How to Automate Document Workflows

I have been learning about an emerging type of AI agent I’ll call "Smart Document Agents" (SDAs) It’s exciting to think through how SDAs can boost efficiency by 5–10x by: - converting unstructured documents (pdfs, faxes, images) into structured data - embedding these “smart documents” into relevant high value workflows - communicating across multiple parties to get things done automatically or with humans in the loop My friend, Andrei Radulescu-Banu (founder of https://docrouter.ai/) and I recently discussed several compelling use cases - I know some of these are being worked on. 1. B2B Procurement: For example hospitals order countless supplies for patient-specific procedures as well as ongoing clinical care. Meanwhile underlying all this they have thousands of unstructured pdfs / paper contracts that need to be adhered to. Normally, someone manually extracts the details of what is to be ordered when from the EHR / ERP, checks contract terms, creates the corresponding order and inputs it into a supplier’s workflow. An SDA can automatically parse the EHR (patient info, procedure date, item details) or the ERP to understand what is to be ordered when, choose the right supplier, verify pricing and contract terms, and create and submit orders. This should reduce 80% of the manual work and errors on either side while speeding up the process. 2. Tax Prep Automation: While W-2s and 1099s are structured, other tax documents vary widely (charitable donation letters, client prepared schedules, property tax payments, K-1s income classified generically in box 11ZZ). SDAs could learn these formats over time, reduce the manual burden of tax prep, and significantly lower costs. 3. Pre and Post Anesthesia Screening: Medical history, medication lists, allergies, vital signs, post-operative notes - these often reside in unstructured or semi-structured formats (scanned intake forms, typed or handwritten notes, PDF lab reports). SDAs can extract these to flag risk factors, populate checklists, and ensure compliance. Post-surgery, they can collect outcomes, trends, and potential complications for swift follow-up. This reduces errors, enhances patient safety, and expedites billing and auditing. 4. VC/PE/ Consulting Firms: Analysts reviewing large volumes of 10-Ks and 10-Qs could use an SDA to extract key financial metrics, risk factors, and strategically relevant points — accelerating analysis and comparison across companies and time periods. 5. Clinical Trials: A lab invoice might detail services, dates, and amounts to be billed to a trial. An SDA can verify charges against contract terms, flag discrepancies, and submit a verified invoice requiring much lower touch. 6. Shipping Logistics: Shipping container manifests list items, routes, weights, and special instructions. An SDA could automatically verify these details against physical inventory, saving time and reducing errors. What other SDA applications do you find exciting?

LlamaIndex just unveiled a new approach involving AI agents for reliable document processing, from processing invoices to insurance claims and contract reviews. LlamaIndex’s new architecture, Agentic Document Workflows (ADW), goes beyond basic retrieval and extraction to orchestrate end-to-end document processing and decision-making. Imagine a contract review workflow: you don't just parse terms, you identify potential risks, cross-reference regulations, and recommend compliance actions. This level of coordination requires an agentic framework that maintains context, applies business rules, and interacts with multiple system components. Here’s how ADW works at a high level: (1) Document parsing and structuring – using robust tools like LlamaParse to extract relevant fields from contracts, invoices, or medical records. (2) Stateful agents – coordinating each step of the process, maintaining context across multiple documents, and applying logic to generate actionable outputs. (3) Retrieval and reference – tapping into knowledge bases via LlamaCloud to cross-check policies, regulations, or best practices in real-time. (4) Actionable recommendations – delivering insights that help professionals make informed decisions rather than just handing over raw text. ADW provides a path to building truly “intelligent” document systems that augment rather than replace human expertise. From legal contract reviews to patient case summaries, invoice processing, and insurance claims management—ADW supports human decision-making with context-rich workflows rather than one-off extractions. Ready to use notebooks https://lnkd.in/gQbHTTWC More open-source tools for AI agent developers in my recent blog post https://lnkd.in/gCySSuS3

How we shrank 30-40 hours of weekly manual work into just 2-3 hours 🤯 (Automation Tip Tuesday 👇) This home services company was struggling with their invoice reconciliation process. They received numerous vendor invoices via email (PDF format) and needed to manually match them against jobs in ServiceTitan. Their team was stretched thin, discrepancies and overpaying were daily occurrences, and one day, they had enough. We worked on a three-step automated solution: Step 1: Finding the PDFs Zapier monitors the inbox for invoices. When it detects an invoice with a PDF attachment, it proceeds to Step 2. Step 2: Parsing the Data Nanonets uses AI to extract data from the PDF. Step 3: Data Comparison The extracted data is compared with jobs in ServiceTitan. Any discrepancies are added to a spreadsheet for internal review. 30-40 hours of weekly manual verification time is now just 2-3 hours. With instant discrepancy flagging, their system allows for better vendor management, improved billing accuracy, and more time for the team to pursue higher-value tasks. Which manual task that can be automated is currently taking up too much valuable time? If you’re thinking of one, it’s time we spoke. Book a free call (link in the comments 👇) and let’s see what we can do for your workflow. -- Hi, I’m Nathan Weill, a business process automation expert. ⚡️ These tips I share every Tuesday are drawn from real-world projects we've worked on with our clients at Flow Digital. We help businesses unlock the power of automation with customized solutions so they can run better, faster and smarter — and we can help you too! #automationtiptuesday  #automation #workflow

𝗪𝗵𝗲𝗻 𝗦𝗵𝗼𝘂𝗹𝗱 𝗬𝗼𝘂 𝗖𝗮𝗹𝗹 𝗶𝗻 𝗮𝗻 𝗔𝗜 𝗔𝗴𝗲𝗻𝘁? Not every process needs a full-blown AI agent. Sometimes a simple macro or integration does the trick. But there are clear signs that your workflow is begging for an autonomous assistant. Here’s how to spot them—and why agents succeed where traditional automation stalls: 🔍 𝟭. 𝗖𝗿𝗼𝘀𝘀-𝗦𝘆𝘀𝘁𝗲𝗺 𝗢𝗿𝗰𝗵𝗲𝘀𝘁𝗿𝗮𝘁𝗶𝗼𝗻 𝗣𝗿𝗼𝗯𝗹��𝗺: You’re juggling data from ERP, CRM, email, and a custom database—and every handoff is a manual export-import. 𝗔𝗴𝗲𝗻𝘁 𝗪𝗶𝗻: An AI agent can ingest records from your ERP API, enrich contacts in your CRM, send templated emails, and log responses. 𝘢𝘭𝘭 in one continuous flow. No more copy-paste handovers. 📚 𝟮. 𝗨𝗻𝘀𝘁𝗿𝘂𝗰𝘁𝘂𝗿𝗲𝗱-𝗗𝗮𝘁𝗮 𝗢𝘃𝗲𝗿𝗹𝗼𝗮𝗱 𝗣𝗿𝗼𝗯𝗹𝗲𝗺: Your team spends hours reading PDFs, extracting key specs, and summarizing them in slides or Jira tickets. 𝗔𝗴𝗲𝗻𝘁 𝗪𝗶𝗻: An agent reads documents, highlights critical passages, generates bullet-point summaries, and files them where you need. slashing review time from hours to minutes. 🔄 𝟯. 𝗕𝗿𝗶𝘁𝘁𝗹𝗲 𝗥𝘂𝗹𝗲 𝗘𝗻𝗴𝗶𝗻𝗲𝘀 𝗣𝗿𝗼𝗯𝗹𝗲𝗺: Your decision tree works until a rare edge case pops up, then everything crashes and you scramble for ad-hoc fixes. 𝗔𝗴𝗲𝗻𝘁 𝗪𝗶𝗻: Agents pair a flexible language model with hard constraints (“never quote over X without approval”) so they adapt to new inputs without breaking your guardrails. 📈 𝟰. 𝗦𝗶𝗴𝗻𝗮𝗹-𝗗𝗿𝗶𝘃𝗲𝗻 𝗧𝗿𝗶𝗴𝗴𝗲𝗿𝘀 𝗣𝗿𝗼𝗯𝗹𝗲𝗺: You know that building-permit filings or job postings signal capital-investment opportunities. if only you could catch them in real time. 𝗔𝗴𝗲𝗻𝘁 𝗪𝗶𝗻: An agent monitors permit APIs, scrapes relevant job boards, scores leads by fit, and pings reps the moment a trigger appears. 🎯 𝗣𝘂𝘁𝘁𝗶𝗻𝗴 𝗜𝘁 𝗜𝗻𝘁𝗼 𝗣𝗿𝗮𝗰𝘁𝗶𝗰𝗲 1. 𝗠𝗮𝗽 𝗬𝗼𝘂𝗿 𝗦𝘁𝗲𝗽𝘀: Document each tool and data source in your current workflow. 2. 𝗜𝗱𝗲𝗻𝘁𝗶𝗳𝘆 𝗣𝗮𝗶𝗻 𝗣𝗼𝗶𝗻𝘁𝘀: Where do handovers break down? Which tasks feel painful or error-prone? 3. 𝗣𝗶𝗹𝗼𝘁 𝗮 𝗠𝗶𝗻𝗶-𝗔𝗴𝗲𝗻𝘁: Start with a single “signal-to-action” flow, say, permit-to-email and measure time saved. 4. 𝗜𝘁𝗲𝗿𝗮𝘁𝗲 & 𝗘𝘅𝗽𝗮𝗻𝗱: Add complexity. Multi-tool flows, conditional logic, and human-in-the-loop checks as you gain confidence. Agents aren’t black boxes. They shine where processes span multiple systems, rely on unstructured inputs, or need continuous vigilance. If your team still wrestles with exports, manual reviews, or brittle scripts, an AI agent could help. 𝗖𝘂𝗿𝗶𝗼𝘂𝘀 𝘄𝗵𝗲𝘁𝗵𝗲𝗿 𝗮𝗻 𝗮𝗴𝗲𝗻𝘁 𝗳𝗶𝘁𝘀 𝘆𝗼𝘂𝗿 𝘁𝗼𝘂𝗴𝗵𝗲𝘀𝘁 𝘄𝗼𝗿𝗸𝗳𝗹𝗼𝘄?