Acceldata, a leader in data observability solutions, has acquired Bewgle, an AI and natural language processing (NLP) startup. This strategic acquisition aims to deepen data observability for AI, adding AI capabilities to Acceldata’s platform. In an era when enterprises are increasingly relying on AI solutions, this acquisition positions Acceldata to offer enhanced visibility into AI data pipelines, facilitating improved data organization and reliability.
Acceldata’s Data Observability Platform
Acceldata, based in California, provides end-to-end visibility into distributed data systems used by large enterprises, including notable clients like Oracle, PubMatic, PhonePe, and Dun & Bradstreet. The platform leverages AI and machine learning (ML) to offer insights into data processing, pipeline performance, and data quality. This empowers teams to build and maintain reliable data products.
The platform provides Chief Data Officers (CDOs) with real-time insights into potential risks to their businesses through a holistic lens of data. This capability enables proactive decision-making to achieve the desired business outcomes. Acceldata’s technology monitors data quality throughout complex data pipelines and transformations across various environments, including cloud, hybrid, and on-premises setups. It identifies data problems and triggers alerts before data is used for model building, ensuring the quality and reliability of data used in AI and analytics.
Bewgle’s Contribution to Acceldata
Founded in 2018, Bewgle specializes in AI and NLP, offering solutions that generate insights by analyzing large volumes of unstructured text data, such as conversations and reviews. The company has served clients in sectors like retail, wellness, and consumer packaged goods (CPG) by providing instant competitor, content, product, and consumer insights.
With this acquisition, Bewgle’s team and technology will become part of Acceldata. The founders of Bewgle, Shantanu Shah and Ganga Kumar, who have extensive experience in building large-scale consumer and enterprise intelligence products, will lead Acceldata’s AI team. Their expertise will be instrumental in expanding data observability capabilities to help teams build stronger AI and large language model (LLM) products.
AI Observability and Smarter AI
Beyond enhancing data observability, Bewgle’s team and technology will also contribute to Acceldata’s product with AI capabilities. This will provide data practitioners with new tools and features for detecting anomalies, automating decisions, and identifying root causes.
Acceldata’s AI roadmap is expected to be accelerated with the integration of Bewgle’s expertise in running foundational models and large language models over the past several years. While specific details about the AI capabilities are yet to be revealed, the acquisition has fast-tracked Acceldata’s plans to incorporate AI into its platform.
Competition in the Data Observability Space
Acceldata faces competition from other well-funded players in the data observability space, such as Cribl, Monte Carlo, and BigEye. These companies are also addressing the challenges of ensuring data quality and reliability for AI and analytics. Notably, Monte Carlo has begun incorporating generative AI into its solutions, partnering with OpenAI to offer features that allow users to create SQL code using natural language and suggest code fixes.
The acquisition of Bewgle strengthens Acceldata’s position in this competitive landscape, enabling it to provide enhanced data observability and AI capabilities to its customers. As AI continues to play a pivotal role in enterprises’ data strategies, solutions that offer robust data observability and AI monitoring will become increasingly important.
Acceldata’s previous funding rounds have raised nearly $100 million from various investors, including Insight Partners, March Capital, Industry Ventures, Lightspeed, Sorenson Ventures, Sanabil, and Emergent Ventures. With its recent acquisition and AI-driven enhancements, Acceldata is poised to play a significant role in helping enterprises harness the power of AI with confidence in their data pipelines.
