Contextual AI vs Harvey
Relationship
Contextual AI Platform and Harvey Vault do comparable work on document extraction; similar scale (private); ships AI agent and application rather than the same layer.
Assembled from the recorded fields for this pair, not hand-checked. The comparison below is read from each company’s own profile.
3 of 5 capabilities — Shares agent orchestration, document extraction and knowledge retrieval.
Ludbee capability tags · from the product recordsDifferent layer — Harvey ships AI agent and application, not the same layer.
Ludbee product recordsAligned comparison
Capability overlap
Shared · 3
Not verified for Harvey · 2
Recorded for Contextual AI. Harvey’s product records say nothing either way — a missing record is not a missing capability.
Not verified for Contextual AI · 3
Recorded for Harvey. Contextual AI’s product records say nothing either way — a missing record is not a missing capability.
Products, side by side
Algorithmic pairing — assembled from recorded fields, not hand-checked
Contextual AI
No shared stack layer with the other side.
Harvey
No shared stack layer with the other side.
No counterpart
Contextual AI sells these in a stack layer with no product recorded for Harvey yet — nothing on the other side to compare them against.
API service
Parsing, reranking and grounded-generation endpoints sold individually for teams building their own retrieval stack.
Agent platform
Orchestration layer inside the Contextual AI Platform providing an enterprise-scale agent runtime, no-code agent/workflow builder and AI toolkit for multi-step reasoning and multi-tool orchestration over enterprise data.
Platform
Builds and serves retrieval-augmented agents over an organisation's own documents.
Harvey sells these in a stack layer with no product recorded for Contextual AI yet — nothing on the other side to compare them against.
Application
Legal work platform that drafts, reviews and researches documents for law firms and in-house teams.
Analyzes legal-AI adoption across a firm and recommends improvements.
Legal, regulatory and tax research across licensed sources, answering questions with citations back to the underlying authority.
Cross-product personalization layer that stores and applies a lawyer's preferred writing conventions, analytical approach and formatting across Harvey's tools (Web App, Outlook, Word Add-In, playbook runs).
Repository for a firm's legal documents that runs queries and extractions across a whole matter at once rather than file by file.
AI agent
Delegates end-to-end legal research and work-product creation to AI agents, executing multiple tasks in parallel with cited, review-ready outputs.