Katana Graph, an analytics startup based in San Francisco, has developed an AI-driven platform that helps companies to quantify and visualise large amounts of unstructured data.
The startup has recently raised $28.5 million in a Series A funding round led by Andreessen Horowitz. This funding will further develop Katana Graph’s technology and expand its reach in the global market.
The goal of their technology is to help to transform how companies handle and analyse data.
Katana Graph raises $28.5 million to handle unstructured data at scale
Katana Graph is an AI-based software platform that enables businesses and organisations to analyse large volumes of unstructured data. Founded in 2017, the Cupertino, California-based company has developed a suite of core technologies, including a data integration layer, graph processing engine, distributed query engine and machine learning layer that allow users to manage and query vast amounts of unstructured data in real time. With the help of Katana Graph’s technology, companies can gain insights faster and more efficiently than ever before.
In 2019, Katana Graph raised $28.5 million in Series A funding from Redpoint Ventures and Norwest Venture Partners. This capital injection allowed Katana Graph to develop cutting-edge technology for dealing with massive amounts of unstructured data. The company has since made several important improvements to its core product lineup, including introducing its high-performance distributed query engine (‘KGQL’). As a result, customers can explore their data from anywhere on any device with near-zero latency — ensuring maximum business agility.
What problem does Katana Graph solve?
Katana Graph has developed groundbreaking technology to manage enormous amounts of unstructured data more efficiently. Unstructured data is data with no particular structure – such as text, audio, images, or video. There’s an increasing demand for analysing and managing this kind of data due to the proliferation of text documents, PDFs, customer records, social media and technological advances that rely on large datasets for AI and machine learning.
Although there are many ways to store and process big data sets, there are limited options for handling unstructured data at scale. Most traditional methods have limitations such as high latency in search queries and scalability issues when dealing with large volumes of data. Along with these challenges is the fact that it can take days or weeks, even months to ingest large volumes of unstructured data into traditional databases.
Katana Graph’s advanced platform changes this by providing a fast-query solution that can handle massive amounts of unstructured information in real-time without sacrificing scalability or performance.
Katani Graph’s patented graph database technology ingests all types of unstructured information while maintaining unified search engine performance regardless how quickly it scales. Additionally its underlying distributed systems architecture makes it possible to adapt the platform to various workloads whether a global online platform or an IoT connected device in less time than traditional databases require for scanning records from disk drive disks.
Katana Graph’s Technology
Katana Graph, a company committed to helping businesses use technology to better understand their data, recently announced that it has raised $28.5 million in funding.
Katana Graph’s technology is designed to tackle the challenge of unstructured data, a problem that has become increasingly prevalent as businesses generate ever-greater volumes of data over time.
Let’s take a closer look at how Katana Graph’s technology works to handle large amounts of data.
How does it handle large amounts of data?
Katana Graph’s technology is built to process and analyse large amounts of unstructured data, from emails and audio files to images and videos. To do this, Katana Graph leverages its graph computing technology to dramatically reduce the typical complexity of handling unstructured data.
At its core, Katana Graph uses an advanced graph-computing platform that links elements in data sets together in a manner that can be instantly identified. This allows for faster search times, more accurate interpretations of complex relationships compared to other systems, and real-time analytics.
In addition to providing an efficient platform for handling large amounts of data, Katana Graph’s technology also applies machine learning algorithms to quickly interpret the data into useful insights. This is done by applying specific algorithms designed to interpret structured and unstructured data types such as natural language processing (NLP) or computer vision (CV). Furthermore, by understanding patterns within the dataset, these algorithms can assist in making predictions with greater accuracy.
By combining these technologies into one system, Katana Graph can rapidly ingest massive volumes of unstructured datasets while producing meaningful insights that can be used immediately. The result is an efficient method for businesses to conduct text mining and predictive analytics on their massive datasets combined with access to a rich database for further analysis—all delivered at scale without any need for complex coding.
What sets it apart from other data-handling tools?
One unique aspect of Katana Graph’s technology is its ability to deliver innovative, real-time insights from unstructured data at scale. Traditional tools are limited by structure, meaning they aren’t able to query unstructured data and generate meaningful insights in real time. Katana Graph’s distributed architecture allows users to easily build their analytics applications without needing intermediate ETL (Extract – Transform – Load) operations or manual coding.
Katana Graph also stands out from other data-handling tools regarding scalability and cost efficiency. Its distributed nature makes it possible for enterprises to manage datasets up to a billion records without worrying about extra storage costs or long query response times. As such, it can help improve the performance of workloads requiring precise results from large datasets in an economical manner.
Moreover, Katana Graph offers an agile, user-friendly platform with intuitive graphical interfaces that enable development teams working with big data to quickly develop new applications and related queries and immediately observe the results. This makes it easier for non-technical users to create end-to-end analytics solutions with minimal programming expertise.
Finally, the proprietary distributed index structure used by Katana Graph helps simplify the management of unstructured datasets while minimising latency when querying across multiple nodes. This gives organisations unprecedented scalability and speed when analysing their ever increasing amounts of complex data.
Katana Graph’s Funding
Katana Graph, a Silicon Valley-based startup, recently raised $28.5 million in venture capital to help develop its technology to handle large amounts of unstructured data. Several high-profile investors provided the funding, which shows that the technology can revolutionise how companies process and store data.
Let’s take a closer look at the technology and the funding round.
How much money did they raise?
Katana Graph, a San Francisco-based startup, has recently raised $28.5 million to help handle large amounts of unstructured data at scale. The round was led by existing investor Wing Venture Capital and included new investors BCG Digital Ventures and JFrog Ltd. This brings the total amount of funding the company has raised since its inception in 2018 to $51 million.
The funding will accelerate product development and onboard additional sales and technical talent – especially data engineers. This influx of investment is also expected to provide a more robust platform for customer needs with client support, integrations, accurate execution without the complexity of traditional databases and an increased speed for complex query results.
Katana Graph is leveraging their proprietary distributed graph database technology to revolutionise how businesses store, search and manipulate big data effectively utilising artificial intelligence (AI) techniques such as deep learning/machine learning (ML) or natural language processing (NLP). Specifically, it allows customers to access accurately calculated relationships between entities stored in any type of format in data lakes— delivering decisive insights in milliseconds instead of hours or days. Ultimately, this funding boost will enable businesses worldwide to make instant decisions on huge datasets while saving significant time, costs and effort associated with traditional technologies.
What are they using the funding for?
Katana Graph has closed its Series B funding round of $28.5 million to accelerate the development of a platform that can handle unstructured data at scale. The funding will go toward product development, customer success and marketing initiatives, and global operations expansion.
The company’s product offering is based on graph technology – a sophisticated data representation system that uses nodes and edges to visually store information about its environment. Katana Graph’s platform harnesses the power of graph technology to make sense of large amounts of complex data from sources such as mobile devices, Internet of Things (IoT) sensors, wearables and databases.
By providing an easier way to explore structured and unstructured data sets at scale, the platform helps customers cut down the time they need to gain critical insights from their data stores. It can also be used in various industry sectors such as financial services, healthcare, retail and logistics for fraud detection, product recommendation engines and supply chain optimization applications.
Katana Graph’s platform also provides API integrations with leading analytics solutions such as Tableau, Looker and Metabase, making it easier for customers to leverage their existing enterprise analytics systems while enabling them to explore new possibilities on graphs. With this new funding round, the company plans to build a self-service version of their enterprise-grade graph platform, enabling users with little or no technical knowledge about graph processing engines or algorithms to explore their data in real time.
Benefits of Katana Graph
Katana Graph is a technology platform designed to handle large amounts of unstructured data at scale. As a result, it is a powerful tool for data scientists and engineers who rely on the performance and scalability of their data.
This article will discuss the advantages of using Katana Graph to store, manage, and analyse unstructured data.
What advantages does it offer?
Katana Graph’s technology is designed to provide advanced analytics capabilities for business customers by leveraging the power of graph processing and machine learning. With these capabilities, businesses can gain insights from their data more quickly and accurately. In addition, this technology provides businesses with various advantages designed to help them succeed in the ever-evolving digital world.
The first advantage offered by Katana Graph’s technology is its scalability. This allows it to handle large amounts of data, including both structured and unstructured information. This allows businesses to process more data faster and more accurately, enabling them to make better informed decisions. Furthermore, Katana Graph’s API-driven architecture makes deploying on various cloud services platforms easier while providing tighter integration with existing software applications.
In addition, Katana Graph can also be used for predictive analytics capabilities such as forecasting demand or customer retention rates. By leveraging graph database queries with machine learning algorithms, the platform can help businesses understand trends in customer behaviour over time and use this data to make better decisions related to marketing campaigns or product enhancements.
Finally, Katana Graph’s technology offers unparalleled visualisation capabilities by utilising graph database queries. The platform provides an easy-to-use interface that allows users to quickly filter through large datasets to visualise relationships between entities or events over time or project potential scenarios based on certain parameters or assumptions.. This helps make many data-related tasks much easier and faster for businesses than conventional solutions would allow.
What industries is it most useful for?
Katana Graph’s technology can benefit several industries, providing automated analysis of vast amounts of data to allow companies to make informed and strategic decisions. This can be particularly useful for businesses dealing with larger datasets or multiple sources of data, such as in particular manufacturing, finance and AI/ML operations.
Manufacturing: Katana Graph has the potential to give insight into complex production processes and facilitate automation. For example, by leveraging its ability to connect all related datasets, it could help manufacturers identify ways to streamline their workflow and reduce costs. Furthermore, its advanced analytics capabilities allow them to monitor supply chains so organisations can prioritise tasks and optimise purchasing strategies in real-time.
Finance: Katana Graph’s technology can help financial firms better manage their investments by providing an algorithm that automatically detects patterns from massive data sources. This gives banks the power to quickly analyse diverse portfolios across multiple markets and risk-control operations on global scales.
AI/ML: Katana Graph is also beneficial for AI/ML operations since its platform offers a way for these operations to automate labour-intensive tasks such as feature engineering and dataset preparation needed to train predictive models more efficiently. Additionally, its technology allows organisations working with unstructured datasets—such as web pages or documents—to extract useful insights from them by clustering large volumes of data and understanding intricate relationships between variables or items within datasets.
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