# From piles of paper to records you can use · Understand · Dscvry > Understand turns what the AI senses into structured, searchable records, and answers questions with the source behind every fact. Source: https://dscvryai.com/technology/understand/ # From piles of paper to records you can use. Extract, classify, structure, summarize, translate and search, so every document, call and message becomes data you can rely on. What the AI can understand · How it works · Wherever the work is. Hosted Private cloud On-premise Edge Air-gapped ## The facts exist. They just don't connect. The renewal date is in an email, the notice period is in a contract, the owner is in a spreadsheet. Every answer means opening all three, and hoping nothing was missed. ### Spread across formats. PDFs, spreadsheets, emails and exports each hold part of the picture. ### Inconsistent shapes. Every supplier, carrier and system writes the same fact a different way. ### Answers without sources. Search and chat tools return confident text with nothing to check it against. ## What the AI can understand. Pull out the fields that matter. ### Extract Fields, tables and line items taken off the page into a schema-ready record, and checked against the schema before anything downstream sees it. See it in invoice errors → https://dscvryai.com/use-cases/invoice-errors/ Sorted before anyone opens it. ### Classify Emails, documents and requests labelled by type, priority and owner as they arrive, with the reason for each label kept, so the right team starts on the right thing. See it in customer complaints → https://dscvryai.com/use-cases/customer-complaints/ Many formats. One shape. ### Structure The same fact written three different ways becomes one consistent record: same fields, same units, same dates. See it in purchase orders → https://dscvryai.com/use-cases/purchase-orders/ The points that matter, and where they came from. ### Summarize Long documents and threads condensed into the decisions, dates and open questions, with each point linked to the passage it came from. See it in customer complaints → https://dscvryai.com/use-cases/customer-complaints/ Read in one language, worked on in another. ### Translate Supplier emails, contracts and reports handled in the language they arrive in, with part numbers, dates and amounts carried across exactly. See it in supplier quality → https://dscvryai.com/use-cases/supplier-quality/ Find it across everything you hold. ### Search Reports, work orders, manuals and logs searched together, with each result showing where it came from and why it matched. See it in equipment failure → https://dscvryai.com/use-cases/equipment-failure/ Answers with sources, or no answer. ### Answer Questions answered from your own documents, with a citation for every fact. Where the sources don't say, the AI says so instead of guessing. See it in contract compliance → https://dscvryai.com/use-cases/contract-compliance/ ## Structure first. Language last. Most understanding is parsing, matching and checking, which rules and small models do well. A language model is used only where it adds something, and never without a source. Everything sensed Sense Pages, transcripts, frames and feeds. Parse & normalise Rules & code Dates, units, names and references made consistent. Extract & link Specialized model Fields pulled out and linked into one record. Search Specialized model Relevant passages found and ranked. Answer Reasoning Written only from what was found, with citations. ## Give notice by 2 July. Three sources. Question · Northline Haulage notice date. An answer you can check in a minute, not one you have to trust. **Found.** Renewal on the same terms from 30 September. **Found.** Either party may end the agreement on 90 days' written notice. **Found.** Contract owner is J. Patel, procurement. **Worked out.** 30 September minus 90 days is 2 July. Illustrative example. Supplier, contract and dates are fictional. ## Built to be checked. Understanding is only useful if a person can see where it came from. - ### A source for every fact. Each value and each answer links back to the page, cell or second it came from. [Documents](https://dscvryai.com/technology/sense/documents/) - ### Knows what it doesn't know. When the sources are silent, the AI says so instead of filling the gap. [How Check works](https://dscvryai.com/technology/check/) - ### Permission-aware. People only see answers drawn from documents they are allowed to open. [Security & trust](https://dscvryai.com/security/) ## Where it shows up. Problems that start with scattered information. Did they deliver what the contract says? ### Contract compliance See whether obligations were actually met. See how → https://dscvryai.com/use-cases/contract-compliance/ Which invoices are we overpaying? ### Invoice errors Catch overbilling, duplicates and mistakes before payment. See how → https://dscvryai.com/use-cases/invoice-errors/ What does this new rule change for us? ### Regulatory changes Map new rules to what the business must change. See how → https://dscvryai.com/use-cases/regulatory-changes/ What actually happened with this complaint? ### Customer complaints Reconstruct what happened, and how it was handled. See how → https://dscvryai.com/use-cases/customer-complaints/ ## Where it runs. The AI goes to where the work is, from hosted to air-gapped. ### A managed environment. Start with a hosted service when speed of adoption and managed operations are priorities. Agree data handling, access and service requirements as part of the engagement. Discuss hosted · ## The other capabilities. Each one is tested on your own work before you rely on it. ### Sense It sees, hears and reads the work as it happens. Explore Sense → https://dscvryai.com/technology/sense/ ### Check Every line compared. Only the gaps reach you. Explore Check → https://dscvryai.com/technology/check/ ### Investigate Follow the evidence across systems. Find out what happened, and why. Explore Investigate → https://dscvryai.com/technology/investigate/ ### Anticipate Know what comes next, and plan for it. Explore Anticipate → https://dscvryai.com/technology/anticipate/ ### Operate The next step, taken. The reason, recorded. Explore Operate → https://dscvryai.com/technology/operate/ ## Bring us the work where wrong is expensive. Start with the operational problem. We’ll work out the data, models and agents it needs, and where it should run. 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