Voyance Vision: Transforming Document Management with AI

The Challenge: Automating Document Management at Scale

Businesses generate and process thousands of documents daily, from invoices and contracts to compliance forms. Managing these documents manually is time-consuming, prone to human error, and costly. Traditional document management systems (DMS) often struggle with low-quality images, poor scanning, and inefficient search capabilities.

The fintech sector in Nigeria, in particular, faces stringent Know Your Customer (KYC) regulations, requiring businesses to verify customer identities rapidly and accurately. The existing manual processes were slow, expensive, and error-prone, highlighting the urgent need for an intelligent, automated solution.

‍

‍

The Solution: Voyance Vision

Voyance Vision is a next-generation Document Management System that leverages computer vision, machine learning, and artificial intelligence to extract, store, manage, and retrieve documents seamlessly. Designed for businesses dealing with high document volumes, Vision automates data extraction, reducing processing time and human intervention.

‍

Key Features

• Trainable AI Models: Businesses can train custom models or use pre-trained models developed by Voyance’s data engineers.
• Seamless Upload & Export: Documents can be uploaded from local or cloud storage, with extracted data downloadable in multiple formats.
• Advanced Annotation Tools: Users can label and annotate documents to improve data accuracy.
• Workflow Integration: Automation reduces human effort by instructing the system to extract data during predefined events.

‍

My Role: Leading the Design Vision

As the lead designer, I defined the overall design direction, developed prototypes, and crafted research documents to guide the project. I created a design strategy document that outlined our vision and principles, ensuring alignment across teams.

Beyond design, I worked closely with:

• Project Managers to align the design with business objectives.
• Data Scientists & Engineers to accommodate technical requirements.
• Frontend & Backend Developers to ensure accurate implementation.
• The CEO, a software and machine learning engineer, to gain deeper technical insights and refine the user experience.

‍

Research & Insights: Understanding User Needs

To create a solution tailored to real-world business challenges, we conducted research with fintech businesses. Our findings highlighted critical pain points:

• Speed & Accuracy: Manual document processing was slow and error-prone.
• Automation & Cost Reduction: Businesses wanted to minimize manual intervention.
• Security & Compliance: KYC and other regulatory processes needed to be streamlined.

‍

These insights guided our two-phase development approach:

1. Improve speed and accuracy by refining AI-driven data extraction.
2. Reduce cost and enhance automation through workflow integration.

We adopted rapid prototyping to test concepts and iterate quickly based on feedback, ensuring a user-friendly, high-quality solution.

‍

‍

‍

Testing & Iteration: Refining the Experience

During prototype testing, we collaborated with external data scientists, engineers, and machine learning experts. Their feedback led to two major enhancements:

• PDF Upload Support: Initially, we assumed all documents would be in image format. User testing revealed a significant need for PDF compatibility.
• API Integration: Businesses wanted to integrate our AI models into their systems, prompting us to develop API support.

By iterating based on real user feedback, we ensured Voyance Vision met industry needs effectively.

‍

The Launch: Delivering Impact

The launch was a resounding success. The implementation of Voyance Vision resulted in:

• 80% reduction in manual intervention
• 70% decrease in human resource dependency
• 90% faster document processing

Businesses benefited from instant approvals and seamless activations, significantly improving customer experience and operational efficiency.

‍

‍

‍

Future Applications

While Vision started as a document management solution, its AI capabilities open doors to broader applications:

• Fraud Detection: Identifying fraudulent documents and suspicious patterns.
• Vehicle Damage Assessment: AI-powered analysis of vehicle damage for insurance claims.
• Claims Management: Automating claim processing while minimizing false positives.

‍

Challenges & Learnings

Building an AI-driven DMS was not without challenges:

• Defining the Core Solution: With AI’s vast capabilities, we had to focus on what businesses needed most.
• Bridging Knowledge Gaps: As a designer without a background in OCR, machine learning, or AI, I had to rapidly upskill to create intuitive interfaces.
• Cross-Team Alignment: Regular documentation and sync sessions helped keep product, design, and engineering teams on the same page.

‍

Reflections

Voyance Vision was a challenging but rewarding project. By blending AI, user-centric design, and automation, we delivered a system that transformed how businesses handle documents. The experience reinforced the importance of user research, iterative design, and technical collaboration in building impactful products.