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.
C3 AI Releases New C3 Generative AI Suite
C3 AI (NYSE: AI), the Enterprise AI application software company, announced the launch of the C3 Generative AI Suite including 28 new domain-specific generative AI offerings available to address the unique needs of industries, business processes, and enterprise systems. The new offerings combine C3 AI’s deep enterprise domain and industry expertise with the latest innovations in generative AI.
“The market interest that we are seeing in C3 Generative AI is staggering,” said Thomas M. Siebel, C3 AI CEO. “The addressable market is unknowably large and appears to more than double our Enterprise AI market opportunity. You can expect that we will be investing in the coming quarters to maximize our first-to-market advantage.”
ArrayFire Announces Version 3.9 Supporting oneAPI Devices
ArrayFire announced the release of ArrayFire v3.9, a major update to the popular GPU library for technical computing. With this update, ArrayFire introduces a new backend fully supporting oneAPI devices alongside its existing CUDA, OpenCL, and CPU backends.
Since its inception in 2007, ArrayFire has been a technical computing benchmark, offering an easy-to-use software library that harnesses the power of GPUs and accelerators to optimize computing performance. Trusted by professionals across industries, ArrayFire continues to push the boundaries of what’s possible in parallel computing.
“We are excited to bring the power of oneAPI device support to our user community,” commented John Melonakos, an ArrayFire maintainer and CEO of ArrayFire Consulting. “Version 3.9 signifies our commitment to supporting major technological trends and ensuring that our users have access to cutting-edge features and unparalleled performance.”
Lanner Electronics Collaborates with Hailo to Unveil Revolutionary PCIe AI Acceleration Card – Falcon Lite
Lanner Electronics, a leading provider of advanced network appliances and edge AI computing platforms, introduced the new PCIe AI Acceleration Card, Falcon Lite, powered by Hailo-8™ AI processors. The Falcon Lite’s modular PCIe form factor provides a flexible solution for solution providers looking to accelerate edge AI workloads with deployment flexibility and power efficiency.
“We are thrilled to collaborate with Hailo to introduce the Falcon Lite PCIe AI Acceleration Card to the market,” said Jeans Tseng, CTO of Lanner. “As AI continues to transform industries, our commitment to innovation drives us to deliver top-tier solutions that empower businesses to harness the full potential of artificial intelligence. The Falcon Lite represents a significant leap forward in AI processing power, and we are confident it will drive new possibilities for AI-driven applications across various sectors.”
Braze Introduces New Data Integration Innovations to Help Brands Create Personalized, Cross-Channel Campaigns Faster
Braze (Nasdaq: BRZE), the comprehensive customer engagement platform that powers interactions between consumers and the brands they love, unveiled new and enhanced data features, partnerships, and functionality to help brands streamline data integration and reduce time-to-value. Leveraging these advancements, brands will be able to easily access and activate valuable first-party data quickly to power personalized customer engagement strategies that can drive loyalty, retention, and revenue. In addition, Braze announced the expansion of its Cloud Data Ingestion offering integrations with Amazon Redshift from Amazon Web Services (AWS), Databricks’ Lakehouse Platform, and Google BigQuery, making it easier for marketers to directly access data in Braze.
“Leveraging Braze, technical teams can deliver more value faster, spend less time building extra data pipelines, and empower marketers to quickly take action on accurate, accessible data,” said Kevin Wang, Chief Product Officer of Braze. “Notably, with the expansion of our Cloud Data Ingestion partnerships to include leading data warehouses like Databricks, marketers can seamlessly connect and sync data to create more personalized, creative customer engagement strategies at scale.”
Civo showcases its new Machine Learning Speech to Text Managed Service
Civo, the pure-play cloud-native service provider, revealed its new High-Performance Machine Learning Speech to Text Managed Service named Civo Recite. It will be demoed to the tech community for the first time today at Civo Navigate Europe – Civo’s first tech conference in Europe, held in London.
Recite is one of the fastest audio and video to text translation services on the market. Users are able to upload an audio file or audio stream and receive a high-quality transcription with zero configuration and setup. The fully managed service is based on OpenAI’s Whisper Large-v2, which has been rebuilt for Civo’s Bleeding Edge Cloud. Accelerated by Civo’s High-Performance Nvidia GPU Infrastructure, the service supports more than fifty languages and over seven file formats. The service is also ready for large audio files and big data formats, addressing enterprise adoption and surpassing OpenAI’s 25 MB file limit.
Josh Mesout, Chief Innovation Officer at Civo, said, “Machine learning is right at the heart of some of the most exciting innovation in tech today. Businesses are already seeing the benefits. One of the biggest opportunities is streamlining time-intensive processes, freeing staff up to focus on higher value tasks. But we can always do better. Too often these tools do not meet the needs of users, with complexity and inefficiencies in how they are run limiting their value. Every user should have access to ML tooling that is high performance, easy to use, and does not cost the Earth to run. At Civo we are committed to pushing forward ML innovation, making developers’ lives easier with our technology every step of the way. Civo Recite is our next step in upholding this promise to developers.”
InfluxData Announces InfluxDB Clustered to Deliver Time Series Analytics for On-Premises and Private Cloud Deployments
InfluxData, creator of a leading time series platform InfluxDB, announced InfluxDB Clustered, its self-managed time series database for on-premises or private cloud deployments. With the release of InfluxDB Clustered, InfluxData completes its commercial product line developed on InfluxDB 3.0, its rebuilt database engine optimized for real-time analytics with higher performance, unlimited cardinality, and SQL support.
InfluxDB Clustered is the evolution of InfluxDB Enterprise, InfluxData’s long-standing enterprise software product for on-premises and private cloud environments. Now with the release of InfluxDB Clustered, those same customers gain all the capabilities of the reimagined InfluxDB 3.0, but now specifically packaged and configured for their own unique hosting environments and data storage requirements. Deployed natively in Kubernetes, InfluxDB Clustered combines the scale and flexibility of the cloud with the security and control of a self-managed infrastructure.
“This release brings InfluxDB 3.0’s fundamental tenets of performance – unlimited cardinality, high-speed ingest, real-time querying, and superior data compression – to customers deploying their own custom infrastructure,” said Rick Spencer, VP of Products, InfluxData. “With InfluxDB Clustered we complete our 3.0 product portfolio and deliver on our promise to customers, bringing the flexibility of the cloud and the power of InfluxDB 3.0 together for the self-managed stack.”
Quantum Expands Hybrid Cloud Leadership with New Features across End-to-End Unstructured Data Platform
Quantum Corporation (NASDAQ: QMCO), a leader in solutions for unstructured data, announced new features in the company’s end-to-end data platform, including advances to its policy-driven data movement technologies, to help customers build their ideal hybrid cloud workflow to seamlessly bridge on-prem deployments with multi-cloud integration. With the massive amount of data customers need to retain for business and compliance purposes, customers are using both public and private cloud resources to store and manage this data, driven by their budget, frequency with which they need to access the data, and their data protection requirements. With these new features, customers can place data exactly where it’s needed, when it’s needed. By using a highly flexible and powerful hybrid cloud environment, customers increase operations agility, reduce business risk, and optimize costs across on-prem and public cloud resources.
“Our strategic vision is to deliver the best end-to-end data platform from on-premises to any cloud that empowers our customers to address their unstructured data needs across the entire data lifecycle,” said Brian Pawlowski, chief development officer, Quantum. “This isn’t about ‘public cloud versus private cloud’; It’s about giving customers choice and enabling them to create flexible, hybrid cloud workflows that are designed for their unique needs and goals, and these new features we are delivering make that easier for customers to achieve.”
Domo Announces Domo.AI to Revolutionize the Way Businesses Manage and Deploy Artificial Intelligence
Domo (Nasdaq: DOMO) announced Domo.AI, a portfolio of comprehensive and flexible artificial intelligence (AI) services, powered by the company’s award-winning data experience platform. With Domo.AI, Domo users can access and capitalize on the broad possibilities of AI and have meaningful AI-powered experiences that help them multiply their impact on the business at scale.
“Our approach is rooted in the understanding that every business has unique needs and challenges that require flexibility and adaptability,” said Daren Thayne, chief technology officer and EVP of product, Domo. “Customer use cases for AI + Data have as many variations as there are companies and employee roles. The Domo platform — and our architectural approach to Domo.AI — is purpose-built to deliver on this need for unique data experiences that help businesses overcome real-world challenges and accelerate innovation and growth.”
Xactly Announces Xactly AI Copilot, a Next-Generation AI Engine Transforming Revenue Process Management
Xactly, a leader in intelligent revenue solutions, unveiled Xactly AI Copilot, an AI engine poised to revolutionize the way businesses manage and optimize their revenue processes. Backed by 18 years of proprietary and empirical performance data, Xactly AI Copilot is the industry’s first generative AI engine of its kind, granting revenue organizations unprecedented productivity boosts and streamlined workflows between stakeholders invested in the end-to-end revenue process.
“At Xactly, we remain committed to pushing the boundaries of what’s possible,” said Arnab Mishra, Chief Operating Officer at Xactly. “The accolades we’ve received for our innovations, along with the launch of Xactly AI Copilot, serve as a testament to our dedication to empowering organizations with cutting-edge technologies.”
Fauna Adds Groundbreaking New Database Language and Seamless Developer Experience to Enterprise Proven, Document-Relational Database
Fauna, the distributed document-relational database delivered as a cloud API, announced the general availability of their new TypeScript-inspired database language, new web and local development experiences, and the addition of a declarative database schema. Combined, these new capabilities deliver a superior software development experience for teams building and scaling new and existing applications.
The new database language and developer experience unleashes the power of Fauna’s industry-leading distributed, document-relational database. Fauna is used today by 3000+ development teams spanning 180+ countries for user-centric and distributed/edge applications, real-time services, stateful serverless and multi-tenant SaaS offerings.
“Fauna’s distributed, document-relational database provides the flexibility and familiarity of documents with the relationships, multi-region strong consistency and querying power of a relational database. Our API delivery model removes the burden of database operations,” said Eric Berg, CEO of Fauna. “A well-designed database language saves developers time, improves collaboration, and enhances performance. With FQL, the addition of schema management, and new and local cloud development experience, we’re bringing state-of-the-art software development practices to an operational data platform that securely scales without operations or limits.”
Neo4j Adds Vector Search Capability Within Its Native Graph Database for Richer Generative AI Insights
Neo4j®, a leading graph database and analytics company, announced that it has integrated native vector search as part of its core database capabilities. The result enables customers to achieve richer insights from semantic search and generative AI applications, and serve as long-term memory for LLMs, all while reducing hallucinations.
Neo4j’s graph database can be used to create knowledge graphs, which capture and connect explicit relationships between entities, enabling AI systems to reason, infer, and retrieve relevant information effectively. The result ensures more accurate, explainable, and transparent outcomes for LLMs and other generative AI applications. By contrast, vector searches capture implicit patterns and relationships based on items with similar data characteristics, rather than exact matches, which are useful when searching for similar text or documents, making recommendations, and identifying other patterns.
“We see value in combining the implicit relationships uncovered by vectors with the explicit and factual relationships and patterns illuminated by graph,” said Emil Eifrem, Co-Founder and CEO, Neo4j. “Customers when innovating with generative AI also need to trust that the results of their deployments are accurate, transparent, and explainable. With LLMs evolving so dynamically, Neo4j has become foundational for enterprises seeking to push the envelope on what’s possible for their data and their business.”
SADA Releases New Enterprise Data Warehouse Modernization Solution
SADA, a leading business and technology consultancy and award-winning Google Cloud partner, announced the availability of a new Enterprise Data Warehouse (EDW) Modernization solution to help businesses gain insight from their data. The solution is designed to lay the groundwork for enhanced analytics – empowering businesses globally to make real-time decisions while simultaneously enabling governance, lowering risk in making business decisions, and increasing compliance rigor, all powered by Google Cloud.
SADA’s EDW services include a discovery assessment, a foundation proof of concept implementation, and a complete Data Warehouse Platform Migration. SADA is partnering with FiveTran and ThoughtSpot, who will help implement these services and transform data into actionable insights.
“Data warehousing is the foundational backbone of an organization’s business analytics,” said Brian Suk, Associate CTO of Data at SADA. “As organizations continue throughout their digital transformation journey, EDW modernization solutions are necessary for success in the market. By working with SADA, customers can expect to realize value from their data quickly and increase the potential to grow revenue while saving costs.”
LogicMonitor Expands Observability Intelligence to New Environments
LogicMonitor, a leading SaaS-based unified observability platform for hybrid IT infrastructure, announced expanded integrations, insights and workflows to the LM Envision Platform. LogicMonitor is also introducing Dexda, an event management solution that filters through the noise of thousands of daily alerts by using advanced machine learning (ML) techniques, contextual enrichment capabilities and deduplication efforts. Together, these additions allow customers to reach a significantly lower mean time to resolution and lower risks to the business.
“Every business is under tremendous pressure to seamlessly deliver exceptional digital performance,” states Christina Kosmowski, CEO, LogicMonitor. “To efficiently do that, our customers look to us to contextualize the overwhelming amount of data within their complex IT environments.“
Agiloft Launches AI Trainer to Put the Power of Artificial Intelligence Into the Hands of Non-Technical Users
Agiloft, a leader in agile contract lifecycle management (CLM), announced the release of AI Trainer, a powerful, new AI model training capability that will empower non-technical users to fully customize the way they review and analyze contracts. Designed to be a force multiplier for legal and contract teams, AI Trainer empowers non-technical, subject matter experts to train Agiloft’s AI to identify important key terms and clauses, so they can quickly analyze and draw actionable insights from their contracts, then share that business-critical intelligence with the rest of their organization to drive real enterprise value. Agiloft’s AI Trainer also actively accelerates its own training process by continuously learning and then auto-suggesting additional relevant data for users to consider tagging.
“No two contracts are quite alike, nor are any two organizations. That is why relying on pre-trained, generic AI models alone simply does not get the job done,” explained Agiloft’s Chief Product Officer Andy Wishart. “We are introducing AI Trainer to ensure more organizations can use our best-of-breed AI to surface, analyze, and report on their contracts effectively. This provides legal and contracting teams with an easy-to-use, self-service tool that helps them codify their expertise to enhance the automation of the contracting process. AI Trainer empowers the very teams who are closest to the contracting process and gives them a way to train and individualize the systems they use to uncover and categorize key terms and clauses in their contracts.”
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