Acceldata Enhances Data Observability with Innovative AI Copilot Feature

As the demand for generative AI assistants surges, vendors across the data ecosystem are integrating these technologies into their products. Early adopters like Snowflake and Informatica have paved the way, and now Acceldata, a notable leader in the data observability space, has introduced its own AI copilot.

Designed for immediate use, the AI copilot operates seamlessly across the Acceldata platform, enhancing various data observability workflows—from monitoring data pipelines for anomalies to establishing policy rules.

“Our innovative approach empowers enterprises to customize AI-assisted data observability to meet their unique operational and business needs, distinguishing us in the industry. This AI technology simplifies manual configurations, shortens setup times, enables automatic anomaly monitoring, and promotes collaboration among non-technical users,” said Rohit Choudhary, CEO and co-founder of Acceldata.

How Does the AI Copilot Enhance Data Observability?

According to media demos, the AI copilot is accessible via a dedicated button on the Acceldata platform, allowing users to automate and expedite previously manual tasks using simple natural language inputs.

Key benefits include anomaly detection and cost control. Users can leverage the AI to investigate and resolve issues related to data freshness, profiling, and quality, as well as analyze consumption patterns to mitigate excessive usage.

“We have optimized models to comprehend enterprise data taxonomy, detect data anomalies, provide policy recommendations, and forecast costs. Additionally, our copilot incorporates RAG technology with industry-standard LLMs, such as GPT, to address user inquiries relating to data observability,” Choudhary shared. This extensive capability encompasses all data used in applications, including generative AI models.

Beyond core observability functions, the copilot streamlines error-prone tasks such as bulk generation of data quality rules and policies. Users can issue natural language commands to create SQL rules and generate human-readable descriptions for data assets and policies. This feature is crucial for fostering seamless communication between technical and business stakeholders.

General Availability in Q2

Although the copilot has just been unveiled, Acceldata reports that some major clients are already testing it in preview mode. While specific customer names remain undisclosed, the company confirmed general availability is anticipated in the early weeks of Q2.

Acceldata has raised over $100 million from various investors and serves numerous clients, including leading banks, telecommunications companies, consumer goods firms, and data providers.

“This product has been validated in highly complex and scalable environments,” Choudhary remarked, noting future plans to enhance capabilities for monitoring large language model performance, although a timeline for this is still pending.

Acceldata’s AI initiatives gained momentum in September 2023 with the acquisition of NLP company Bewgle for an undisclosed amount. The company faces competition in the data observability realm, with well-funded rivals such as Cribl, Monte Carlo, and BigEye also offering solutions aimed at similar challenges.

Monte Carlo has recently taken steps in the generative AI space, launching two AI features in collaboration with OpenAI in June 2023—one for generating SQL code via natural language and another for suggesting code fixes. Both features are now available to users.