Platforms > AI Builder

Microsoft AI Builder Consulting

Alphabyte offers Microsoft AI Builder consulting. We help mid-market and enterprise organizations add AI to Power Apps and Power Automate, from reading invoices and forms to scoring records, so the AI runs inside the apps and workflows your team already uses.

We design the models and flows, test them on your real documents and data, and train your team to run them.

Success Stories

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What We Do

AI Builder consulting that puts document processing and predictions inside your everyday Power Platform workflows.

Microsoft AI Builder is the AI feature of the Microsoft Power Platform. It offers prebuilt models for common tasks, such as reading invoices and receipts, and custom models you train on your own data. Because it works inside Power Apps and Power Automate, AI Builder results can drive approvals, fill in records and route work without a separate system.

The hard part is rarely switching it on. It is choosing the right use case, training a model that is accurate on your documents and handling the cases it gets wrong. Our guide to AI-powered document processing explains how it works, and we often pair it with custom Power Apps for the screens your team uses. When the process itself needs fixing first, our business process improvement service covers that work.

AI Builder suits organizations already on Microsoft 365 and the Power Platform. For harder problems we build custom machine learning models, and for language tasks we work with models such as Claude.

01

AI Builder Implementation & Configuration

The right AI Builder models set up and connected to your data sources.

02

Intelligent Document Processing

Data pulled from invoices, forms, contracts and receipts without manual entry.

03

Predictive Analytics & Scoring Models

Prediction models that score records and flag risks from your business history.

04

Custom AI Model Development

Custom object detection, text classification and entity extraction models trained on your data.

05

Power Apps Integration

AI results shown inside the custom Power Apps your team works in daily.

06

Power Automate AI Workflow Automation

Flows that route documents, trigger approvals and flag exceptions using AI Builder.

07

AI Builder & Dataverse Integration

Model results stored in Dataverse for Power BI reporting and audit trails.

08

Ongoing Support & Optimization

Retraining, accuracy reviews and workflow updates as your use cases grow.

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Our Approach

  • We review your workflows, documents and data with the people who do the work, and find where AI Builder can remove manual steps. We check how consistent your documents are and whether there is enough history to train a model. Discovery usually takes 1 to 2 weeks and ends with a ranked list of use cases.

  • We choose between prebuilt and custom models for each use case and design the flows, apps and data storage around them. You see how documents and predictions will move through the process, what happens when the model is unsure and where people review results, all before any build work starts.

  • We test prebuilt models on samples of your real documents and train custom models on your own data, refining them until they meet accuracy thresholds agreed with your team. Where a model struggles, we look at the training data, the document layouts or the scope before deciding whether to retrain or change approach.

  • We connect the models to Power Apps and Power Automate, map each output to the right field and add error handling for low-confidence results. Development, test and production environments stay separate, so every change is tested before it reaches the people who rely on it.

  • We test model accuracy, flow logic and data outputs against real scenarios, with your users checking the results. Administrators and end users are trained on how to review AI outputs and handle exceptions. Go-live is coordinated with your team, with a rollback plan ready in case a flow needs to be switched off.

  • We document model settings, training data requirements, flow logic and maintenance steps, including how and when to retrain a model. Your team gets a walkthrough of each part so it can manage and extend the solution itself. If you prefer, we can stay on to review accuracy and add new use cases over time.

Your AI Builder Consulting Team

Alphabyte is a data and AI consultancy, founded in 2015, and a Microsoft Solutions Partner. Our Power Platform developers and AI practitioners work on one team, so AI Builder models, apps, flows and reporting are designed together rather than handed between groups. We have served 100+ organizations, and built production machine learning models, automation workflows and embedded analytics for clients in e-commerce, financial services, manufacturing and professional services.

Our team holds Microsoft certifications including Power Platform Developer Associate, Power Platform Functional Consultant Associate and Power Platform App Maker Associate. See the full list on our certifications page. After go-live we can stay on to retrain models, review accuracy and extend your flows as new use cases come up.

We work with mid-market and enterprise organizations. Related services: business process improvement, AI consulting and custom software development.

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Frequently Asked Questions

  • Microsoft AI Builder is the AI capability built into the Microsoft Power Platform. It lets you add models to Power Apps and Power Automate without writing machine learning code. It includes prebuilt models for tasks such as reading invoices and receipts, and custom models you train on your own data for document processing, prediction, classification and object detection. Results can be stored in Dataverse and used in reports.

  • AI Builder consulting covers choosing the right use cases, deciding between prebuilt and custom models, preparing training data, training and testing models, and building the Power Apps and Power Automate flows that use them. At Alphabyte it also includes storing results in Dataverse, reporting in Power BI, handling exceptions, documentation and training, so your team can run and retrain the models after launch.

  • Most organizations ask for help when a team spends hours typing data from invoices or forms into another system, when a pilot model is not accurate enough on real documents, or when AI Builder results need to feed approvals, Dataverse or Dynamics 365. It also makes sense to bring in a consultant when you are not sure AI Builder is the right tool for the problem.

  • Cost depends on the number of use cases, how varied your documents are, whether prebuilt models are enough or custom models are needed, and how many apps, flows and systems are involved. AI Builder capacity and Power Platform licences are billed separately by Microsoft. We scope each project during discovery, often starting with one use case so you can see results before adding more.

  • AI Builder document processing reads a document, such as an invoice or form, and pulls out the fields you need, such as dates, totals and vendor names. For common documents a prebuilt model may be enough. For your own layouts, you train a custom model on sample documents. A Power Automate flow then sends the extracted data to the right system and routes low-confidence results to a person for review.

  • In Power Automate, AI Builder models run as steps in a flow. A flow might start when an invoice arrives by email, extract its fields with AI Builder, check the totals, start an approval and save the result to Dataverse. Prediction and classification models can also route records or flag exceptions. We design these flows with error handling, so nothing is lost when a model is unsure.

  • AI Builder suits common business tasks inside the Power Platform, such as document extraction, classification and simple predictions. A custom model suits problems that need more control, larger data or logic AI Builder does not support. For language tasks we also work with models such as Claude.

  • A first use case usually goes live in about 6 to 10 weeks. Discovery takes 1 to 2 weeks, and model training, flow building and testing make up most of the rest. Timelines depend on how many document types are involved, how much training data you have and how many systems the flow touches.

  • It depends on your documents and data. Consistent, clear documents and a good set of training samples give better results than varied layouts or poor scans. We test each model on your real documents before go-live and agree a confidence threshold with your team. Results below that threshold go to a person for review, so the process stays reliable even when the model is unsure.

  • Yes. AI Builder works natively with Dataverse, so model results, predictions and extracted document data can be stored as structured records with a clear audit trail. From there the data can be used in Power BI reports and in Dynamics 365 apps that run on Dataverse. We design the tables and security so the right people see the right results.

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