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Akridata has raised $15.0M across 1 funding round.
Key people at Akridata.
Akridata has raised $15.0M in total across 1 funding round.
Based in Los Altos, California, Akridata is a software company that develops a data-centric artificial intelligence platform designed to help data scientists explore, search, and curate massive visual datasets for computer vision model training. The enterprise software-as-a-service platform spans edge, core, and cloud resources to manage smart data pipelines, featuring a Data Explorer tool that reduces visual data analysis time by a factor of fifteen. The company primarily serves organizations building machine learning models across the autonomous vehicle, retail, smart city, healthcare, and manufacturing sectors. Operating with approximately 60 employees and generating an estimated $9.8 million in revenue, the venture-backed firm has raised $16.1 million in total funding, including a $15 million Series A round led by Accel, Telesoft Partners, MFV Partners, and Clear Ventures. Akridata was founded in 2018 by Vijay Karamcheti, Kumar Ganapathy, and Sanjay Pichaiah.
Key people at Akridata.
Akridata has raised $15.0M across 1 funding round. Most recently, it raised $15.0M Series A in October 2021.
| Date | Round | Lead Investors | Other Investors | Status |
|---|---|---|---|---|
| Oct 1, 2021 | $15M Series A | Accel, Arjun Gupta | AIX Ventures, Array Ventures, Mobile Foundation Ventures, Obvious Ventures, Streamlined Ventures, Summit Partners, The Valley Fund, BIZ Stone | Announced |
Akridata has raised $15.0M in total across 1 funding round.
Akridata's investors include Accel, Arjun Gupta, AIX Ventures, Array Ventures, Mobile Foundation Ventures, Obvious Ventures, Streamlined Ventures, Summit Partners, The Valley Fund, Biz Stone.
Akridata is a technology company specializing in AI-powered visual inspection and data-centric AI platforms for edge computing, enabling automated defect detection, data curation, and model optimization across manufacturing, medical devices, critical infrastructure, and more.[1][3][4] It builds a no-code, turnkey platform that processes multimodal visual data from edge devices—such as images and videos—delivering real-time insights, seamless integration into workflows, and up to 80% cost savings in training deep learning computer vision models by accelerating data ingestion, outlier detection, and model evaluation.[1][2][5] Serving Fortune 100 clients like Toyota and data science teams in automotive, healthcare, retail, and transportation, Akridata solves the exascale data challenge of organizing massive edge-generated datasets (tens of terabytes daily), reducing manual inspection reliance, minimizing defects, and speeding AI from experimentation to production.[3][5]
Akridata was founded in 2018 in Los Altos, California, by Silicon Valley entrepreneurs, data scientists, and product engineers—including co-founder and CEO Kumar Ganapathy—who collectively hold nearly 200 patents and have tackled major data challenges in AI and autonomy.[3][5][6] The idea emerged to address AI's "exascale-class data problem," where streams of rich data from scattered edge devices overwhelm organizations, hindering AI deployment in real-world sectors like automotive, transportation, retail, and healthcare.[3][5] Early traction included processing 20 petabytes of visual data for Fortune 100 customers, raising $15M in Series A funding from investors like Accel, Streamlined Ventures, and MFV, and launching the world's first edge data platform for data-centric AI in 2021.[3][5]
Akridata rides the data-centric AI trend, shifting focus from models to high-quality edge data amid explosive growth in autonomous systems, IoT, and Industry 4.0, where daily terabyte-scale visual data from devices demands scalable processing.[3][5] Timing aligns with AI production bottlenecks—post-2018 edge computing surge—enabling sectors like manufacturing and healthcare to achieve defect-free compliance and predictive maintenance amid labor shortages and quality demands.[1][4] Market forces like rising AI adoption (e.g., Toyota's involvement) favor it, as it bridges edge-to-cloud gaps, influences ecosystems by accelerating computer vision pipelines, and sets benchmarks for no-code tools in exascale data handling.[2][3]
Akridata is poised to expand its edge AI platform amid surging demand for autonomous manufacturing and critical infrastructure monitoring, potentially deepening integrations with cloud giants and Fortune 500s. Trends like multimodal AI and generative models for vision will amplify its data curation edge, evolving its influence from enabler to standard-setter in data-centric workflows—tying back to its core mission of turning edge data avalanches into production-ready AI fuel.[1][3][5]
