Imagine: the incoming invoice processing department spends hours manually entering data from PDFs. Errors, delays, repeated approvals — a familiar pain.
Power Automate with AI Builder solves this in seconds: a low-code platform built into Microsoft 365, with no need to hire a data scientist. Instead of 7 minutes per invoice — 45 seconds. Instead of 8% errors — 0.5%.
And this is not fantasy, but a real result of implementation on our projects. AI Builder lets you use ready-made models for form recognition, sentiment analysis, and forecasting that train on your data without programming.
The entire process is configured visually: add a trigger, select a model, specify actions — and the flow works.
What business tasks do we solve
AI Builder is an ML module within Power Platform. It covers three critical scenarios:
- Data extraction from forms and documents. The pre-built model recognizes invoices, business cards, receipts, and delivery notes. Accuracy ~90–95% on standard templates. If your form is non-standard, it is enough to upload 5–10 examples for retraining.
- Forecasting and classification. AutoML on tabular data: predicting churn, overdue payments, and demand. The model is built in a couple of clicks without a single line of code.
- Text analysis (Sentiment, Key Phrases, Language Detection). Useful for processing requests, comments, and reviews.
Compared with manual entry, AI Builder reduces document processing time by 10–15 times, and errors drop from 5% to <1% (data from our projects).
How AI Builder works in practice: an invoice processing case study
Let's look at a real scenario: a distribution company receives 200–300 invoices per day. Previously, operators manually transferred the data into 1C. Errors reached 8% — discrepancies in amounts and counterparties.
We implemented a flow in Power Automate: when an email with a PDF attachment arrives, a trigger fires, AI Builder Form Processing extracts fields (number, date, amount, supplier Tax ID), then the flow validates the data via the 1C API and writes it to a SharePoint list. If there is a discrepancy, it sends a task to Teams for manual review.
Result: processing time for one invoice decreased from 7 minutes to 45 seconds. Errors are almost eliminated. A team of 5 operators has been freed up for analytics.
Comparison: manual entry vs AI Builder
| Parameter | Manual entry | AI Builder + Power Automate |
|---|---|---|
| Time per invoice | 7 minutes | 45 seconds |
| Error rate | 5–8% | <1% |
| Need for operators | 5 people | 1 person (oversight) |
| Cost of processing 1,000 invoices | high | low (license + operations) |
How does AI Builder integrate with Power Automate?
The integration is built through built-in Power Platform connectors. You create a flow, select a trigger (for example, receiving an email or creating a list item), then an AI Builder action — call the model, pass input data, and get the result.
All models are deployed in the cloud and do not require infrastructure setup. Connectors to SharePoint, Dynamics 365, SQL Server, and external systems via HTTP, REST, and SAP are supported.
What is included in the implementation stage (deliverables)
| Stage | What we do | Duration |
|---|---|---|
| Analytics | Identify processes with the greatest impact, assess data volume and complexity | 1–2 days |
| Design | Define the flow, configure the AI Builder model, select triggers | 2–3 days |
| Implementation | Set up connectors, write expressions (if needed), integrate with external systems | 3–5 days |
| Testing | Test on real data, adjust accuracy, configure exceptions | 1–2 days |
| Deployment and training | Deploy to production, train operators, hand over documentation | 1–2 days |
Bottom line: from 1 to 3 weeks turnkey. The cost includes licensing (you must have Power Automate per user with attended RPA or Power Apps per user), setup, team training, and one month of support.
Why AI Builder and not Azure Cognitive Services directly?
AI Builder is positioned as a low-code add-on. If you do not have ML engineers, this is the optimal choice. If you need a custom model on PyTorch or specific predictive scenarios, it is better to use Azure ML or SageMaker — they offer more flexibility. But for 80% of typical tasks, AI Builder is sufficient.
How to integrate Power Automate with 1C or ERP?
Via the HTTP connector or an intermediate database. For example, we use the 1C REST API and XML transformations. Power Automate supports web service calls and JSON/XML parsing. AI Builder documentation describes all available connectors.
What are the data requirements for training?
For Form Processing, a minimum of 5 completed forms. For Prediction — 50+ records with labeled outcomes. Data must be in CSV or Excel, without gaps.
Advantages of working with our team
We have implemented Power Automate in more than 30 projects — from small business to enterprise with tens of thousands of documents per day. We have Microsoft Power Platform certifications and experience with AI Builder since its launch.
We guarantee that the automation will pay for itself in the first 2–3 months. Contact us to assess your processes — in just 1–2 days we will prepare a solution. Request a consultation on automation with AI Builder and get the first results within a week.
