Tag Features

Everything you need for AI-assisted document workflows—from data collection through professional output

Smart Data Collection

Traditional data collection is tedious: open a document, find the relevant information, switch to your form, paste it in, repeat 50 times. Tag transforms this into a streamlined workflow.

Batch Autofill Wizard

Select dozens of source documents for autofill at once from anywhere on your computer. The wizard provides:

  • Multi-folder selection - Pick files from different locations

  • Favorite folders - Save frequently used source folders for quick access

  • Document-to-form mapping - Attach relevant source documents to each form that needs data, process them separately or together in AI requests

  • Per-form AI configuration - Choose AI vendor and model for each form independently

  • Routing flexibility - Send requests to a secure AWS Bedrock server (Managed AI subscription) or to the AI vendor’s server directly (BYOK subscription) per form

  • Parallel processing - Up to 30 source documents process simultaneously, more than that safely queue for their turn

  • Real-time progress - Progress bars show what's running; detailed JSON traces show what happened

How it works: You design forms with fields that match the data you need. Data fields use public standards (RNG, XML Schema) to define structure and validation rules. When you run batch autofill, AI scans your source documents, finds the specific information for each field, and populates the form.

Tag sends a big system prompt to explain how this works to the AI. You can enhance this by attaching a custom prompt, or typing a custom instruction at runtime (e.g., Ignore all events prior to 2023, only fill fields A, B and C).

When autofill is done, you review and correct data before it is transformed and/or flowed into final documents. Autofill can be run multiple times if you need more control over the sequence of source documents used.

Advanced Data Import

Unlike simple form builders that only accept manual typing, Tag pulls data from multiple sources:

  • Excel/CSV imports with field-level transformations (e.g., reformat dates, split names, apply calculations)

  • Advanced find helps you search for a single row in a spreadsheet to import from

  • Transformation rules can change values (e.g., from a survey or online Google Form) into exactly what your data fields expect

  • Database queries (SQL: MySQL, PostgreSQL, SQL Server, Oracle; NoSQL: MongoDB, CouchDB)

  • API calls to web services and cloud systems

  • Semantic data endpoints for knowledge graphs and linked data

Some data sources require a bit of help from us to setup. Ensuring user credentials are safely managed is of utmost importance.

Targeted AI Processing

The difference between AI that helps and AI that frustrates is control. Tag doesn't generate entire documents from vague prompts - it processes specific data with specific instructions.

AI-Chains for Precision

AI-Chains bundle everything needed for a focused task: the data to process, the context to provide, the prompt that instructs the AI, and model settings.

How it works:

  • Define data sources - Select which form fields, local files, or other data the chain sees

  • Connect prompts - Pull from your prompt library or write inline

  • Choose vendor and model - Use Claude for complex reasoning, Gemini for fast extraction, or compare multiple models and decide for yourself

  • Attach to form fields - By convention, fields named *_ai support AI-Chain attachment

  • Execute on demand - Run on one field, one form, or all forms together

What makes this powerful:

  • Granular control - AI processes exactly the data you specify, nothing more

  • Reusable patterns - Save successful chains for similar tasks elsewhere

  • Vendor flexibility - Switch between Anthropic, Google, OpenAI, or Cohere per task (some vendors are not available in our Managed AI subscription)

  • Complete transparency - Detailed JSON traces show every request and response (required for HIPAA/PIPEDA audit trails)

  • No hidden prompts - Tag system prompts are visible in the trace log; everything else is in your prompt library or explicitly provided by you

Writing Samples Inform Style

Instead of relying on AI's default voice, provide samples of your actual writing. AI analyzes the examples and matches:

  • Tone and formality level

  • Sentence structure and paragraph length

  • Technical vocabulary appropriate to your field

  • Organizational patterns you consistently use

This isn't just prompt engineering - it's teaching AI to write like you.

Writing samples are key to getting good results. Our experience with healthcare professionals has shown that different authors typically want completely different output content for the same set of input data. As a result, customizing writing samples is an important part of getting started.

Professional Document Generation

Tag excels at generating complex documents that maintain your standards and branding. The template designer gives complete control without requiring coding expertise.

Rich Template Designer

Create sophisticated layouts with full formatting control:

  • Tables with dynamic rows, merged cells, calculated totals

  • Sections with conditional inclusion based on data

  • Styles and formatting - fonts, colors, spacing, headers/footers precisely as you want them

  • Mixed content - combine fixed text (disclaimers, standard language) with dynamic fields and AI-generated sections

  • Repeating elements - generate tables or lists of items in your data

  • Nested structures - complex documents with multiple levels of organization

Powerful Expression Language

  • XPath-based expressions - leverage the full power of XPath functions for data manipulation and logic

  • Conditional content - show or hide sections, paragraphs, or table rows based on expression results

  • Dynamic repetition - loop through data collections to generate tables, lists, or document sections

  • Data insertion - pull values from your data source using value-of expressions

  • Transform on import - apply expressions during data import to calculate, format, or restructure information

  • Point-and-click editors - build common expressions visually without writing code

  • Raw expression editing - drop into code for advanced scenarios requiring fine-tuned control

Flexible Integration

Real-world workflows involve data from many places in many formats. Tag handles integration complexity so you don't have to.

Desktop Architecture Advantages

Tag runs on your computer (Windows or Mac), not in a browser:

Performance benefits:

  • Fast processing of large files without upload/download delays

  • Parallel operations leverage your CPU cores

  • Reduced impact of variable server availability or network congestion

  • Utilize larger amounts of local memory instead of a slice of remote server memory

Security advantages:

  • Files stored locally, not on remote servers

  • You control what data leaves your computer

  • Connect to databases on private networks (VPN, corporate intranet)

  • Access file shares behind firewalls

  • Work with systems that can't be exposed to the public internet

XML and JSON Capability

Tag has flexible support for structured data:

  • XML parsing and generation with schema validation

  • JSON handling for modern web APIs

  • Bidirectional conversion - read XML, write JSON; read JSON, write XML

  • XSLT transformations for complex document generation

  • XPath and JSONPath queries for precise data extraction

This makes Tag suitable for industries with strict data interchange requirements (healthcare HL7, financial FIXML, government standards).

What You Won't Find in Tag

  • Autonomous AI agents: Tag does not include AI agents that independently take actions. Every AI operation is explicitly triggered by a human clicking a button. This is deliberate - we believe in keeping humans in control.

  • Generic document generation: Unlike tools that generate entire documents from a single vague prompt, Tag requires you to design workflows. This takes more initial setup but produces predictable, highly customized results.

  • Cloud-based storage: Tag is a desktop application. If you need cloud storage for your files, use your existing solutions (Google Drive, OneDrive, Dropbox). Tag reads from and writes to wherever you store files locally.

  • Real-time collaboration editing: Multiple users can contribute to shared forms asynchronously, but Tag doesn't support Google Docs-style simultaneous editing of documents. Final document generation happens on one person's computer.

These are intentional design decisions aligned with our philosophy: human control, predictable workflows, security, and compliance.

Tag is available for Windows and macOS. All features described are included in both Individual-BYOK and Individual-Managed subscription plans. Blueprint modeling features are available through consulting engagements.