Transforming Contract Management With AI-Powered Extraction and Intuitive UX

1. About the Company

SpotDraft is a New York-based, award-winning contract automation platform with a team of over 200, purpose-built to help sales teams close deals faster, automate manual legal workflows, and maintain complete control over the contract lifecycle. Trusted by high-growth companies and enterprise legal teams alike, SpotDraft’s platform handles everything from contract creation and negotiation to metadata extraction and compliance. As the platform scaled to serve increasingly complex contract environments, the need for intelligent automation and a frictionless user experience became critical to maintaining its competitive edge.

2. The Challenge

As SpotDraft expanded its user base and tackled more complex contract workflows, several product and experience challenges surfaced:

• A Cluttered, Click-Heavy Commenting System: Users struggled to navigate the existing commenting interface, which required frequent clicks to view associated comments, lacked clear visual organization, and made it difficult to track conversations by user or context. The complexity of the system slowed down contract review cycles and created unnecessary friction for legal and sales teams collaborating on documents.
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• Manual, Error-Prone Metadata Extraction: Legal teams were manually extracting critical metadata — client information, payment terms, key dates — from contracts, a process that was time-consuming and prone to errors. This manual overhead consumed significant bandwidth that could have been directed toward higher-value legal work, and inaccuracies in extracted data created downstream risks.
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• No Support for Custom Metadata Fields: Users needed the flexibility to define and extract metadata fields unique to their specific contract types, but the platform did not support custom configurations. This one-size-fits-all approach limited the system’s usefulness for teams with specialized contract structures and prevented adoption by users with more complex metadata requirements.
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• Unreliable Extraction From Scanned PDFs: Verifying and correcting AI-extracted metadata from scanned PDFs was particularly challenging. Inconsistencies in OCR output and the lack of a clear verification workflow reduced user confidence in the system’s accuracy, leading to hesitation in adopting automated extraction for a significant portion of the contract pipeline.

These challenges demanded a combination of UX refinement and AI-driven automation to transform SpotDraft’s contract workflows from manual and fragmented to intelligent, accurate, and scalable.

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3. Solution Implemented by Tequity

Tequity partnered with SpotDraft as its dedicated product design and AI experience team, working across interface design, machine learning-powered extraction, and intelligent document processing to elevate the platform’s core contract workflows.

• Redesigned the Commenting Interface for Speed and Clarity: Tequity gathered user feedback on the existing commenting system to pinpoint the specific pain points driving frustration. The interface was simplified and reorganized into a compact, intuitive layout that allowed users to view and interact with comments without excessive clicks. Filters were introduced for easier tracking and access to tagged comments, while the layout was redesigned to resemble a familiar Word-like format. Visual clutter was eliminated, jargon was replaced with clear language, and icons were repositioned subtly to create a streamlined, distraction-free collaboration experience.
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• Automated Metadata Extraction With Machine Learning: Tequity identified the most frequently used metadata fields — client details, payment terms, key dates — and mapped them to machine learning models for automated extraction. A verification tool was designed to allow users to quickly confirm or adjust extracted data, ensuring accuracy without slowing down the workflow. Critically, each user correction was fed back into the system as training data, progressively improving the model’s extraction accuracy over time. This human-in-the-loop approach delivered the efficiency of AI automation while maintaining the precision legal teams demand.
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• Enabled Configurable Custom Metadata Fields: Tequity analysed the requirement for custom metadata fields specific to diverse contract types and designed a flexible configuration interface. Users could now define additional data types unique to their contracts, with date fields supplemented by automated guidance for easy selection and text-based fields supporting manual entry. These custom fields were integrated as configurable options within the extraction workflow, creating a tailored experience that adapted to each team’s unique contract structures without compromising the platform’s consistency.
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• Implemented AI-Powered OCR for Scanned PDF Processing: Tequity evaluated OCR technologies and developed a processing pipeline that converted scanned PDFs into selectable, tagged text. Users could verify metadata directly within the document, with key sections highlighted to guide the review process. Where automated extraction fell short, manual adjustment tools were provided for seamless correction. A feedback loop was built to store verified corrections and continuously improve the OCR model’s reliability, creating an AI system that grew more accurate with every contract processed.

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4. Results

The partnership between SpotDraft and Tequity delivered measurable outcomes across collaboration, automation, and user confidence:

• The redesigned commenting interface reduced the average clicks required to interact with a comment from 6 to just 1, transforming contract collaboration from a friction-heavy process into a seamless, near-instant interaction.
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• AI-powered metadata extraction with human-in-the-loop verification reduced metadata extraction time by 70%, freeing legal teams from manual data entry while continuously improving accuracy through the self-learning feedback loop.
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• The configurable custom metadata fields saw rapid adoption, with 72% of contracts now utilizing custom fields, demonstrating that users valued and actively used the flexibility to tailor extraction to their specific contract requirements.
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• The AI-powered OCR pipeline for scanned PDFs drove a 54% increase in user engagement, indicating that users now trusted the system to handle scanned documents accurately and were actively adopting automated extraction for a wider range of their contract pipeline.
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• With intelligent, self-improving AI extraction and a streamlined collaboration experience now at its core, SpotDraft is positioned to deepen its automation capabilities, expand its contract intelligence features, and cement its leadership in the enterprise contract management space.

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