AI Agents
Production-ready AI agents you can deploy on infrastructure you own, with any LLM you choose — built on the ibl.ai Agentic OS.
20 pages
- AI Client Intake Agent for Law Firms
- AI Clinical Documentation Agent, HIPAA-Ready
- AI Contract Review Agent for Law Firms
- AI Legal Research Agent for Law Firms
- AI Prior Authorization Agent, HIPAA-Ready
- AI Tutoring Agent for Schools & Universities
- Autonomous Medical Coding Agent, HIPAA-Ready
- Career Development Agent for Enterprise
- Compliance Agent for Enterprise
- Customer Support Agent for Enterprise
- Document Processing Agent for Enterprise
- HR Support Agent for Enterprise
- IT Help Desk Agent for Enterprise
- Knowledge Management Agent for Enterprise
- KYC/AML Agent for Financial Services
- Onboarding Agent for Enterprise
- Operations Agent for Enterprise
- Personal Learning Agent for Enterprise
- Sales Enablement Agent for Enterprise
- Training Creation Agent for Enterprise
What's in the AI Agents Library
Each entry in this library is a production AI agent — a configured combination of a model, a system prompt, a tool set, and behavioral guardrails — that runs on the ibl.ai platform inside the customer's own infrastructure. The agent code is open source, the model is the customer's choice (Claude, GPT, Gemini, Llama, DeepSeek, Qwen, or any OpenAI-compatible provider), and the data the agent operates on never leaves the customer's environment.
The agents cluster into a few groups by what they do: clinical (prior auth, intake triage, clinical documentation), revenue cycle (KYC, AML, sanctions screening, advisor copilot), IT and HR (help desk, onboarding, internal Q&A), academic (advising, tutoring, course content, IEP drafting), and customer-facing (support automation, lead qualification). Each agent's page shows the workflow, the integrations it needs, the compliance posture, and the cost math at typical scale.
The full set of pre-built agent configurations also lives in the open source claws repository — see github.com/iblai/claws for the configuration files organized by vertical. Browse the agents below, then connect them to your data sources through MCP, LTI 1.3, or direct API integration. The deployment model is the same for every agent: orchestration runs on ibl.ai, compute and data stay in your perimeter.
Related on ibl.ai
What AI agents does ibl.ai document here?
These 20 pages describe agents built for a specific job — document processing, compliance review, onboarding, client intake, sales enablement, operations, training creation, and more. Each explains what the agent does, the systems it connects to, the guardrails it runs behind, and what deploying it involves.
Can these agents be modified or replaced?
Yes — that is the point of the ownership model. Every agent is a configuration you receive and can edit, not a hosted black box: you change its instructions, swap the model behind it, add or remove its tools, and run it inside your own infrastructure. An agent you cannot inspect is one you cannot audit, which is why the definitions are open rather than proprietary.
What makes the ibl.ai platform different?
ibl.ai is the agentic AI platform where you own all the code and the data. You self-host the entire stack inside your own perimeter, run it model-agnostic across any LLM and switch anytime, and pay by usage with no per-seat pricing — so you can deploy anywhere: your cloud, on-premise, GovCloud, or fully air-gapped.