Search for document intelligence in 2026 and you will find one answer repeated everywhere: it is AI-powered software that extracts structured data from documents coming into a business. Invoices, purchase orders, contracts, insurance claims. The technology reads them, classifies them, and routes them into the right workflow. Tools like ABBYY, Hyperscience, and Azure Document Intelligence own this definition, and they are good at what they do.
However, that definition covers only half the story. It describes document intelligence for documents flowing inward. It says nothing about document intelligence for documents flowing outward: the proposals, pitch decks, investor updates, and research reports that leave your organization every day and land in the hands of clients, prospects, and investors. This post covers that second definition, why it matters more for sales and IR teams, and what it looks like in practice.
First, it helps to understand why the phrase splits in two directions and why that matters before choosing any tool.
Inbound document intelligence handles documents that arrive at your organisation and need to be processed. An accounts payable team receiving thousands of supplier invoices each month, a lending team reviewing mortgage applications, or an insurance company triaging claims: these all benefit from AI that reads incoming documents, extracts relevant fields, and feeds structured data into downstream systems. Notably, this category is mature. ABBYY, Hyperscience, Rossum, and Microsoft Azure all compete here, and the market has been growing for several years.
Outbound document intelligence handles documents that leave your organization and need to be understood. A sales team sending proposals to prospects, an investor relations team distributing quarterly LP reports, a consulting firm delivering strategy decks to clients: these all benefit from AI that reads outgoing documents, surfaces what recipients understood, and tells senders what to do next. Consequently, this category is newer. Fewer tools compete here, and the definition itself is still being established.
Libertify operates in the second category. Specifically, it is the document intelligence layer for documents you send, not documents you receive.
Consider what happens in a typical proposal workflow today. A sales rep spends two hours building a proposal, sends it to a prospect, and then waits. Two days later, with no reply, the rep sends a follow-up asking if they had a chance to review it. The prospect says they will circle back next week. Another five days pass. The rep follows up again. The deal stalls.
Throughout that entire sequence, the rep had no idea whether the prospect read the proposal, which sections held their attention, or what question formed in their mind but never made it into a reply. Furthermore, they had no signal telling them when to follow up or what to say when they did. As a result, they defaulted to a calendar-based cadence that treats every prospect identically regardless of actual engagement.
Outbound document intelligence changes that sequence entirely. Instead of guessing, the rep sees that the prospect opened the proposal three times, spent four minutes on the pricing section, and asked a question through the in-document AI assistant about implementation timelines. That signal tells the rep exactly when to follow up, what objection to address, and how to open the conversation.
Standard document tracking tools measure behavior: opens, time-on-page, and forwards. These are useful signals and a step above sending blind. However, behavior data tells you what a prospect did, not what they understood.
Outbound document intelligence goes further. Specifically, it captures four categories of signal that behavior tracking misses:
First, comprehension patterns. Which sections the reader re-read, which they skipped entirely, and which generated questions. Second, reader questions. If a document includes an AI assistant grounded in the document content, every question the reader asks becomes a signal about what is unclear or unresolved. Third, stakeholder behavior. Not just who forwarded the document, but which sections the new stakeholder focused on and how their engagement pattern differs from the original recipient. Fourth, next-move recommendations. Rather than leaving the sender to interpret raw data, outbound document intelligence converts signals into a prioritised action: who to contact first, what objection to address, and which section to rewrite.
Together, these signals close the gap between sending a document and understanding what it actually did.
Libertify sits on top of any PDF, PowerPoint, or Word document you already send. It requires no rebuild of existing documents and goes from upload to first send in about three minutes. Readers receive a guided AI walkthrough that helps them navigate the document, and an in-document assistant that answers questions grounded strictly in the document content. Senders receive a stream of comprehension signals and a clear recommendation for what to do next.
Today, teams at Amundi, Société Générale, EY, Generali AM, and ODDO BHF use Libertify specifically because the documents they send carry real financial and commercial consequence. Opens alone tell them nothing about whether an LP understood the quarterly report or whether a client is ready to proceed. Outbound document intelligence tells them both. See how it works across sales, consulting, and investor relations workflows in the Libertify success stories, and explore specific use cases at libertify.com/use-cases/.
What is document intelligence?
Document intelligence is AI that reads and interprets documents to generate actionable signals. Inbound document intelligence processes documents arriving at an organisation, such as invoices and contracts, and extracts structured data. Outbound document intelligence processes documents leaving an organisation, such as proposals and investor reports, and surfaces what recipients understood and what the sender should do next.
Is document intelligence the same as intelligent document processing?
Not exactly. Intelligent document processing (IDP) is the established term for inbound document automation: OCR, data extraction, classification, and workflow routing. Document intelligence is a broader term that also covers the outbound layer, meaning what happens when documents reach their recipients and how senders can act on that understanding.
What is the difference between document intelligence and document tracking?
Document tracking reports behavioral signals: opens, time-on-page, and forwards. Document intelligence goes further, capturing comprehension signals such as what readers understood, what confused them, what questions they asked, and what the sender should do next as a result.
Which teams benefit most from outbound document intelligence?
Sales teams sending proposals and pitch decks, investor relations teams distributing LP reports and fund factsheets, and consulting firms delivering strategy decks and client deliverables. In each case, the document carries commercial or financial consequence, and the sender needs to know not just that it was opened but what it actually did.
How is Libertify different from a document tracking tool like DocSend?
DocSend tracks opens, page-level time, and forwards. Libertify adds the comprehension layer: what the reader understood, what questions they asked, and what the sender should do next. Furthermore, Libertify includes an in-document AI assistant grounded in the document content, which turns the document itself into a two-way signal rather than a one-way send.
Upload any document to Libertify and go from send to first comprehension signal in about three minutes. No rebuild required. Start with Libertify →