Deep Vector is a technology company.
Deep Vector has raised $2.0M across 1 funding round.
Deep Vector has raised $2.0M in total across 1 funding round.
Deep Vector has raised $2.0M in total across 1 funding round.
Deep Vector's investors include Aperture Venture Capital.
Deep Vector is an AI-powered platform that automates the extraction, structuring, and analysis of unstructured data from documents like PDFs, images, and scans, primarily targeting insurance but expanding to healthcare, finance, and more.[1][2][4][5] It serves insurers, brokers, risk managers, and businesses with document-heavy workflows, solving the problem of manual processing inefficiencies by using proprietary algorithms and machine learning to handle over 5,600 document formats with high accuracy and speed.[1][3][4][5] The company, previously known as Loss Scan, recently closed a $1.5M seed round co-led by Aperture Venture Capital and InsurTech NY, signaling strong early growth momentum in a data-intensive market.[2][3][5]
Deep Vector was co-founded by Scott Knowles and Wesley Janse van Rensburg, who brought deep expertise from insurance, software development, and startups.[1][3][5] Knowles began as a commercial insurance broker and recently sold their prior venture, Modgic (an insurance analytics business), to Zywave, while CTO Janse van Rensburg specializes in scalable solutions for insurance challenges.[1][3][5] The idea emerged from addressing inefficiencies in handling unstructured data like claims loss runs and ACORD forms; it evolved from Loss Scan's success in insurance data extraction into a broader platform adaptable across industries.[2][3][4][5] Early traction included building a proprietary engine now expanding beyond insurance, culminating in the January 2025 seed funding close.[3][5]
Deep Vector rides the wave of AI-driven document automation amid exploding unstructured data volumes in regulated sectors like insurance, where analog docs hinder risk assessment and decision-making.[3][5] Timing is ideal as insurers face pressure to digitize underwriting—Deep Vector bridges brokers and underwriters by unlocking "buried insights" from PDFs and spreadsheets, improving risk modeling and customer experiences.[3][5] Market forces like insurtech growth, AI adoption in finance/healthcare, and investor interest (e.g., $1.5M seed) favor it, positioning Deep Vector to influence ecosystems by standardizing data extraction and enabling scalable operations across industries.[2][3][5]
Deep Vector is poised for rapid expansion beyond insurance, leveraging its seed funding to adapt its engine for finance, healthcare, and government while showcasing at events like InsurTech Spring Conference.[3][5] Trends like multimodal AI, regulatory demands for data accuracy, and enterprise automation will propel growth, potentially evolving it into a cross-industry standard for unstructured data processing.[1][4][5] As it scales, expect deeper integrations and partnerships, amplifying its role in transforming manual workflows into AI-enhanced intelligence—much like how it revolutionized loss runs, now unlocking broader data potential.[1][3]
Deep Vector has raised $2.0M across 1 funding round. Most recently, it raised $2.0M Seed in January 2025.
| Date | Round | Lead Investors | Other Investors |
|---|---|---|---|
| Jan 1, 2025 | $2.0M Seed | Aperture Venture Capital |