Insider Brief

• ApertureData, a company providing a purpose-built database for multimodal AI, raised $8.25M in an oversubscribed seed round led by TQ Ventures to address the “data crisis” in enterprise AI, where most data remains siloed.
• ApertureDB, the company’s database, unifies management and access to complex multimodal datasets (text, images, videos), offering faster and more efficient data processing, which accelerates AI projects and improves ROI.
• With the new funding, ApertureData plans to expand its production deployments, improve user experience, and enhance sales efforts as it supports the growing demand for scalable multimodal AI solutions across industries like biotech, retail, and generative AI startups.

PRESS RELEASE — In the race to adopt multimodal AI systems capable of processing, understanding, and generating text, videos, and images, enterprises are running into a “data crisis”. They have plenty of data assets to work with, but most of them remain closed off, or locked, in siloed systems. According to Google Cloud’s 2024 Data and AI Trends report, 66% of organizations say at least half of their enterprise data is unused. Bridging this gap is California-based ApertureData, which has now closed its oversubscribed seed round at $8.25M for a purpose-built database for multimodal AI.

The funding round was led by TQ Ventures with participation from Westwave Capital, Interwoven Ventures, and a group of high-caliber angel investors. Existing investors also reaffirmed their commitment to ApertureData’s vision.

Currently, enterprises must use multiple disparate solutions to mobilize large multimodal datasets (images, videos, text files) for advanced AI. This involves ingesting data from different sources and storing it in cloud buckets — with continuously evolving metadata in files or databases — and writing bespoke scripts to search, fetch, and maybe do some preprocessing on the information. Vector search and classification further complicate the setup, leaving teams struggling with significant integration and management tasks. As a result, organizations suffer from inefficiencies, the value of AI solutions comes into question, and projects run for months without the expected RoI, leading to missed business opportunities.

ApertureData is bridging a crucial gap in today’s data infrastructure by offering a purpose-built database that provides teams with a unified solution for managing and accessing complex multimodal datasets — perfectly tailored to meet the demands of AI workflows. Users can now unlock the full power of ApertureDB in the cloud with a risk-free 30-day trial. In just a few clicks, they can access advanced graph-vector database capabilities, effortlessly scale their AI applications while eliminating the complexities of data infrastructure management.

ApertureDB provides enterprises with a single interface that centralizes all relevant datasets — including large images, videos, documents, embeddings, and associated metadata — for efficient retrieval and query handling. It stores the data, giving a uniform view of the schema to the users, and then provides knowledge and vector search capabilities for use across the AI pipeline.

By streamlining these disparate processes through one database, ApertureData reduces the time data scientists spend on data infrastructure issues and accelerates their projects’ timelines from months to a few days. Specifically, ApertureDB is 35x faster than existing disparate solutions at mobilizing multimodal datasets and 2–4x faster than other open-source vector databases.

The company was founded by Vishakha Gupta (CEO) and Luis Remis (CTO), who collectively bring over a decade of experience from Intel Labs. Their firsthand experience with the complexities of visual data management led to the creation of ApertureDB.

Vishakha Gupta, CEO of ApertureData commented: “The increasing adoption of multimodal data in powering advanced AI experiences, including multimodal chatbots and computer vision systems, has created a significant market opportunity. As more companies look to leverage multimodality, the demand for efficient management solutions like ApertureDB is expected to grow.”

The company has already secured initial deployments with select Fortune 100 customers, including a major retailer in home furnishings, a large manufacturer, some Biotech, retail, and emerging Generative AI startups.

Andrew Marks, General Partner at TQ Ventures added: “ApertureData has steadily built an amazing business with a wide view on the tech stack. They knew early on that traditional databases, which are geared toward textual data, would be insufficient for managing more complex multimodal data. The quantum of multimodal data and the desire to leverage it for analysis and machine learning is likely to explode over the coming decade as we are already seeing with the growth in use cases for generative and multimodal AI. And so, the work ApertureData is doing today will be foundational towards building the best infrastructure for emerging multimodal AI applications across various industries.”

With this new funding, ApertureData plans to scale its production deployments, enhance user experience through improved documentation and sandbox environments, focus on ecosystem integrations, and significantly expand its sales and marketing efforts. As large-scale multimodal data continues to play an increasingly vital role in AI and machine learning, the company is poised to lead the charge in providing a robust, scalable database for the next generation of AI innovations.

For a free trial of ApertureDB please visit: https://cloud.aperturedata.io/

Ends

Media images can be found here.

About ApertureData
ApertureData’s signature product ApertureDB simplifies the complexities of handling multimodal data like images, videos, embeddings, and related metadata. By using a graph database to combine keyword and label search with vector search and multimodal data management, it offers a single data layer for all your multimodal AI needs.

Petabytes of multimodal data (images, videos, documents) are getting captured or generated across various industries such as smart retail, e-commerce, smart agriculture, visual inspection, and medical imaging. Companies are increasingly using machine learning (ML) to derive insights from this enormous collection of data. These efforts are, however, often hindered by the lack of a data management solution that recognizes the challenges and opportunities presented by this large scale of multimodal data.

ApertureDB is not just an enterprise-ready vector database for multimodal data, but goes beyond that to provide a unified data layer to seamlessly support your entire machine learning pipeline. For more information please visit: https://www.aperturedata.io/home

About TQ Ventures
Based in New York City, TQ Ventures is a venture capital firm led by Schuster Tanger and Andrew Marks. The firm is generally agnostic to industry vertical and geography, and instead is business model-driven and prioritizes partnering with extraordinary founders building primarily software businesses. Across our more than 80 global investments, we believe the differentiated support and networks we provide our founders has fuelled our reputation and in turn performance record. Founded in 2018, TQ has approximately $1 billion under management and is currently investing out of its third fund.

About WestWave Capital
WestWave Capital invests in pre-seed and seed stage enterprise startups. The firm targets companies that build unique, differentiated technologies addressing large markets. WestWave’s core investment areas include software-as-service (SaaS), artificial intelligence, robotics, security, analytics, software infrastructure, and security. In addition to a decades-long investment track record, each of the firm’s partners has extensive startup operational experience.

WestWave Capital has been named to Business Insider’s list of Top 100 Seed Investors in 2023, and 2024.

About Interwoven Ventures
Interwoven Ventures is an early-stage venture capital firm focused on the fields of robotics, artificial intelligence and healthcare technology.

SOURCE