Shelf

Shelf: A Knowledge-First Operating System for Agentic AI

Shelf is an enterprise platform built on a simple premise: AI agents are only as good as the knowledge they reason over. Founded in 2017 and headquartered in New York, with offices in San Francisco and Warsaw, the company started in contact-center knowledge management and has evolved into a knowledge-and-data-first agentic AI platform — one that constructs an AI Data Model of a business so agents, copilots, and search all answer from the same trusted, governed source.

The platform combines several layers: Shelf Core for knowledge management and governance, an Agentic OS for deploying AI agents grounded in company knowledge, CortexAI for workflow orchestration, and multi-channel delivery so answers reach employees and customers over chat, voice, and email. Instead of pointing a language model at a pile of documents, Shelf models business logic and data relationships so agents can reason accurately across complex operations.

Key Features

• AI Data Model that unifies enterprise content and models business logic for agent reasoning
• Agentic OS for deploying AI agents grounded in governed company knowledge
• CortexAI workflow orchestration for multi-step automation across systems
• Knowledge management and governance layer with guardrails, permissions, and content quality controls
• Multi-channel delivery of answers via chat, voice, and email
• Documented contact-center outcomes including a 25% reduction in average handle time and 95% first-contact resolution in customer case studies

Ideal Use Case

Shelf's flagship use case is the contact center: support organizations at scale where agents (human or AI) must answer from policy documents, product knowledge, and procedures without hallucinating. It extends to any enterprise deploying AI assistants that have to be right — healthcare plans, financial services, CPG, delivery, and rideshare operations — where the cost of a wrong answer is measured in compliance exposure or churn.

How Shelf differentiates

Wiki-style knowledge tools organize pages for humans to read; Shelf structures knowledge, data, and guardrails for machines to reason over. The company raised a $52.5 million Series B led by Tiger Global and Insight Partners in 2021 after posting 4x ARR growth, and its customer roster includes Amazon, HelloFresh, Nespresso, Roku, and American Family. Analyst recognition followed the agentic pivot: Gartner Cool Vendor 2025 and IDC Innovator 2025.

FAQ

What is an AI Data Model? It is Shelf's structured representation of a company's knowledge, data relationships, and business logic, built so AI agents can reason over verified information instead of raw document piles.

Is Shelf just for contact centers? No. Contact centers are the flagship use case, but the platform serves operations across healthcare, financial services, CPG, delivery, and other industries where AI answers must be trustworthy.

How is Shelf priced? Pricing is not published. Deployments are scoped through an enterprise sales process; the site directs buyers to "Talk to an Expert."

How is Shelf different from a wiki tool like Guru? Wikis store and surface pages for people. Shelf adds a data model, governance guardrails, agent orchestration, and multi-channel delivery so AI systems — not just humans — can consume and act on knowledge safely.

tl;dr

Shelf turns messy enterprise knowledge into a governed AI Data Model that agents and copilots can trust, with contact-center results to prove it, $52.5M from Tiger Global and Insight Partners, and customers like Amazon and HelloFresh. Enterprise pricing only.

Related

Looking for more options? Browse the AI Infrastructure directory or read our best AI infrastructure tools listicle. Shelf is also tracked on Crunchbase.