Automated Data Extraction for Tax Assessment

Uber processes millions of invoices globally – different formats, currencies, tax codes, and languages. Traditional rule-based OCR pipelines just don’t scale for that level of variability. Interesting to see how Uber solved this using a two-stage GenAI approach: 1. LLM-based field extraction: zero-shot parsing of key fields like vendor, total amount, tax ID. 2. Post-processing logic: country-specific rules (e.g. GST validation for India). The system improves itself through feedback. But this is where data labeling becomes critical. Without accurately labeled fields and validation, the model can hallucinate or misinterpret formats, especially for low-resource languages or unusual layouts. Labeling ensures: 1. Feedback loop quality 2. Accuracy tracking by field 3. Reliable onboarding of new invoice types It’s a solid example of blending GenAI with traditional ML workflows and domain logic for real-world scale. Worth a read 👇 https://lnkd.in/gFqMS9zW #GenAI #DataScience #UberAI #DocumentUnderstanding #LLM #AIInOperations #DataLabeling #InvoiceAutomation

✅ 𝗕𝗔 𝗖𝗮𝘀𝗲 𝗦𝘁𝘂𝗱𝘆 𝗣𝗮𝗿𝘁 𝟮: 𝗚𝗼𝗮𝗹𝘀, 𝗔𝗹𝗶𝗴𝗻𝗺𝗲𝗻𝘁 & 𝗦𝘂𝗰𝗰𝗲𝘀𝘀 𝗠𝗲𝗮𝘀𝘂𝗿𝗲𝘀 I am working on my case study for a fictional oil & gas products trading company struggling with indirect tax reporting in their ETRM system.   In my previous post, I shared the problem statement and current state analysis for my business case. Now, I’m diving into the next step: defining goals, strategic alignment, and success measures. When I started this section, I realized it’s not just about listing objectives. There’s a bigger story. How the project aligns with strategy and how success will be measured. 🎯 𝗚𝗼𝗮𝗹𝘀: 1. Automatically extract and consolidate 𝟵𝟬% 𝗼𝗳 𝘁𝗮𝘅-𝗿𝗲𝗹𝗲𝘃𝗮𝗻𝘁 𝗱𝗮𝘁𝗮 into centralized reports, reducing manual prep time from 2 days to under 2 hours per month within 3 months. 2. Enforce 𝟭𝟬𝟬% 𝘃𝗮𝗹𝗶𝗱𝗮𝘁𝗶𝗼𝗻 𝗿𝘂𝗹𝗲𝘀 for tax-relevant fields at time of trade or shipment entry, targeting a 50% reduction in rework due to data issues within 3 months. 3. Align 𝟭𝟬𝟬% 𝗼𝗳 𝗺𝗮𝘀𝘁𝗲𝗿 𝗱𝗮𝘁𝗮 used in tax logic across trade and logistics modules, with a quarterly governance review process in place within 3 months. 4. Implement a rules engine allowing tax analysts to update 𝟴𝟬% 𝗼𝗳 𝗹𝗼𝗴𝗶𝗰 𝘄𝗶𝘁𝗵𝗼𝘂𝘁 𝗜𝗧, cutting change turnaround time from 2 weeks to 2 days, within 2 months. 5. Ensure that 𝟭𝟬𝟬% 𝗼𝗳 𝘁𝗮𝘅 𝗿𝘂𝗹𝗲 𝗰𝗵𝗮𝗻𝗴𝗲𝘀 𝗮𝗻𝗱 𝗼𝘃𝗲𝗿𝗿𝗶𝗱𝗲 𝗮𝗰𝘁𝗶𝗼𝗻𝘀 are logged with user-level traceability and available for export on demand, within 2 months. 🚀 𝗦𝘁𝗿𝗮𝘁𝗲𝗴𝗶𝗰 𝗔𝗹𝗶𝗴𝗻𝗺𝗲𝗻𝘁: This project isn’t just operational. It supports key business goals. - 𝗘𝗳𝗳𝗶𝗰𝗶𝗲𝗻𝗰𝘆: Automate manual reporting - 𝗖𝗼𝗺𝗽𝗹𝗶𝗮𝗻𝗰𝗲: Standardize & track audits - 𝗔𝗴𝗶𝗹𝗶𝘁𝘆: Let users manage tax rules - 𝗗𝗮𝘁𝗮 𝗜𝗻𝘁𝗲𝗴𝗿𝗶𝘁𝘆: Align master data - 𝗥𝗲𝘀𝗽𝗼𝗻𝘀𝗶𝘃𝗲𝗻𝗲𝘀𝘀: Validate in real time 📊 𝗞𝗲𝘆 𝗞𝗣𝗜𝘀 / 𝗦𝘂𝗰𝗰𝗲𝘀𝘀 𝗠𝗲𝘁𝗿𝗶𝗰𝘀 (𝘀𝗮𝗺𝗽𝗹𝗲): - Prep time reduced from 16 to <2 hours/month - 90%+ reports auto-generated - 50% fewer errors in tax reports - 100% validation of tax-relevant fields - 100% audit traceability - 80% of rule changes completed without IT Defining clear goals, alignment, and metrics gives the project direction, purpose, and accountability. It’s not just about “what we want to do”. It’s about how we know we succeeded. 💡 Next up: I’ll share the proposed solution and future state, showing how these goals come to life. I’m curious. Do you include all 3 (goals, strategic alignment, success measures) in your business cases? #BAPortfolio #BusinessAnalysisCircle #BusinessAnalyst #BusinessAnalysis -- I’m the BA who asks “why,” digs deeper, and aligns business and tech teams to unlock value. ➡️ Follow me for more on problem-solving, reporting, and career journeys in business analysis. ♻️ Repost if you found this helpful.

The first question I get about AI in tax is always accuracy. And it should be. I sat down with ainews.com recently to talk about what we're building at K1x. One of the questions that came up was: How do you prevent hallucination? That's the right question. Because in tax, there's no room for error. A single misread line item can cascade into downstream liability issues. A hallucinated allocation percentage can blow up a client return. Most AI tax tools are built on foundation models trained on general data. They're fast. But they weren't built for the structure and specificity that tax requires. We took a different approach. K1x is built on an 8-year proprietary model. We started building it in 2017, long before the AI hype cycle. The model was trained exclusively on tax documents. That specificity matters. Our AI doesn't guess. It reads the document structure, recognizes the taxonomy, and maps data to the correct fields. It knows what a guaranteed payment is. It understands state withholding nuances. And when it's unsure, it flags the item for human review instead of fabricating an answer. That's the difference between a general AI tool and one built for tax professionals. We've processed K-1’s from over 40,000 organizations and extracted data from over a million K-1s. The downstream impact has been measurable. → 90% reduction in manual data handling → 66% cycle time reduction → 287% ROI in an independent analysis But the real metric is trust. Tax professionals don't adopt tools that create more work. They adopt tools that let them move faster without sacrificing accuracy. The firms winning right now are the ones that understand this. They're not chasing the latest AI feature. They're asking: Does this actually work? Can I trust it? Will it hold up under scrutiny? Those are the right questions. How are you evaluating AI accuracy in your firm? You can listen to the full interview here: https://lnkd.in/erq2rFfQ

A founder who’d been putting off sales tax, like so many others, finally decided to check her exposure. She wasn’t behind on revenue, or growth, or hiring. She was behind on compliance visibility and just three minutes into the process, the results loaded. Dozens of states, thresholds crossed, clear lines drawn where she owed tax. Her response was: “I just spent 3 minutes on the platform and I already understand my sales tax exposure. This tool is a godsend." We hear this story often from founders and finance leaders who have built systems for everything except the one thing no one talks about until it’s urgent: visibility into compliance. They’re exceptional operators. They know their margins, their forecasts, their hiring plans. But when it comes to sales tax, most admit they’re guessing. Every jurisdiction has its own version of nexus, a threshold that determines when you have to register and collect tax. In the U.S., those rules shift state by state, sometimes even county by county. Internationally, they take the form of VAT or GST, each with its own filing requirements. The rules were never designed for the way modern businesses grow. There’s no alert, no reminder, no notification when you cross a threshold. You just grow into new markets, ship to new customers, and suddenly you’re left wondering where the obligations begin and end. That question, Where does my business owe tax? Is exactly what the Kintsugi's Nexus Study helps answer. It’s a free exposure assessment that shows where you’re likely required to register, collect, or file. Go from confusion to clarity in minutes with four simple steps: 1. Connect your sales data. Secure integrations with Shopify, Amazon, Stripe, QuickBooks, Chargebee, and more. All data is handled under SOC 2 Type II and GDPR standards. 2. Automated analysis. The platform reviews every transaction, validates addresses, classifies products and services, and identifies where thresholds have been crossed. 3. A clear report. You receive an audit-ready view of the states, provinces, or countries where you likely owe tax. 4. Expert guidance. Kintsugi’s tax specialists walk through your results and help you plan next steps with no contracts, and no upsells. Most providers charge thousands for this kind of analysis. We made it free, because clarity shouldn’t depend on budget or timing. We’ve seen how much anxiety disappears once teams know where they stand. The unknown is always heavier than the work itself. Map your entire sales tax, VAT, and GST exposure in five minutes. No credit card required. Prevent costly penalties and audits by monitoring your multi-state and international exposure. Stop flying blind on nexus… Run your free Nexus Study today: https://lnkd.in/gJVvg4Pg

9 AI tax tools accounting firms won’t shut up about (at 1.5x) These apps are about to flood your feed in 2026: Core tax software isn’t changing (and still stinks), but the AI-powered workflow layer around it is getting scary good And gets better each time a new AI model drops. I maintain a living database of firm-tested app recs here: https://lnkd.in/gGqUu9VP A roundup of folks building exciting tech for tax pros: 1. / Magnetic / Pulls figures from gov't docs and pushes them into the tax software (extraction). This isn't new for the tax space, but newly much better thanks to AI vision models 🎉 2. / Juno / Extraction + AI review of 1040s(!) + a bit of research + an AI assistant that'll pull from the actual returns of your clients. Like a vastly better data mining utility. 3. / Filed / Beefed-up extraction with simple logic (e.g., every year they do X). Doing a bit of workpaper prep, but for now mainly an input accelerator. 4. / StanfordTax / Intake automation leader. Auto-builds a pro-forma checklist from prior-year data, auto-ticks items as docs arrive with an "AI workpaper". 5. / TaxGPT / Began as an AI research tool, recently introduced an AI 1040 reviewer. 6. / HubSync / Trying to be the home for everything. Has an AI intake & delivery module. Still early. 7. / Soraban / Another intake specialist. Newer “Connect” (extraction/input) and “Deliver” (client delivery) features are maturing. Intake remains the main draw for me. 8. / Blue J / Raised a whopping $122M for their AI research solution. For that amount of money look for them to push further into workflow & AI review. 9. / Truss / Handling intake + basic workpapers + delivery. A new entrant but I got enough unsolicited reviews to put them among my three leaders in the category. So, what's real here? What's working today? Automating intake remains the greatest source of time savings. It's why StanfordTax, Soraban and Truss are my overall category leaders. Any app relying on "integrations" with the tax software remain sketchy. It's a very hard problem to solve, and has been for decades. AI review solutions are still limited, but VERY excited to see how these develop. For the first time in decades tax tech is actually exciting 🫶 PS. My most up-to-date recommendations live in my app recs, linked above. PSS. The only way I've found to reach complete confidence in your tech stack is having a trusted group of peers who are real users. These conversations are happening daily in my private alliance of nearly 600 accounting firms https://lnkd.in/gx8m2wWE where no vendors are allowed, only real firm operators. PSSS. I run a consulting practice in my comments 🙂 If you're considering a new tech selection, drop me a note and I'll spill the tea.

Transform document images into structured data with LlamaParse (automated validation) 📊 Converting document images such as receipts to structured spreadsheet data requires tedious typing and careful validation. LlamaParse automates document data extraction by combining OCR parsing with schema validation, eliminating manual typing and human error. Here is an example pipeline for extracting receipt data: • Parse receipt images to markdown using LlamaParse OCR engine • Define receipt structure with Pydantic models (company, date, items, totals) • Extract structured data automatically with OpenAI integration • Validate types and enforce business rules (positive prices, valid dates) • Export to pandas DataFrames or spreadsheets for analysis #DataScience #Python #MachineLearning #AI

Just in time for taxes... an AI efficiency hack! I've always HATED this part of having my own business, so of course, AI to the rescue in 2025. I created "Kristin's Accounting" GPT where I upload my bank and credit card statements. (In the settings on my OpenAI account, I have it toggled to NOT train the model in order to keep my information private.) The GPT will sort everything into a chart that I can import into Excel, and then I can tag expenses for my companies. I plan to reconcile everything every month, and the final spreadsheet is what I will give to my accountant. Have you thought about doing this for your own finances? Here are the instructions in my GPT if you want to copy them (or edit and tailor to your needs): "This GPT helps users organize their financial data by extracting transaction details from bank and credit card statements in PDF format. It processes the statements to identify key information, including transaction date, description, amount, and relevant notes. The extracted data is structured into a table with five columns: Date, Item, Cost, Notes, and For (leave the for column blank). If necessary, it will clarify unclear transactions or request additional details from the user. It prioritizes accuracy and efficiency while maintaining user privacy. It does not store or retain financial data beyond the active conversation. If a document is unclear or contains inconsistencies, it will flag them for the user to review. The GPT can also provide insights into spending patterns, categorize expenses, and answer questions about financial trends based on the provided data. However, it does not provide financial, legal, or tax advice."

What is the common thread between a Wisconsin corporate income tax return and Pillar Two? After automating the U.S. shareholder income inclusion items as part of federal tax calculations (GILTI inclusion, Subpart F income, related deemed paid credit and Section 78 gross up, foreign tax credit limitations, various international forms, and so forth), we created a mechanism to automate the same data flow to state tax returns. For example, we mechanized the data flow for foreign income inclusion items by U.S. shareholders to a Wisconsin group tax return for U.S. shareholders belonging to that group. The same source data is used for Pillar Two calculations and reporting, such as for CFC tax and blended CFC tax allocations supporting effective tax rates by country. This expanded usage is possible only because Tax Series maintains “hidden data attributes” that are not part of forms reporting but are maintained for automating international tax calculations correctly. By maintaining various hidden data attributes, complex calculations such as tiered partnership structures and tiered partnership attributions to partners are also automated. Being able to maintain such hidden data elements enables automation across many aspects of corporate tax calculations and reporting. It ensures complex corporate income tax returns are accurate and dependable while also making the preparation of these returns easier. The Devil is in the details. Use Tax Series.

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?

𝗙𝗿𝗼𝗺 𝗖𝗼𝗱𝗶𝗻𝗴 𝗔𝗴𝗲𝗻𝘁𝘀 𝘁𝗼 𝗔𝗰𝗰𝗼𝘂𝗻𝘁𝗶𝗻𝗴 𝗔𝗴𝗲𝗻𝘁𝘀: 𝗧𝗵𝗲 𝗡𝗲𝘄 "𝗗𝗶𝗴𝗶𝘁𝗮𝗹 𝗝𝘂𝗻𝗶𝗼𝗿" While the tech world is buzzing about 𝗔𝗻𝘁𝗵𝗿𝗼𝗽𝗶𝗰 and their groundbreaking coding agents—which are already beginning to automate complex software engineering—I’ve been exploring how this same "agentic" logic is set to disrupt the Accounting Industry. We are witnessing a shift from simple software to Autonomous Agents. I don’t believe AI will replace the human accountant at this stage. Instead, it is hyperscaling our efficiency. The best way to look at it is this: We have effectively hired a "𝗗𝗶𝗴𝗶𝘁𝗮𝗹 𝗝𝘂𝗻𝗶𝗼𝗿." Just like a human trainee, you are "teaching" this agent your firm's specific way of preparing accounts. The only difference? The learning curve isn't months or weeks—it’s a matter of days if you use it daily. The Experiment: 3 Hours vs. 3 Minutes To test this, I built a specialized agent using a series of interconnected prompts and data flows. With a single command—"Prepare Accounts"—the agent goes to work. The Workflow: Behind that simple prompt, the agent autonomously processes:   Raw Bank Statements   Sales & Purchase Invoices   Expense Categorization The Result: In just three minutes, it generated a full P&L, completed a Tax Computation, flagged specific queries for client follow-up, and even drafted a Preliminary Tax Advisory Note. This is a workflow that typically takes a skilled team member 2–3 hours of focused manual labor. 𝗔𝗹𝗹 𝘀𝗰𝗿𝗲𝗲𝗻𝘀𝗵𝗼𝘁 𝗮𝘁𝘁𝗮𝗰𝗵𝗲𝗱 𝗵𝗲𝗿𝗲. Why This Matters for the Profession: 1. 𝙍𝙚𝙛𝙞𝙣𝙚𝙙 𝙊𝙪𝙩𝙥𝙪𝙩: The results aren't locked in a "black box." They are delivered in 𝗘𝘅𝗰𝗲𝗹, allowing for the traditional human review and adjustment we all rely on. 2. 𝙁𝙤𝙧𝙢𝙖𝙩 𝙁𝙡𝙚𝙭𝙞𝙗𝙞𝙡𝙞𝙩𝙮: There is massive scope here. These agents can be trained to produce "full-blown" working papers in the exact custom format your firm requires. 3. 𝙎𝙚𝙘𝙪𝙧𝙞𝙩𝙮 & 𝙏𝙧𝙪𝙨𝙩: Data privacy is a valid concern, but with the right paid enterprise subscriptions (much like the security protocols of Dext or Xero), your data remains as secure as any other professional fintech tool. The Road Ahead I am currently developing a fleet of these "Compliance Bots" to handle various facets of the workload at Terra Global Partners - Your Partner in Growth. If Anthropic can build agents that code, we can—and should—build agents that audit, reconcile, and advise. We aren't just saving time; we are reclaiming our capacity for high-level strategy while our "Digital Juniors" handle the compliance grind. 𝗧𝗵𝗲 𝗳𝘂𝘁𝘂𝗿𝗲 𝗼𝗳 𝗮𝗰𝗰𝗼𝘂𝗻𝘁𝗶𝗻𝗴 𝗶𝘀𝗻'𝘁 𝗷𝘂𝘀𝘁 𝗮𝘂𝘁𝗼𝗺𝗮𝘁𝗲𝗱; 𝗶𝘁’𝘀 𝗺𝗲𝗻𝘁𝗼𝗿𝗲𝗱. 🚀 I will be posting more prompts and recorded videos on my website and company linkedin Page. Follow our page to see more. #AI #Accounting #Anthropic #FinTech #TerraGlobalPartners #Automation #FutureOfWork 𝑆𝑜𝑚𝑒 𝑡𝑒𝑥𝑡 hidden due to confidentiality