Haystac Platform / Nashville

Multi-modal document parsing without traditional OCR constraints.

Nashville extracts structured information from complex documents by understanding both the meaning and visual structure of content — including forms, tables, handwriting, and irregular layouts.

Request Demo Back to Platform

Multi-modal parsing Interpret text, layout, and document structure together.

Handles complex formats Process tables, checkboxes, labels, handwriting, and irregular forms.

Structured output Turn messy documents into JSON-ready, workflow-ready data.

Where Nashville Fits

Step 2: Understand content Go beyond separation and extract meaningful fields from business documents.

Powered by OmniSense™ Leverages layout analysis to detect fields, tables, checkboxes, and structure automatically.

Feeds Orion and Polaris Once parsed, structured content can be used for insight generation and automated action.

What Nashville does

Nashville is Haystac’s document parsing layer, designed to extract structured information from real-world business documents with minimal setup and far more resilience than legacy OCR-driven approaches.

Extract structured data

Capture names, dates, values, codes, policy numbers, line items, and other key business information from complex documents.

Understand layout and meaning

Interpret document structure, not just text, so parsing remains effective even when format varies.

Reduce manual data entry

Move from human-heavy extraction workflows to AI-driven parsing that scales with volume.

Visual + language understanding Process text and structure as one unified document experience.

Handprint capable Support handwritten and stylized content that challenges OCR-heavy systems.

No-code curation model Rapidly train and refine parsing workflows through guided experiences.

Enterprise output Return structured data that fits broader host applications and workflows.

How Nashville works

Nashville treats the document as a visual object rather than a flat text source, enabling richer and more accurate parsing across structured and semi-structured content.

Step 1 Analyze the document

Nashville evaluates the page visually and semantically to understand structure and content relationships.

Step 2 Map layout

OmniSense™ detects fields, tables, labels, checkboxes, and other structural elements.

Step 3 Extract key information

The model generates structured outputs based on learned document patterns and business context.

Step 4 Return usable data

JSON-ready output is returned to the host application or downstream Haystac services.

Key capabilities

Nashville is built for document understanding, not just text recognition.

Extract data from forms, semi-structured documents, and irregular layouts.
Interpret tables, checkboxes, handwriting, labels, and visual relationships.
Support multi-modal parsing workflows without rigid OCR dependency.
Enable rapid curation and refinement through guided model-building experiences.

Best-fit use cases

Nashville fits document-heavy processes where structured data must be extracted reliably.

Healthcare records, claims, and insurance forms.
Financial statements, loan documents, and supporting application materials.
Government forms and public-sector intake documents.
Contracts, onboarding documents, and industry-specific semi-structured content.

Explore the platform

Nashville is the parsing layer inside the broader Haystac platform.

Chicago Document classification and separation Nashville Multi-modal document parsing Orion Generative insight and decision support Polaris Action layer and workflow automation

Extract what matters.

Nashville helps organizations turn complex documents into structured, usable business data.

Talk to Haystac