insideBIGDATA Latest News – 9/26/2022

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In this regular column, we’ll bring you all the latest industry news centered around our main topics of focus: big data, data science, machine learning, AI, and deep learning. Our industry is constantly accelerating with new products and services being announced everyday. Fortunately, we’re in close touch with vendors from this vast ecosystem, so we’re in a unique position to inform you about all that’s new and exciting. Our massive industry database is growing all the time so stay tuned for the latest news items describing technology that may make you and your organization more competitive.

Deci Introduces World’s Most Advanced Semantic Segmentation Models

Deci, the deep learning company harnessing AI to build AI, announced a new set of industry-leading semantic segmentation models, dubbed DeciSeg. Deci’s proprietary Automated Neural Architecture Construction (AutoNAC) technology automatically generated semantic segmentation models that significantly outperform the most powerful models publicly available, such as the MobileViT released by Apple, and the DeepLab family released by Google. Deci’s models deliver more than 2x lower latency, as well as 3-7% higher accuracy.

Semantic segmentation is one of the most widely used computer vision tasks across many business verticals, including automotive, smart cities, healthcare, and consumer applications, and is often required for many edge AI applications. However, significant barriers exist to running semantic segmentation models directly on edge devices, such as high latency and the inability to deploy those models due to their size.

With DeciSeg models, semantic segmentation tasks that previously could not be carried out at the edge because they were too resource intensive are now possible. This allows companies to develop new use cases and applications on edge devices, reduce inference costs (since AI practitioners will no longer need to run these tasks in expensive cloud environments), open new markets, and shorten development times.

“DeciSegs are an example of the power of Deci’s AutoNAC engine capabilities to generate custom hardware-aware deep learning models with unparalleled performance on any hardware. AI teams can easily use DeciSegs models or leverage Deci’s AutoNAC engine to build and deploy custom models that run real-time computer vision tasks on their edge devices.” said Yonatan Geifman, PhD, co-founder and CEO of Deci.

Tigris Data launches all-in-one developer data platform to simplify building real-time applications

Tigris Data, a groundbreaking open source developer data platform provider, announced the launch of its serverless and open source developer data platform Tigris. Tigris is aimed at web and mobile apps, providing a unified API that spans search, event streaming, and transactional document store, along with smart features like automatic indexing and management. By using serverless and a single API, this approach simplifies the data infrastructure for application developers and enables them to focus on building. 

The cost of maintaining multiple data services is not only expensive, but is disruptive to development time. Tigris is an all-in-one open source developer data platform with a single, unified API to ensure developers spend less time on tedious infrastructure management and more time on what they do best – coding and feature development. Tigris is based on FoundationDB, a distributed database that was open sourced by Apple in 2018 under the Apache 2.0 licence.

Developers want to build applications and scale up those services, and they don’t want to spend time managing databases or linking up infrastructure components. They want to use an API like approach to interact with data, in just the same way as they interact with other services. And they want to achieve all this fast. This is why we built and launched Tigris,” commented Ovais Tariq, CEO at Tigris Data. “Providing that single approach to data management in one developer-friendly environment makes it easier to prevent data infrastructure sprawl and let the developers focus on what they like best – building – while still providing all the services that developers need. Lastly, building this as an open source platform means that developers can avoid lock-in.

Quest Software Announces Public Beta for SharePlex for PostgreSQL

Quest Software, a global systems management, data protection and security software provider, announced the public beta of SharePlex for PostgreSQL. SharePlex is an industry-leading database management and replication solution designed to help customers ensure high availability and facilitate the movement of data between platforms.

“As enterprise companies look to move their critical Oracle workloads to PostgreSQL, they need trusted vendors to help fill the missing functionality gaps. Quest is committed to supporting customers’ evolving needs by adding new platforms,” said Bharath Vasudevan, Vice President Product Management and Marketing for Quest ISM. “With the release of SharePlex for PostgreSQL, we are empowering organizations to cost-effectively improve their data operations.”

Pega Introduces Pega Customer Data Connectors for Deeper, AI-Powered Data Analysis and Better Customer Outcomes

Pegasystems Inc. (NASDAQ: PEGA), the low-code platform provider that builds agility into the world’s leading organizations, announced Pega Customer Data Connectors that enable clients to easily connect their existing customer data platforms (CDPs) and other signal providers to Pega Customer Decision HubTM. These connectors allow organizations to stream signals from high-value platforms like Adobe, Celebrus, and ZineOne, and activate customer insights in real-time with AI-powered decisioning.

“Every day, companies leave a goldmine of insight on the table because their vendors lack the decisioning capabilities required to operationalize intent, impacting the customer experience,” said Matt Nolan, senior director, product marketing, Pega. “At the same time, it’s unrealistic to expect brands to replace the customer data solutions they’ve already invested in. That’s why Pega is launching Pega Customer Data Connectors – to help clients activate data at its fullest potential, with the freedom to use their CDP of choice. They can feed in whatever event streams or curated signals make sense for their business and Pega’s AI will help put it to work – and use the insights to build much deeper, more valuable customer relationships.”

Introducing Findability.Accelerate: Expediting the Journey from Data Silos to AI-Readiness

Findability Sciences, a global provider of enterprise AI solutions and an Inc. 5000 company, announced the launch of Findability.Accelerate, which provides the tools and framework necessary to equip enterprises to become ‘AI-ready’ and expedite their AI journey. The demand for AI tech has surged in the post-pandemic world; PwC reported that AI is estimated to contribute up to $15.7 trillion to the global economy by 2030 and change the game by emphasizing productivity and consumption. The challenge is that most organizations do not have a sound data architecture in place for successful AI implementation. In fact, the latest research has shown that up to 60% of AI projects fail. Organizations require that data is cleaned, analyzed and organized, but too often, enterprises are struggling with data overload and crippling silos that can hinder digital transformation. Findability.Accelerate mitigates this risk by providing an information architecture (IA) or IA (data) powered by products and solutions built on all major data platforms to ease migration. In addition, the platform also offers a customized comprehensive report to unify data for AI, as well as provides plugins for data migration and machine learning.

“There is no AI without IA,” says Anand Mahurkar, an Inc. 5000 entrepreneur and CEO of Findability Sciences. “The promise of artificial intelligence transforming businesses is appreciated by leadership across industries. However, the way AI is looked at, thought about, adopted and used, can only succeed with the right framework in hand. With the skills, processes and technology that Findability.Accelerate offers, an organization can successfully optimize data and succeed in its AI journey.”

Cockroach Labs Defines its Vision for the Serverless Database

Cockroach Labs, the company behind a leading cloud-native distributed SQL database CockroachDB, announced the general availability of its serverless database. Cockroach Labs built CockroachDB serverless to help teams accelerate their software design cycle from prototype to production, eliminate operational overhead, and always ensure the right capacity—without overspending. In addition, the company released its migration tool CockroachDB Molt and integrations with Vercel, HashiCorp Vault, and Hashicorp Terraform. These updates reflect Cockroach Labs’ deep commitment to helping developers build and scale world-class applications.

“We envision a world where your data-intensive applications effortlessly and securely serve millions of customers anywhere on the planet, with the exact right capacity for that moment – all enabled by a simple SQL API in the cloud,” said Nate Stewart, chief product officer at Cockroach Labs. “We’re a step closer to that vision now that CockroachDB Serverless is generally available. We’ve also released a new migration toolset and formed critical partnerships to help customers with existing applications take full advantage of CockroachDB.”

TDengine Cloud-Managed Service Delivers a Serverless, Purpose-Built Time-Series Data Platform for Instant Deployment, Elastic Scale and Simplified Management 

TDengine™ released TDengine Cloud, a fully managed, open-source cloud time-series data platform. TDengine Cloud lets organizations easily start, operate, and scale the TDengine time-series data platform in AWS, Azure, and Google Cloud. Released as open-source software in 2019, TDengine has more than 19,000 stars on GitHub and more than 154,000 instances across 50 countries worldwide. The TDengine Data Platform combines a database with caching, stream processing, and data subscription as a complete, purpose-built solution for time-series data. TDengine solves the common problem of high cardinality with a unique architecture that supports billions of data points while outperforming general-purpose and legacy time-series databases in data ingestion, querying, and compression. 

“Not all companies have the expertise, time, or resources to fully support a time-series database infrastructure, especially as data continues to flood in and use cases scale,” said Jeff Tao, founder and CEO of TDengine. “TDengine Cloud enables developers to stand up a time-series data platform in seconds and removes all the ongoing operational and management burdens now and as those applications and use cases scale in the future.” 

SoundHound Unveils Full Suite of Edge and Cloud Connectivity Solutions to Boost Accuracy and Privacy in Voice AI

SoundHound AI, Inc. (Nasdaq: SOUN), a global leader in voice artificial intelligence, announced the availability of a whole suite of Edge and Cloud connectivity solutions that will allow brands to voice-enable almost any product, device, or service. Businesses looking to deploy voice AI can choose from options that match their available processing power and end-user needs. These include fully-embedded Edge technology (including a new EdgeLite option), exclusively Cloud-connected technology, or a hybrid combination of Edge+Cloud.

“Voice technology is now a must for products destined for the consumer market, but that doesn’t mean it’s one-size-fits-all. Here we’re offering a range of connectivity options that deliver fast and accurate voice AI to meet different needs,” said James Hom, Co-Founder and Chief Product Officer at SoundHound. “The availability of more Edge options will allow businesses to store and protect sensitive data locally – which could help brands build customer trust. Our hybrid options help supercharge speed and accuracy. So whatever the use case or computing capacity, we can match it for optimal results.”

Bluesky Aims to Save Snowflake Users Millions by Optimizing Workloads

Bluesky formally launched with its first product that provides unprecedented visibility into Snowflake workload usage and costs as well as actionable insights and workload specific recommendations for maximum optimization. Bluesky is already delivering value at well-known brands.

Bluesky co-founders Mingsheng Hong (CEO) and Zheng Shao (CTO) used their rich experience building global scale data systems at Google and Uber to ensure Bluesky goes beyond mere cost visibility to provide deep insights into how data is being used and the wider implications. 

“Bluesky understands how patterns across the whole data fleet combine to add value or waste money. We’re able to clearly explain how to achieve the business value our customers are looking for. Bluesky’s intelligent monitoring ensures our recommendations stay relevant as our customers innovate with data. With Bluesky, customers can make informed decisions with confidence, now and in the future,” said Mingsheng Hong, co-founder and CEO of Bluesky. Launches Video Denoiser for Improved Night Vision, a developer of image processing software, announced the launch of a real-time video denoiser that improves video image quality. It can be applied to extend the operating conditions for the majority of the approximately seven billion image sensors manufactured each year. AI has been previously used for image noise reduction, but mostly for still images. The algorithms that have developed are particularly efficient and sufficiently lightweight to be deployed on cost effective silicon, and to run in real time, at the edge.

“In very low light, when there are few photons for an image sensor to capture, noise is the limiting factor,” says Yoav Taeib, CTO and Co-Founder at “For human vision applications, this noise adds speckles, blurs, and distortion to images, and for machine vision it reduces the accuracy of object recognition. It is not feasible to simply capture, say, ten times more photons because that would need an image sensor and lens that is ten times bigger, driving up costs. An AI based approach, that uses the raw image data and uses a sophisticated algorithm to separate the noise from the image signal is a more effective way to extend camera performance.”

SAPEON X220 has revealed its highest level of performance in the latest MLPerf benchmark test

SAPEON, a global AI semiconductor company, announced that its first commercialized artificial intelligence semiconductor chip, X220, was acknowledged for its groundbreaking AI processing speed and unrivaled efficiency in the latest MLPerf benchmark test.  

SAPEON X220 has demonstrated industry-leading performance, outperforming A2[1], NVIDIA’s latest GPU, which dominates the market. In MLPerf’s Inference: Datacenter benchmark test, which evaluates the performance of AI cloud services for data centers, X220-Compact outperformed NVIDIA A2 by 2.3 times, while X220-Enterprise achieved 4.6 times faster performance.

The benchmark test results also showed that SAPEON is superior in terms of power efficiency in addition to absolute performance. In terms of performance-per-watt capabilities (based on maximum power consumption), the X220-Compact was 2.2 times more efficient than the NVIDIA A2, and the X220-Enterprise was 2.0 times more efficient.

“SAPEON is one of the world’s leading AI semiconductor companies, and we are pleased that X220 – the competitiveness of which has already been verified through internal commercialization – has been independently recognized for its performance excellence in MLPerf benchmark testing and has received great attention in the global market,” said Soojung Ryu, CEO of SAPEON. “We plan to expand X220’s various application fields in the future, and in the second half of next year, we are confident that we will create a gap with competing products with the next-generation chip X330, which represents a further improvement in performance.”

Kensu launches the first Data Observability Community Edition

Kensu, the data observability company, announced the Kensu Community Edition, supporting the data community with the first free solution to monitor the health of their data pipelines at the source and explore first-hand the potential of this new data solution category.

“Data observability is a game changer for data teams,” explained Andy Petrella, Co-Founder and Chief Product Officer at Kensu. “It goes beyond data quality by providing data leaders and practitioners with deep visibility into the health of their data in motion. The fact that today they can get contextual insights in real time about how and when the applications are producing and consuming data will finally allow them to implement trustworthy end-to-end data solutions.”


Excelion Partners is proud to announce their new division, Snow Fox Data. Snow Fox Data is a premier data strategy, data science and analytics solutions provider. Headquartered in Wisconsin and serving customers worldwide, they provide a vast landscape of knowledge that supports success through data-driven decision making. A team of data architects, data scientists, data engineers, and data analysts, Snow Fox Data empowers clients to make clearer decisions through clever data solutions.

“We have a passionate team of experts who are committed to helping companies be successful throughout their data journey,” says Greg Oppermann, President of Excelion Partners and its newest division, Snow Fox Data. “We are ready to take this next step and enhance our support for companies who depend on powerful data science and analytics to run their business.”

Edgeless Systems Releases First Runtime-Encrypted Kubernetes as Open Source

Edgeless Systems, a pioneering Confidential Computing company that is turning the public cloud into the safest place for sensitive data, announced the open source release of Constellation, the first Confidential Kubernetes. Constellation allows anyone to keep their Kubernetes clusters verifiably shielded from the underlying cloud infrastructure and encrypted end-to-end. It is available now on GitHub and comes with new unique features such as “whole cluster” attestation.   

“Edgeless Systems is building the open source infrastructure for the Confidential Computing revolution,” said Felix Schuster, CEO, Edgeless Systems. “The hardware and features required for Constellation mostly weren’t even available in the cloud 12 months ago, but we started the necessary work to ensure Kubernetes users can secure all their data – in rest, in transit and now in use. By making Constellation available to everyone, we can help accelerate the adoption of more secure cloud computing workloads.”

MOV.AI and Lanner Electronics Announce Fully Integrated Platform Powered by NVIDIA Isaac ROS to Accelerate Robotics Development and Improve Operational Efficiency in Industrial Environments

MOV.AI and Lanner Electronics announced the integration of Lanner’s Edge AI computing appliance, MOV.AI‘s Robotics Engine PlatformTM, and the NVIDIA Isaac robotics platform. The integration provides Autonomous Mobile Robot (AMR) manufacturers and automation integrators with a robust platform that speeds up development, improves operational efficiency and optimizes robot performance in dynamic industrial environments.

The new integrated solution solves all these issues by leveraging Lanner’s EAI-I130 NVIDIA Jetson-based edge AI computing appliance and MOV.AI’s Robotics Engine PlatformTM that incorporates NVIDIA Isaac ROS GEMs, which are hardware-accelerated packages for perception, SLAM navigation, image processing and more. The joint offering provides robot developers with fully integrated high-performance hardware, hardware-optimized robotics SDKs and a visual IDE that wraps it together to speed up development. The solution speeds robot time to market and ensures high-performance robots.

Optimized for AI functionality, performance, and ease of deployment, Lanner’s Edge AI appliances are NVIDIA NGC-ready with NVIDIA GPU Compatibility. The appliances are integrated with the MOV.AI’s Robotics Engine PlatformTM that offers developers a visual IDE for faster development and deployment. Developers can drag and drop the NVIDIA Isaac ROS GEMs directly in the MOV.AI development tools to quickly build high-performance robots.

“Our expertise in creating NVIDIA-optimized edge computing servers, combined with MOV.AI’s state-of-the-art AMR software powered by NVIDIA edge AI and robotics technologies, provides an off-the-shelf platform to build enterprise-grade autonomous robots for today’s challenging industrial environments,” said Jeans Tseng, CTO of Lanner Electronics. “We are confident that our AMR platform will enable service providers and manufacturers to quickly deploy the top-performing AMR solution to the industrial IoT applications.”

“This is exciting on several levels,” according to According to Motti Kushnir, MOV.AI’s CEO. “First and foremost the integration allows fast time to market for a superior product that meets the needs of today’s warehouse automation challenges. Logistics is a $9 trillion industry, and automation is playing an important role in its optimization. We are excited to integrate with NVIDIA Isaac ROS GEMs as part of our strategy to improve operational efficiency and accelerate deployment of AMRs in warehouses and industrial manufacturing environments. Second, from MOV.AI’s perspective, this is a huge achievement. NVIDIA, with its Isaac platform, is a major force in the robotics industry, continuously driving it forward. Together with Lanner, we are honored to partner to provide the robotics community with the tools they need to create robots that deliver value quickly and continuously.”

Mperativ Unlocks Strategic AI for Marketing with First Cloud Offering to Bring AI Predictions to Marketing Planning and Measurement

Mperativ, the Revenue Marketing Platform that connects marketing activities to revenue outcomes, announced AI-powered platform features, including Marketing Pipeline Coverage Analysis and Marketing Opportunity Scoring. The new capabilities are industry-first in bringing the strategic value of AI to marketers and their stakeholders. With Marketing Pipeline Coverage Analysis, marketing and revenue teams can more precisely determine the exact pipeline coverage necessary across every business segment to hit revenue goals, rather than assuming flat 3X-4X coverage. Marketing and revenue teams can then more effectively deploy resources to different activities and areas of the business. Marketing Opportunity Scoring aids this deployment by providing insights on which specific potential opportunities have the highest propensity to convert to pipeline. Opportunity Scores can be paired with 3rd party intent data to identify the most likely paths to revenue. Combined, these capabilities finally embed AI predictions into the strategic marketing lifecycle, removing the guesswork from the marketing planning and measuring process.

“Marketing and revenue teams struggle to overcome the historical disconnect between reporting from marketing and sales systems,” said Jim McHugh, co-founder and CEO at Mperativ. “This is compounded by a prevailing marketing credibility gap entrenched by the use of outdated lead-centric marketing metrics that do not meet revenue teams’ needs. We developed these new features to equip marketing leaders with a powerful predictive platform that eliminates the credibility gap without the cost, time and resource-intensive construction of a custom data science practice.”

Bitfount reaches milestone in making the world’s intractable data interactable 

Bitfount announced the launch of its open beta product, a distributed data science platform making it possible for data custodians and data scientists to collaborate in performing privacy-preserving data analysis and ML without transferring or revealing raw data. From private SQL analysis to federated machine learning and evaluation, Bitfount helps data scientists and custodians safely harness the potential value of data collaboration. The launch coincides with Bitfount’s debut at Big Data LDN, where Bitfount CEO, Blaise Thomson, will speak about how the techniques powering Bitfount’s open beta product can enable privacy-preserving data collaboration on sensitive datasets such as patient, financial, or other protected data categories. 

“Unlocking the value of data for the benefit of humankind has always been core to Bitfount’s vision, and for the first time today, anyone can sign up to contribute to and benefit from the Bitfount community and vision. We look forward to seeing what our community builds,” expresses Bitfount CEO, Blaise Thomson. While Bitfount’s platform is currently leveraged to ensure the safety of data analysis in healthcare and financial-services contexts, its open beta offering is built for general purpose use across any industries or sectors wishing to collaborate to analyse or build models in association with sensitive data.

Syniti Announces New Data Quality and Catalog Capabilities to Help Deliver Clean, Actionable Data

Syniti, a global leader in enterprise data management, announced new data quality and catalog capabilities available in its industry leading Syniti Knowledge Platform, building on the enhancements in data migration and data matching added earlier this year. The Syniti Knowledge Platform now includes data quality, catalog, matching, replication, migration and governance, all available under one login, in a single cloud solution. This provides users with a complete and unified data management platform enabling them to deliver faster and better business outcomes with data they can trust.

“Poor quality data pollutes the entire organization, negatively impacting business operations and wasting time, money and resources,” said Kevin Campbell, CEO, Syniti. “We have purpose-built a data platform to drive business value as opposed to the many siloed solutions that treat data quality as purely a technical exercise. We want our customers to spend more time drawing insights from trusted data versus finding and fixing data problems.”

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