When to Use Microsoft Syntex

Microsoft Syntex is a content AI service that lives inside Microsoft 365. It uses trained models to read, classify, and extract information from documents at scale. Used well, it removes hours of manual handling from content-heavy workflows. Used badly, it is an expensive way to do something a folder structure already solved.

What Syntex actually does

Syntex provides three core capabilities:

• Document understanding: trains a model on examples of a document type (contracts, invoices, RFPs) and then identifies and extracts key fields from new documents that match
• Form processing: extracts data from structured forms using Power Automate AI Builder
• Image tagging and OCR: applies tags and extracts text from images, including scanned content

The result is content that arrives in SharePoint with metadata already populated, classified, and ready to be searched, governed, or routed.

Where Syntex is the right answer

Syntex earns its place when:

• You receive a high volume of similar documents (contracts, purchase orders, claim forms)
• The documents share a recognisable structure or layout
• You currently extract information manually or with a brittle script
• The extracted data drives downstream workflow (routing for approval, recording in a register, triggering a notification)

Where Syntex is the wrong answer

Syntex is not the right tool when:

• You only handle a handful of documents per month, the licensing does not pay back
• Your documents are wildly inconsistent in layout and content
• What you actually need is search optimisation, not classification
• The metadata can be captured at upload time with a simple form

Licensing in plain terms

Syntex is billed per transaction in most cases, with prepaid bundles available. A "transaction" is one document processed by one model. The pricing rewards high-volume, consistent use cases and penalises occasional ad hoc use.

TC can help you model the expected transaction volume against the cost of the manual process you are replacing.

What a Syntex project usually looks like

A typical Syntex engagement runs in three phases:

1. Use case selection: identify two or three candidate document types and validate the business case
2. Model training: collect 5 to 20 example documents per type, train the model, and tune to acceptable accuracy
3. Integration: connect the model output to your library metadata, workflow, or downstream system

Where to start

Pick one document type that is high-volume and high-friction today. Run a Syntex proof of value on it before committing to a wider rollout. To scope a Syntex engagement, submit a support ticket.