How to Streamline Invoice Processing

How we saved 10+ hours weekly by giving finance a simple interface. Our finance team was processing invoices the same way for years: 1. Email attachments → 2. Manual download → 3. Print → 4. Physical signature → 5. Scan → 6. Manual data entry The entire cycle took 3-5 days. The request to "build a proper approval system" kept getting deprioritized—it felt like a multi-month project. We reframed the problem: We didn't need a complex system. We just needed to connect two things: the data from our accounting software's API and a simple list where the right people could click "Approve" or "Reject." What actually got built: • A single-page app that pulls unpaid invoices automatically • Logic that routes invoices over $5k to directors, others to managers • A comment field for rejections • A basic audit log showing who approved what and when What changed: ✅ Approvals now happen in under 24 hours ✅ The finance team stopped chasing paper trails ✅ Vendors get paid faster ✅ Every decision is logged automatically The takeaway: Sometimes "digital transformation" isn't about big platforms. It's about giving a team one less PDF to manage by building a simple, focused tool that sits on top of the data they already use. What's the most stubborn, repetitive task in your team's workflow? Often the highest-impact tools are the smallest ones that remove a single point of friction. https://uibakery.io/ #ProcessAutomation #FinanceTech #OperationalEfficiency #DigitalTransformation

🚀 Built an Enterprise-Grade Agentic AI Invoice Processing System In most organizations, invoice processing is still manual, slow, and error-prone. I recently designed and developed a scalable, multi-agent AI solution to handle high-volume invoice processing with parallel intelligence and automated decisioning. 🔍 What makes this system powerful? Instead of a single pipeline, this solution uses a multi-agent architecture where specialized AI agents work in parallel: ✅ Invoice Agent – validation & duplicate detection ✅ PO Agent – purchase order matching ✅ GRN Agent – goods receipt validation ✅ Compliance Agent – GST & regulatory checks ✅ Contract Agent – pricing & terms validation ✅ Fraud Agent – anomaly detection using ML All agents execute simultaneously using a fan-out / fan-in orchestration pattern, significantly reducing processing time. 🧠 A Manager Agent (AI brain) then: Aggregates all agent outputs Identifies discrepancies (price, quantity, tax) Generates a detailed audit-ready report Makes a decision → YES / NO / HOLD 📧 If issues are detected, the system automatically notifies vendors using Microsoft Graph API. ⚙️ Tech Stack Highlights Microsoft Agent SDK (multi-agent orchestration) Azure AI Document Intelligence (data extraction) Azure OpenAI (reasoning & report generation) MongoDB (low-latency structured data storage) AKS (scalable agent execution) Azure Durable Functions (parallel orchestration) 🏗️ Architecture Highlights Parallel agent execution for high throughput Cloud-native, microservices-based design AI + rule-based hybrid validation Designed for thousands of invoices per second Built with extensibility (plug-and-play agents) 💡 Why this matters? This approach transforms invoice processing from a manual back-office task → intelligent, autonomous system with: ⚡ Faster processing 🎯 Higher accuracy 🔍 Better auditability 📉 Reduced operational cost This is a strong step toward Agentic AI systems in enterprise finance operations. Would love to hear your thoughts or discuss how this can be extended further (RAG, real-time fraud detection, etc.) 👇 #AI #GenAI #AgenticAI #Azure #MachineLearning #Automation #FinTech #MLOps #CloudComputing

Imagine this scenario You’ve created a billing document (an invoice), and you want it to automatically go out to the customer by email, maybe with a PDF attached. In S/4HANA, that’s all handled through BRF+ Output Management instead of the old NACE setup. Here’s what you’d actually do, step by step, and what’s happening behind the scenes. Step 1: Tell SAP you’re using the new system Go to SPRO → Sales and Distribution → Basic Functions → Output Control → Activate Output Management. This is just flipping a switch so SAP uses BRF+ logic instead of the older method. You’re basically saying, “Hey SAP, use the modern output engine for billing.” Step 2: Create your Output Type Next, go to: SPRO → Output Control → Define Output Types Here you define something like: Output Type: ZBILL_INV Description: “Customer Invoice Email” Form Template: your Adobe or SmartForm Channel: Email (or Print, or EDI) Think of this like naming what kind of message you want SAP to send, a label that says “Invoice” or “Credit Memo”. Step 3: Hook that Output Type to Billing Documents Still in configuration, link that output type to your billing application object (V3 for billing). Now SAP knows: whenever a billing document is saved, this output type might be triggered, depending on your rules. Step 4: Build the logic in BRF+ Now comes the brain of it all, BRF+. Open transaction BRFPLUS (or open the Fiori app “Manage Your Solution → Configure Output Management”). Inside BRF+, you’ll do three small things: 1. Create an Application – just a container (like a folder). 2. Create a Decision Table – this is where you tell SAP when to send your invoice. 3. Create a Function – the entry point BRF+ calls when a billing document is saved. You just link the decision table to this function. That’s it; BRF+ now knows how to make output decisions for you. Step 5: Fine-tune with “Output Parameter Determination” Now, head over to the Fiori app “Output Parameter Determination” (OPD) or t-code OPD. Here you can easily add: Which Channel to use (Email, Print, etc.) Who the Receiver is (customer contact, internal email, etc.) Which Form Template to use This app looks a lot like Excel and is very simple to maintain. Step 6: Test it out Create a billing document in VF01, then go to VF02 → Issue Output → Edit. If everything’s right, you’ll see your new output type appear automatically. Try emailing or printing it; you’ll see your BRF+ setup in action. Step 7: Check or troubleshoot If you send via email, check SOST to confirm the message actually went out. If it didn’t, BRF+ logs can help you see why (like a missing condition or wrong recipient).

"We just saved $24,000 a year by fixing one broken process."   That's what my construction client told me after we transformed their accounts payable system. As a fractional controller, these are the wins that get me excited.   Let me share what was happening behind the scenes. This growing construction company was drowning in paperwork - their team was spending 15-20 hours weekly manually entering invoices, chasing down approvals from project managers in the field, and reconciling payment records. Late payments were straining vendor relationships, and they had zero visibility into their cash flow.   Here's what we did: We implemented BILL as their AP automation solution. The transformation was remarkable. Within just two months: ✔️ Their AP processing time dropped to just 3 hours per week ✔️ Project managers could approve invoices right from their phones ✔️ Vendors started getting paid consistently on time ✔️ They saved $2,000 monthly in administrative costs ✔️ Most importantly, they gained real-time visibility into their cash flow   But the best part? 𝗧𝗵𝗲𝗶𝗿 𝗔𝗣 𝗰𝗹𝗲𝗿𝗸 𝘁𝗼𝗹𝗱 𝗺𝗲 𝘀𝗵𝗲 𝗳𝗶𝗻𝗮𝗹𝗹𝘆 𝗳𝗲𝗹𝘁 𝗶𝗻 𝗰𝗼𝗻𝘁𝗿𝗼𝗹 𝗼𝗳 𝗵𝗲𝗿 𝘄𝗼𝗿𝗸 𝗶𝗻𝘀𝘁𝗲𝗮𝗱 𝗼𝗳 𝗱𝗿𝗼𝘄𝗻𝗶𝗻𝗴 𝗶𝗻 𝗽𝗮𝗽𝗲𝗿𝘀 𝗮𝗻𝗱 𝗲𝗺𝗮𝗶𝗹𝘀. She's now focusing on more strategic tasks like vendor relationship management and process improvement.   I've seen this pattern repeatedly in my work with various businesses. 𝗠𝗮𝗻𝘂𝗮𝗹 𝗔𝗣 𝗽𝗿𝗼𝗰𝗲𝘀𝘀𝗲𝘀 𝗮𝗿𝗲𝗻'𝘁 𝗷𝘂𝘀𝘁 𝗶𝗻𝗲𝗳𝗳𝗶𝗰𝗶𝗲𝗻𝘁 - 𝘁𝗵𝗲𝘆'𝗿𝗲 𝗰𝗼𝘀𝘁𝗶𝗻𝗴 𝘆𝗼𝘂 𝗺𝗼𝗻𝗲𝘆 𝗮𝗻𝗱 𝗽𝗼𝘁𝗲𝗻𝘁𝗶𝗮𝗹𝗹𝘆 𝗱𝗮𝗺𝗮𝗴𝗶𝗻𝗴 𝘆𝗼𝘂𝗿 𝘃𝗲𝗻𝗱𝗼𝗿 𝗿𝗲𝗹𝗮𝘁𝗶𝗼𝗻𝘀𝗵𝗶𝗽𝘀.   _____________________________________________ I'm Melissa Armstrong, CPA* and founder of SteadyHand Accounting & Advisory. Want to get insider tips and tricks from a powerhouse accountant on how to streamline your accounting operations? 𝗝𝗼��𝗻 𝗺𝘆 𝗩𝗜𝗣 𝗺𝗮𝗶𝗹𝗶𝗻𝗴 𝗹𝗶𝘀𝘁 (𝗹𝗶𝗻𝗸 𝗶𝗻 𝗰𝗼𝗺𝗺𝗲𝗻𝘁𝘀).   *𝗡𝗼𝗽𝗲𝗅 𝗜 𝗱𝗼𝗻'𝘁 𝗱𝗼 𝘁𝗮𝘅𝗅

Too many business owners and finance teams spend time manually matching payments to invoices. This is a terrible use of time. They spend hours cross-referencing $2,500 deposits, trying to guess if that wire transfer came from Customer A or Customer B. It feels like productive work, but it’s actually just expensive data entry. When we built the invoicing product at Haven, the goal wasn't to give people a way to send PDFs. The world has enough of those. The goal was to eliminate the financial detective work that eats up a founder's focus. Our system handles the auto-matching of payments. When a customer pays, the invoice is marked as paid. Period. No manual clicks, no checking bank balances against invoice numbers, and no wondering why your ARR reporting feels off because you forgot to update a status on a Tuesday. Scaling a company is already hard enough. You shouldn't make it harder by doing work that a well-built piece of software can do for you. Learn more here: https://lnkd.in/eGjz_q83

Eric Foster, Director of Finance & Ops at Compa, wasted HOURS on submitting invoices to portals every week. Here’s how Invoice Butler fixed it👇 For context: Compa helps some of the world’s biggest companies figure out high-stakes pay decisions. Eric joined as Head of Finance during a period of rapid growth, but their AR setup only scaled to ~20 customers. > Manual invoices in QuickBooks > One master Google Sheet for deals > Another Google Sheet for collections > Manual follow-ups… if anyone remembered He tried to fix it by automating invoicing. Yet, collections and enterprise portals remained manual. The real issue: Compa’s enterprise customers paid invoices via different portals, not automated dunning. This meant: - Overdue AR stacking up - Dozens of Coupa and Ariba accounts across reps - Invoices stuck for weeks between creation and submission Eric was left with two options: do it himself or hire an analyst to do just this. Neither scaled..... That’s when he found Invoice Butler.. Within a week of collaborating: • $120K collected in an overdue invoice  • A small follow-up brought ~$130K in the bank • Overdue accounts dropped from 15-20 to barely 2-3 More importantly, Eric got his time back. Instead of chasing invoices, he could focus on working with founders on growth strategy. He could confidently deploy capital on sales hires, engineering investments, and vertical expansion. As Eric put it:  “Invoice Butler does the annoying part ....consistently, persistently, and better than I ever could. I haven't touched Coupa/Ariba in months.” PS: We’re on a mission to automate B2B cash collections forever. If enterprise invoice submissions to supplier portals are draining your time (and sanity), we might be able to help. Full case study link in the comments👇

Stop sending "Quick reminder on that invoice" emails forever. Here's how we tie in an automated system for some of our clients: - Connect Xero to Stripe natively or connect Quickbooks to Acodei - Set up recurring invoice templates - Enable auto-pay options for clients - Automate payment matching in your books Results from one agency client: - Reduced payment delays by 84% - Saved 12 hours per month on invoice admin - Improved cash flow prediction accuracy to 94% - Zero additional dollars spent hiring collection agenices Offering auto-pay doesn't just help you - it helps your clients too. I find that MOST clients happily chose auto-pay when given the option because: - No manual processing each month - Simpler expense tracking - Better budgeting on their end But here's what most miss: Don't just automate the invoices. Automate the ENTIRE system: - Payment reminders - Receipt generation - Bookkeeping entries - Revenue recognition - Tax documentation Your time is worth more than chasing payments.

Manual invoice processing costs finance teams hundreds of hours every year? Here's how to fix it. Most finance teams are losing hours every week on AP tasks a system could handle. I spent years as a CFO signing off on payment runs. Half the time, the real bottleneck was upstream - invoice capture, approvals, matching. Not strategy. Data entry. Here is what accounts payable automation actually covers: 𝗜𝗻𝘃𝗼𝗶𝗰𝗲 𝗖𝗮𝗽𝘁𝘂𝗿𝗲 ✅ Automatic invoice capture and data extraction ✅ Email, PDF, portal - all ingested automatically 𝗪𝗼𝗿𝗸𝗳𝗹𝗼𝘄 𝗔𝘂𝘁𝗼𝗺𝗮𝘁𝗶𝗼𝗻 ✅ Approval workflows without chasing people on email ✅ Rules-based routing with a full audit trail 𝗘𝗿𝗿𝗼𝗿 𝗣𝗿𝗲𝘃𝗲𝗻𝘁𝗶𝗼𝗻 ✅ 2-way and 3-way purchase order matching ✅ Duplicate payment detection before it costs you 𝗩𝗶𝘀𝗶𝗯𝗶𝗹𝗶𝘁𝘆 ✅ Real-time view of what is owed and when ❌ No more spreadsheets tracking open invoices manually ❌ No more month-end surprises from unrecorded liabilities 💡 The business case is straightforward. Fewer errors. Faster close. Better cash flow timing. And your team stops doing work that adds zero analytical value. Want to see how AP automation works inside a real finance function? Check out how BILL can transform your process. P.S. Where are you losing the most time and money when it comes to managing AP?

Is your accounting team working weekends to close the books? A recent client of mine had this problem while using their folder-based system. Employees wasted time sorting invoices, chasing approvals, and doing manual data entry. The team had to work weekends to close the books every month. We fixed up the process for them by: → Centralizing invoices to one email integrated with ProcureDesk. → Using OCR technology to match invoice data with existing PO. → Implementing a three-way matching system to approve invoices. → Approved invoices were automatically entered into the accounting system. Doing this gave the accounting team their weekends back. It also meant closing the books every month was no longer a headache. I love how simple automation processes within ProcureDesk.com can do wonders for accounting teams.

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