Double vs Document360
Side-by-side trajectory, velocity, and editorial themes.
Double is folding an AI copilot into the core of the bookkeeping loop.
Double is an AI-assisted bookkeeping product built around a conversational assistant, Ask Double. Recent releases push that assistant deeper into the accounting workflow: it can now create transactions from documents or plain-English descriptions, edit posted transactions in place, and work with live spreadsheets in chat. Client-facing work is progressing too, with in-context Q&A on published financials.
The direction is unmistakable — Ask Double is moving from a helper that answers questions to one that performs the bookkeeping itself: reading source files, posting and editing entries, and handling multi-transaction documents. In parallel, Double is turning the client portal into a two-way surface. The product is betting that conversational, document-driven data entry becomes the default way books get kept.
Expect the beta features (loan amortization, live spreadsheets) to reach general availability and the assistant to take on more of the reconciliation and categorization loop.
Document360 is rebuilding the knowledge base around AI agents — readable by them and operable through them.
Document360 is a knowledge-base and documentation platform shipping monthly point releases. The recent arc is heavily AI-shaped: an MCP server connects ChatGPT, Claude, and Copilot to the KB, then expands to manage the full content lifecycle — search, create, update, assign reviewers, and publish — from inside an AI assistant. The June release adds auto-generated llms.txt so AI agents can discover and cite docs accurately, plus native Mermaid diagrams. Enterprise plumbing (SCIM, multiple JWT configs, CSP controls) rounds out the cadence.
The product is positioning the knowledge base for the AI-agent era on two fronts: making docs machine-readable and citable (llms.txt, MCP search), and making content operations agent-driven (publish/workflow via MCP). Around that core bet, Document360 keeps hardening multilingual, security, and analytics for enterprise buyers.
Expect continued deepening of the MCP and AI-discoverability surface — more lifecycle actions exposed to assistants and richer agent analytics — alongside the steady enterprise security and localization work.
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