ibl.ai: An AI Operating System for Educators
A practical blueprint for an on-prem, LLM-agnostic AI operating system that lets universities personalize learning with campus data, empower faculty with control and analytics, and give developers a unified API to build agentic apps.

ibl.ai: The Platform for Campus Builders
A practical look at how ibl.ai gives universities Python/Web SDKs and a unified API to build, embed, and measure agentic apps with campus data—on-prem or in their cloud.

ibl.ai Evidence of Impact
An academic analysis of the ibl.ai platform — the learning theories behind its design, the features that drive student engagement, and documented learning outcomes from deployments at GWU, Morehouse, and Syracuse.

American University of Sharjah × ibl.ai: Course-Tuned AI Mentors for Calculus & Physics
AUS and ibl.ai are launching a fall pilot of course-tuned AI mentors for Calculus and Physics that use a code interpreter to compute, visualize, and cite instructor-approved resources—helping students learn reliably and transparently.

Seamless LTI Deep Linking in Canvas, Brightspace and Blackboard with ibl.ai
A step-by-step walkthrough of how ibl.ai supports LTI Deep Linking in Canvas, Brightspace, Blackboard, and other compliant LMS platforms—allowing instructors to embed AI mentors directly into courses with minimal setup and a seamless launch experience.

Human-In-The-Loop Course Authoring With ibl.ai
This article shows how ibl.ai enables human-in-the-loop course authoring—AI drafts from instructor materials, faculty refine in their existing workflow, and publish to their LMS via LTI for speed without losing academic control.

Guided, Proactive Mentors on ibl.ai
Guided, proactive mentors from ibl.ai are course-aware assistants that know your units and outcomes, nudge learners with timely suggestions, and cite your slides/readings by default—bringing structure, transparency, and better study habits to every class.

Per-Course and Per-Student Mentors on ibl.ai
How ibl.ai enables per-course and per-student assistants that answer with cited sources, follow instructor-defined pedagogy, and respect domain-specific safety—so campuses get precision, transparency, and control without the complexity.

Cited Answers By Design with ibl.ai
An overview of ibl.ai’s Document Retrieval—answers that cite the exact lecture/slide/page, a ranked Source Panel that updates as you chat, one-click opening of the originals, and admin-level visibility controls—so campuses get transparent AI that teaches students to verify claims and helps faculty keep content governance simple.

UCSD's ibl.ai Collaboration
UC San Diego is partnering with ibl.ai to pilot ibl.ai, an instructor-centered assistant that analyzes student drafts and suggests top, rubric-aligned comments from UCSD’s approved comment banks—keeping faculty in full control while scaling high-quality feedback in writing-intensive courses.

Security-First LMS Integration
A practical, standards-aligned overview of how ibl.ai integrates with Canvas, Blackboard, and Brightspace using admin-registered LTI 1.3, optional, IT-approved RAG ingest, and course-scoped links—delivering security, transparency, and instructor control without fragile workarounds.

How ibl.ai Makes AI Simple and Gives University Faculty Full Control
A practical look at how ibl.ai pairs “factory-default” simplicity with instructor-level control—working out of the box for busy faculty while offering deep prompt, corpus, and safety settings for those who want to tune pedagogy and governance.

How ibl.ai Keeps Your Campus’s Carbon Footprint Flat
This article outlines how ibl.ai enables campuses to scale generative AI without scaling emissions. By right-sizing models, running a single multi-tenant back end, enforcing token-based (pay-as-you-go) budgets, leveraging RAG to cut token waste, and choosing green hosting (renewable clouds, on-prem, or burst-to-green regions), universities keep energy use—and Scope 2 impact—flat even as usage rises. Built-in telemetry pairs with carbon-intensity data to surface real-time CO₂ per student metrics, aligning AI strategy with institutional climate commitments.

How ibl.ai Makes Top-Tier LLMs Affordable for Every Student
This article makes the case for democratizing AI in higher education by shifting from expensive per-seat licenses to ibl.ai—a model-agnostic, pay-as-you-go platform that universities can host in their own cloud with full code and data ownership. It details how campuses cut costs (up to 85% vs. ChatGPT in a pilot), maintain academic rigor via RAG-grounded, instructor-approved content, and scale equity through a multi-tenant deployment that serves every department. The takeaway: top-tier LLM experiences can be affordable, trustworthy, and accessible to every student.

Microsoft Education AI Toolkit
Microsoft’s new AI Toolkit guides institutions through a full-cycle journey—exploration, data readiness, pilot design, scaled adoption, and continuous impact review—showing how to deploy AI responsibly for student success and operational efficiency.