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Bodo.ai, a high-performance parallel compute platform for data workloads, has secured $14 million in Series A investment headed by Dell Technologies Capital, with Uncorrelated Ventures, Fusion Fund, and Candou Ventures also participating.
Bodo was founded in 2019 with the purpose of making Python a first-class, high-performance, and production-ready platform for sophisticated data analytics and machine learning applications. With the simplicity and flexibility of native Python, the company’s unique compiler technology would enable clients to address difficult, large-scale data and machine learning issues at exceptional performance and low cost.
Bodo provides previously unachievable supercomputing-like performance with linear parallel scalability, having been validated at 10,000+ cores and petabytes of data. Bodo users may reach a new level of performance and economic efficiency for large-scale ETL, Data Prep, Feature Engineering, and AI/ML Model training by removing the need to utilize additional libraries or APIs or rewrite Python into Scala, C++, Java, or GPU code to achieve scalability.
“Big data is getting bigger, and in today’s data-driven economy, enterprise customers need speed and scale for their data analytics needs,” said Behzad Nasre, co-founder and CEO of Bodo.ai. “Existing workarounds for large scale data processing like extra libraries and frameworks fail to address the underlying scale and performance issues. Bodo not only addresses this, but does so with an approach that requires no rewriting of the original application code.”
AI and Machine Learning Engineers
Python is a widely used programming language owing to its appeal among AI and machine learning engineers and data scientists. Many developers and data engineers who use Python for AI and ML algorithms, on the other hand, are frustrated by the language’s poor performance when dealing with huge amounts of data, stated Bodo. Even those that utilize extensions and frameworks would discover that their performance falls well short of Bodo’s. By utilizing Bodo instead of a major cloud data platform, developers may achieve a significant real-time performance increase for mission-critical program metric analysis workloads while saving on cloud infrastructure expenses.
“Customers know that parallel computing is the only way to keep up with computational demands for artificial intelligence and machine learning and extend Moore’s Law. But such high-performance computing has only been accessible to select experts at large tech companies and government laboratories,” added Ehsan Totoni, co-founder and CTO of Bodo.ai. “Our inferential compiler technology automates the parallelization formerly done by performance experts, democratizing compute power for all developers and enterprises. This will have a profound impact on large-scale AI, ML and analytics communities.”
Bodo may be installed on any infrastructure, from a laptop to the cloud. The company is headquartered in San Francisco and has offices in Pittsburgh, Pennsylvania.
“We see enterprises using more ML and data analytics to drive business insight and growth. There is a nearly constant need for more and better insights at near-real-time,” said Daniel Docter, Managing Director, Dell Technologies Capital. “But the exploding growth in data and analytics comes with huge hidden costs – massive infrastructure spend, code rewriting, complexity, and time. We see Bodo attacking these problems head-on, with an elegant approach that works for native Python for scale-out parallel processing. It will change the face of analytics.”