LlamaIndex

LlamaIndex is an enterprise-focused platform for building document-centric AI agents and workflows. It combines agentic OCR, document parsing, structured extraction, and retrieval into a modular stack you can mix and match for your own use cases. The core audience is technical teams and enterprises that need to automate complex, document-heavy processes across finance, manufacturing, healthcare, and other regulated or data-intensive industries.

The product is structured around LlamaCloud for enterprise-grade document automation and a set of components like LlamaParse, LlamaExtract, and Index. On top of this, LlamaIndex provides a Workflows engine—an event-driven, async-first system for orchestrating multi-step AI processes, agents, and document pipelines. You typically start by signing up for LlamaCloud and following their documentation to wire these components into your own applications, especially modern Python apps (they explicitly call out FastAPI) and existing data workflows.

LlamaIndex is notably agentic: it’s designed not just to answer questions over documents, but to run multi-step, stateful workflows that parse, extract, index, and retrieve information, then feed that into agents that act on it. Their claims of "industry-leading" parsing and the ability to handle 90+ unstructured file types, embedded images, complex layouts, multi-page tables, and handwritten notes suggest strong capabilities for messy real-world documents, though independent accuracy benchmarks are not shown on the page. The Workflows engine is event-driven and async-first, which is a good fit if you’re already building in Python and need fine-grained control over long-running or branching processes.

According to the site, LlamaIndex has processed hundreds of millions of documents and supports large-scale, enterprise deployments, but details like supported LLM providers, specific model choices, and security/compliance certifications are not described in the provided content. Pricing is also not disclosed here. If you’re a non-technical user looking for an out-of-the-box chatbot or a simple document viewer, this is likely more infrastructure than you need; it’s better suited to developers and teams who want to compose their own document agents and integrate them directly into existing systems.