Query.AI: Unleashing Decentralized Data Access and Analysis

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Andrew Maloney, COO
In today’s corporate world, data is the most valuable resource, as all businesses rely on data to power their operations. However, there is one primary challenge faced by these businesses and that is getting access to the data which is often distributed in silos across different platforms, locations, and cloud providers. For years now, the belief has been that to effectively analyze data and gain centralized insights; the data must first be centralized. Businesses have deployed various technologies to accomplish this, like SIEMs and data lakes, however these attempts to centralize have proven very costly and the amount of time and effort required to stand up infrastructure, collect, and normalize the data does not keep pace with the rapid changes of modern business meaning some critical piece of data remains outside the central repository.

Query.AI challenges the status quo and simplifies data access and analysis with a unique decentralized approach. With its Assistive-AI platform, Query.AI is on a mission to empower organizations to unlock the power of data by removing the barriers that come with data centralization. To achieve this feat, Query.AI leverages a new and innovative API-driven architecture that allows businesses to connect to disparate data platforms simultaneously, directly from their browser to perform data analysis.

The key benefit of Query.AI’s technology is that organizations no longer have to duplicate data and make large license and infrastructure investments to gain these centralized insights. This provides an opportunity for massive savings over tools that have exponential cost increases based on the volume of data ingested. To foster more intuitive interactions for users, the platform also offers Natural Language Processing (NLP) capabilities to serve as a universal translator allowing organizations’ to query data in plain English, regardless of the platform’s syntax. The results are then returned in an aggregated form through a virtual normalization layer appearing as if it had come from one platform for simple analysis.

“Our goal is to reduce the cost and complexity associated with access to data. We want to empower businesses with a new approach providing them flexibility when deciding where data should reside. The key is to access data where it lives, often in a native repository or system of record, and stop duplicating data in attempts to centralize it. We’ve been trying that for 20 years; it’s impractical. Users should just be able to ask questions and get answers on-demand, whenever they need to, from wherever their data lives,” explains Andrew Maloney, COO of Query.AI.

Notably, while the technology has been developed to be agnostic to the data accessed, allowing its application in multiple disciplines, the company has a strategic focus in augmenting security operations. It allows security professionals to initiate free-form investigations and leverage compelling visualizations and insights, even apply orchestration and automation capabilities to support incident response and threat hunting.


Our goal is to reduce the cost and complexity associated with access to data. The key is to access data where it lives rather than duplicating in an attempt to centralize.” explains Andrew Maloney, COO of Query.AI

Query.AI provides a real-time interactive command and control interface across your security infrastructure. This can be leveraged via a platform’s native syntax or through NLP.

To illustrate Query.AI’s capabilities further, Maloney narrates an instance where the company helped a Fortune 500 customer solve security issues related to siloed data. Common to other enterprises, the customer uses several tools to store and access security-related data and telemetry such as SaaS-based Endpoint technology, multiple on-premise SIEMs, and more. Equipped with such tools, whenever they were tasked to investigate a potential incident or indicator, they had to switch between multiple applications, writing queries for each specific platform, and manually aggregating and correlating the data before actually beginning their analysis.

This process was not only inefficient but also challenging, requiring a detailed level of understanding for each platform to access and extract the data. With Query.AI’s decentralized approach to data access and analysis, the customer is now able to simply ask questions and get answers from one interface in a very intuitive way. They are able to quickly access the various repositories to get the relevant data and context in the complex hybrid environment of on-premise and cloud / SaaS technologies to support the investigation. Therefore, by partnering with Query.AI, the customer has reduced the time and effort required for security investigation while gaining flexibility as to where the data lives, and simplifying access to it.

Established in late 2018, Query.AI obtained its first customer shortly after MVP release owing to its technology’s unparalleled capabilities. During this distressing time of the COVID-19 pandemic while many look at contraction, Query.AI is focused on expanding operations and customer adoption. All-in-all, as decentralized data access gains traction, new technologies like Query.AI that are providing simplified data access and reducing costs associated with legacy data centralization will play a significant role in the road ahead.

Company
Query.AI

Headquarters
Brookings, SD

Management
Andrew Maloney, COO and Dhiraj Sharan, CEO

Description
Query.AI challenges the status quo and simplifies data access and analysis with a unique decentralized approach. With its Assistive-AI platform, Query.AI is on a mission to empower organizations to unlock the power of data by removing the barriers that come with data centralization. To achieve this feat, Query.AI leverages a new and innovative API-driven architecture that allows businesses to connect to disparate data platforms simultaneously, directly from their browser to perform data analysis. The key benefit of Query.AI’s technology is that organizations no longer have to duplicate data and make large license and infrastructure investments to gain these centralized insights

Query.AI