Alternatives to Zuro

DataSet offers dynamic, searchable real-time insights that can be stored indefinitely, either through DataSet-hosted solutions or customer-managed, cost-effective S3 storage options. It enables the rapid ingestion of structured, semi-structured, and unstructured data, creating an unlimited enterprise framework for live data queries, analytics, insights, and retention without adhering to rigid data schema requirements. This technology is favored by engineering, DevOps, IT, and security teams seeking to harness the full potential of their data. With sub-second query performance driven by a patented parallel processing architecture, users can operate more efficiently and effectively to enhance business decision-making processes. It can effortlessly handle hundreds of terabytes of data without the need for rebalancing nodes, storage management, or resource reallocation. The platform scales flexibly and limitlessly, while its cloud-native architecture enhances efficiency, reducing costs and maximizing output. Users benefit from a predictable cost structure that delivers unparalleled performance, ensuring that businesses can thrive in a data-driven landscape. Additionally, the ease of use and robust capabilities of the system empower organizations to focus on innovation rather than data management challenges.

All aspects of Digital Marketing will be optimized by Artificial Intelligence today, with the exception of Creatives. AdCreative.ai aims to change that. It makes data-backed, results-oriented ad creatives easily accessible. Convert conversion-focused ad creativity in minutes while remaining true to brand. Our AI allows you to test more creatives and decrease the time spent on the design process. You can get up to 14x higher conversion and click-through rates. Create headlines and sales-focused texts that are specific to the platform where you advertise. Our Artificial Intelligence will be your copywriter, so you can concentrate on what really matters: your business. You can see which creatives perform best in your ad account at a glance. Get inspired by your top-performing creatives and let our AI learn more from your data to bring you even better results.

Voyage AI is an advanced AI platform focused on improving search and retrieval performance for unstructured data. It delivers high-accuracy embedding models and rerankers that significantly enhance RAG pipelines. The platform supports multiple model types, including general-purpose, industry-specific, and fully customized company models. These models are engineered to retrieve the most relevant information while keeping inference and storage costs low. Voyage AI achieves this through low-dimensional vectors that reduce vector database overhead. Its models also offer fast inference speeds without sacrificing accuracy. Long-context capabilities allow applications to process large documents more effectively. Voyage AI is designed to plug seamlessly into existing AI stacks, working with any vector database or LLM. Flexible deployment options include API access, major cloud providers, and custom deployments. As a result, Voyage AI helps teams build more reliable, scalable, and cost-efficient AI systems.

Enhance your digital transformation initiatives and realize enduring business value by swiftly converting proprietary data into practical insights using our comprehensive GenAI platform. With Articul8’s GenAI engine, you can quickly build and launch enterprise GenAI applications through sleek APIs, ensuring seamless integration throughout your development processes. The advanced technologies of Articul8, including ModelMesh™, FlexLLM™, and LLM-IQ™, intelligently choose and coordinate a range of cutting-edge (SOTA) LLMs and probabilistic models that are tailored for optimal performance and efficiency, yielding significant business results and exceptional cost-effectiveness. All necessary data store connectors for our GenAI engines are conveniently included and fully supported, providing a "batteries included" experience. Additionally, you can dynamically scale data pre-processing and ingestion to streamline and expedite your GenAI implementations, enhancing overall efficiency.

We are excited to announce the launch of Phi-2, a language model featuring 2.7 billion parameters that excels in reasoning and language comprehension, achieving top-tier results compared to other base models with fewer than 13 billion parameters. In challenging benchmarks, Phi-2 competes with and often surpasses models that are up to 25 times its size, a feat made possible by advancements in model scaling and meticulous curation of training data. Due to its efficient design, Phi-2 serves as an excellent resource for researchers interested in areas such as mechanistic interpretability, enhancing safety measures, or conducting fine-tuning experiments across a broad spectrum of tasks. To promote further exploration and innovation in language modeling, Phi-2 has been integrated into the Azure AI Studio model catalog, encouraging collaboration and development within the research community. Researchers can leverage this model to unlock new insights and push the boundaries of language technology.

StarWind VTL enables organizations to transition away from expensive physical tape backup systems while still meeting regulatory requirements for data retention and archiving, utilizing on-premises Virtual Tape Libraries combined with cloud and object storage tiering. To safeguard your backups against ransomware threats, they can be kept "air-gapped" on virtual tapes. You have the flexibility to replicate and tier backups to any public cloud, utilizing industry-standard object storage for enhanced scalability, security, and cost-effectiveness. We are excited to present a consumption-based licensing model for StarWind VTL, eliminating restrictions on the number of installations or backup servers. Instead, you only pay for the data managed by the VTL instances operating within your infrastructure. Additionally, we offer automatic discounts for larger data sets, meaning that as your archive grows, the cost per terabyte decreases significantly. As we introduce the subscription model gradually across different regions, your sales representative is ready to provide you with specific information regarding availability in your area, ensuring that you have the best options suited for your needs. This approach allows businesses to enhance their backup strategies while optimizing their budgets effectively.

ZeroEntropy is an advanced retrieval and search technology platform designed for modern AI applications. It solves the limitations of traditional search by combining state-of-the-art rerankers with powerful embeddings. This approach allows systems to understand semantic meaning and subtle relationships in data. ZeroEntropy delivers human-level accuracy while maintaining enterprise-grade performance and reliability. Its models are benchmarked to outperform many leading rerankers in both speed and relevance. Developers can deploy ZeroEntropy in minutes using a straightforward API. The platform is built for real-world use cases like customer support, legal research, healthcare data retrieval, and infrastructure tools. Low latency and reduced costs make it suitable for large-scale production workloads. Hybrid retrieval ensures better results across diverse datasets. ZeroEntropy helps teams build smarter, faster search experiences with confidence.

Make critical decisions on operations in the moment while ensuring minimal adverse effects on the community and the environment. We gather sensing information from either your monitoring equipment or ours, transforming it into user-friendly software interfaces that support business decision-making. Designed to provide real-time insights, our solutions cater to clients in aviation, waste management, wastewater treatment, water purification, mining, and other sectors that depend on immediate feedback to optimize their operations. Enhance operational results, boost output, achieve significant cost reductions, and foster a positive relationship with local communities. Our software simplifies the interpretation of intricate environmental data in industrial settings, providing actionable insights. Utilizing digital twin technology for water treatment, our system is driven by machine learning and deterministic modeling. Over 150 of the leading airports worldwide rely on our solutions to ensure compliance with stakeholders and enhance operational efficiency, all while promoting sustainable practices in their operations. This commitment to sustainability not only benefits the environment but also strengthens community trust and engagement.

AI teams encounter obstacles that necessitate the development of innovative technologies, which we specialize in creating. Traditional data warehouses and lakes struggle to accommodate unstructured data types such as text, images, and videos. Our approach integrates AI with software development, specifically designed for data scientists, machine learning engineers, and data engineers alike. Instead of reinventing existing solutions, we provide a swift and cost-effective route to bring your projects into production. Your data remains securely stored under your control, and model training occurs on your own infrastructure. By addressing the limitations of current data handling methods, we ensure that AI teams can effectively meet their challenges. Our Studio functions as an extension of platforms like GitHub, GitLab, or BitBucket, allowing seamless integration. You can choose to sign up for our online SaaS version or reach out for an on-premise installation tailored to your needs. This flexibility allows organizations of all sizes to adopt our solutions effectively.

Seed2.0 Pro is a high-performance general-purpose AI model engineered for demanding enterprise and research environments. Built to manage long-chain reasoning and complex multi-step instructions, it ensures consistent and stable outputs across extended workflows. As the flagship model in the Seed 2.0 series, it introduces substantial enhancements in multimodal intelligence, combining language, vision, motion, and contextual understanding. The system achieves top-tier benchmark results in mathematics, coding, STEM reasoning, and multimodal evaluations, positioning it among leading industry models. Its advanced visual reasoning capabilities enable it to interpret images, reconstruct structured layouts, and generate fully functional interactive web interfaces from visual inputs. Beyond creative tasks, Seed2.0 Pro supports technical operations such as CAD design automation, scientific research problem-solving, and detailed data analysis. The model is optimized for real-world deployment, balancing inference depth with operational reliability. It performs strongly in long-context scenarios, maintaining coherence across extended documents and conversations. Additionally, its robust instruction-following capabilities allow it to execute highly specific professional commands with precision. Overall, Seed2.0 Pro combines research-level intelligence with production-grade performance for complex, high-value tasks.

Voyage AI has introduced voyage-3-large, an innovative general-purpose multilingual embedding model that excels across eight distinct domains, such as law, finance, and code, achieving an average performance improvement of 9.74% over OpenAI-v3-large and 20.71% over Cohere-v3-English. This model leverages advanced Matryoshka learning and quantization-aware training, allowing it to provide embeddings in dimensions of 2048, 1024, 512, and 256, along with various quantization formats including 32-bit floating point, signed and unsigned 8-bit integer, and binary precision, which significantly lowers vector database expenses while maintaining high retrieval quality. Particularly impressive is its capability to handle a 32K-token context length, which far exceeds OpenAI's 8K limit and Cohere's 512 tokens. Comprehensive evaluations across 100 datasets in various fields highlight its exceptional performance, with the model's adaptable precision and dimensionality options yielding considerable storage efficiencies without sacrificing quality. This advancement positions voyage-3-large as a formidable competitor in the embedding model landscape, setting new benchmarks for versatility and efficiency.

Composer 2 is a high-performance AI coding model available within Cursor, built to handle complex programming tasks with improved accuracy and efficiency. It is trained through advanced pretraining and reinforcement learning, allowing it to solve long-horizon coding problems that involve multiple steps and decisions. The model shows significant improvements across major benchmarks such as Terminal-Bench and SWE-bench Multilingual, reflecting its strong real-world coding capabilities. It delivers faster performance while maintaining high-quality outputs, making it suitable for demanding development workflows. Composer 2 is designed to balance intelligence and cost, offering competitive pricing compared to other frontier models. It also includes a faster variant that provides the same level of intelligence with optimized speed for time-sensitive tasks. The model is integrated directly into the Cursor platform, enabling seamless use within development environments. Its ability to handle complex coding scenarios makes it valuable for both individual developers and teams. Overall, Composer 2 enhances productivity by automating and accelerating software development tasks.

CelerData is an advanced SQL engine designed to enable high-performance analytics directly on data lakehouses, removing the necessity for conventional data warehouse ingestion processes. It achieves impressive query speeds in mere seconds, facilitates on-the-fly JOIN operations without incurring expensive denormalization, and streamlines system architecture by enabling users to execute intensive workloads on open format tables. Based on the open-source StarRocks engine, this platform surpasses older query engines like Trino, ClickHouse, and Apache Druid in terms of latency, concurrency, and cost efficiency. With its cloud-managed service operating within your own VPC, users maintain control over their infrastructure and data ownership while CelerData manages the upkeep and optimization tasks. This platform is poised to support real-time OLAP, business intelligence, and customer-facing analytics applications, and it has garnered the trust of major enterprise clients, such as Pinterest, Coinbase, and Fanatics, who have realized significant improvements in latency and cost savings. Beyond enhancing performance, CelerData’s capabilities allow businesses to harness their data more effectively, ensuring they remain competitive in a data-driven landscape.

IBM® StreamSets allows users to create and maintain smart streaming data pipelines using an intuitive graphical user interface. This facilitates seamless data integration in hybrid and multicloud environments. IBM StreamSets is used by leading global companies to support millions data pipelines, for modern analytics and intelligent applications. Reduce data staleness, and enable real-time information at scale. Handle millions of records across thousands of pipelines in seconds. Drag-and-drop processors that automatically detect and adapt to data drift will protect your data pipelines against unexpected changes and shifts. Create streaming pipelines for ingesting structured, semistructured, or unstructured data to deliver it to multiple destinations.

Gain a comprehensive understanding of your model's efficacy by logging both inputs and outputs while enhancing them with relevant metadata and user insights. This approach allows you to truly assess your model's functionality and identify areas that require refinement. Keep an eye out for errors and pinpoint underperforming user segments and scenarios that may need attention. The most effective models leverage user-generated data; therefore, systematically collect atypical or low-performing instances to enhance your model through retraining. Rather than sifting through countless outputs following adjustments to your prompts or models, adopt a programmatic evaluation of your LLM-driven applications. Rapidly identify and address performance issues by monitoring new deployments in real-time and effortlessly updating the version of your application that users engage with. Establish connections between your self-hosted or third-party models and your current data repositories for seamless integration. Handle enterprise-scale data effortlessly with our serverless streaming data flow engine, designed for efficiency and scalability. Moreover, Gantry adheres to SOC-2 standards and incorporates robust enterprise-grade authentication features to ensure data security and integrity. This dedication to compliance and security solidifies trust with users while optimizing performance.

Instill Core serves as a comprehensive AI infrastructure solution that effectively handles data, model, and pipeline orchestration, making the development of AI-centric applications more efficient. Users can easily access it through Instill Cloud or opt for self-hosting via the instill-core repository on GitHub. The features of Instill Core comprise: Instill VDP: A highly adaptable Versatile Data Pipeline (VDP) that addresses the complexities of ETL for unstructured data, enabling effective pipeline orchestration. Instill Model: An MLOps/LLMOps platform that guarantees smooth model serving, fine-tuning, and continuous monitoring to achieve peak performance with unstructured data ETL. Instill Artifact: A tool that streamlines data orchestration for a cohesive representation of unstructured data. With its ability to simplify the construction and oversight of intricate AI workflows, Instill Core proves to be essential for developers and data scientists who are harnessing the power of AI technologies. Consequently, it empowers users to innovate and implement AI solutions more effectively.

dRPC is a decentralized RPC network designed to improve security, reliability, and cost-effectiveness for Web3 enterprises, regardless of their scale. Our aim is to create the most dependable and affordable data provision solution through a decentralized framework. This includes an automatic intelligent node balancing system, robust data verification, and the ability to make payments in stablecoins. From the outset, our model establishes an economy that benefits all participants in the network by connecting and utilizing existing nodes while ensuring transparency in request routing. By leveraging these innovative features, we strive to empower Web3 companies to thrive in an ever-evolving digital landscape.

Personified is a chatbot-as-a-service that utilizes LLM technology to effectively engage with users. This chatbot is designed to pull insights from various files and datasets, enabling it to deliver accurate and trustworthy responses to inquiries. We prioritize the confidentiality and security of our clients' information, ensuring that your knowledge is only utilized for support when necessary and not for model training. Our commitment to protecting your data is an ongoing priority, and we implement robust policies to safeguard against any potential mishandling of information. In this way, we strive to maintain a trustworthy relationship with all our users.

The Gemma family consists of advanced, lightweight models developed using the same innovative research and technology as the Gemini models. These cutting-edge models are equipped with robust security features that promote responsible and trustworthy AI applications, achieved through carefully curated data sets and thorough refinements. Notably, Gemma models excel in their various sizes—2B, 7B, 9B, and 27B—often exceeding the performance of some larger open models. With the introduction of Keras 3.0, users can experience effortless integration with JAX, TensorFlow, and PyTorch, providing flexibility in framework selection based on specific tasks. Designed for peak performance and remarkable efficiency, Gemma 2 is specifically optimized for rapid inference across a range of hardware platforms. Furthermore, the Gemma family includes diverse models that cater to distinct use cases, ensuring they adapt effectively to user requirements. These lightweight language models feature a decoder and have been trained on an extensive array of textual data, programming code, and mathematical concepts, which enhances their versatility and utility in various applications.

Cloud Datalab is a user-friendly interactive platform designed for data exploration, analysis, visualization, and machine learning. This robust tool, developed for the Google Cloud Platform, allows users to delve into, transform, and visualize data while building machine learning models efficiently. Operating on Compute Engine, it smoothly integrates with various cloud services, enabling you to concentrate on your data science projects without distractions. Built using Jupyter (previously known as IPython), Cloud Datalab benefits from a vibrant ecosystem of modules and a comprehensive knowledge base. It supports the analysis of data across BigQuery, AI Platform, Compute Engine, and Cloud Storage, utilizing Python, SQL, and JavaScript for BigQuery user-defined functions. Whether your datasets are in the megabytes or terabytes range, Cloud Datalab is equipped to handle your needs effectively. You can effortlessly query massive datasets in BigQuery, perform local analysis on sampled subsets of data, and conduct training jobs on extensive datasets within AI Platform without any interruptions. This versatility makes Cloud Datalab a valuable asset for data scientists aiming to streamline their workflows and enhance productivity.

Hydrolix serves as a streaming data lake that integrates decoupled storage, indexed search, and stream processing, enabling real-time query performance at a terabyte scale while significantly lowering costs. CFOs appreciate the remarkable 4x decrease in data retention expenses, while product teams are thrilled to have four times more data at their disposal. You can easily activate resources when needed and scale down to zero when they are not in use. Additionally, you can optimize resource usage and performance tailored to each workload, allowing for better cost management. Imagine the possibilities for your projects when budget constraints no longer force you to limit your data access. You can ingest, enhance, and transform log data from diverse sources such as Kafka, Kinesis, and HTTP, ensuring you retrieve only the necessary information regardless of the data volume. This approach not only minimizes latency and costs but also eliminates timeouts and ineffective queries. With storage being independent from ingestion and querying processes, each aspect can scale independently to achieve both performance and budget goals. Furthermore, Hydrolix's high-density compression (HDX) often condenses 1TB of data down to an impressive 55GB, maximizing storage efficiency. By leveraging such innovative capabilities, organizations can fully harness their data potential without financial constraints.

Opus, recognized as our most advanced model, surpasses its competitors in numerous widely-used evaluation benchmarks for artificial intelligence, including assessments of undergraduate expert knowledge (MMLU), graduate-level reasoning (GPQA), fundamental mathematics (GSM8K), and others. Its performance approaches human-like comprehension and fluency in handling intricate tasks, positioning it at the forefront of general intelligence advancements. Furthermore, all Claude 3 models demonstrate enhanced abilities in analysis and prediction, sophisticated content creation, programming code generation, and engaging in conversations in various non-English languages such as Spanish, Japanese, and French, showcasing their versatility in communication.

5X is a comprehensive data management platform that consolidates all the necessary tools for centralizing, cleaning, modeling, and analyzing your data. With its user-friendly design, 5X seamlessly integrates with more than 500 data sources, allowing for smooth and continuous data flow across various systems through both pre-built and custom connectors. The platform features a wide array of functions, including ingestion, data warehousing, modeling, orchestration, and business intelligence, all presented within an intuitive interface. It efficiently manages diverse data movements from SaaS applications, databases, ERPs, and files, ensuring that data is automatically and securely transferred to data warehouses and lakes. Security is a top priority for 5X, as it encrypts data at the source and identifies personally identifiable information, applying encryption at the column level to safeguard sensitive data. Additionally, the platform is engineered to lower the total cost of ownership by 30% when compared to developing a custom solution, thereby boosting productivity through a single interface that enables the construction of complete data pipelines from start to finish. This makes 5X an ideal choice for businesses aiming to streamline their data processes effectively.

DDN and Tintri's IntelliFlash systems merge high-performance capabilities with cost-effectiveness to create a fully functional intelligent storage infrastructure that independently fine-tunes SSD-to-HDD ratios while offering scalable performance. The management features are designed to save time and provide superb support for enterprise applications, allowing for the consolidation of diverse workloads with simultaneous multiprotocol support for block, file, object storage, and virtual machines, all on a unified platform. Additionally, these systems improve cost-efficiency through advanced data reduction technologies, quick backup solutions, robust disaster recovery options, and powerful analytics software that accelerates data insights. Furthermore, DDN's A³I solution effectively tackles the challenges of unstructured data management, addressing the demands of data-heavy applications. This architecture not only supports unstructured data but also enhances the performance and scalability for structured data types, including call and transaction records as well as consumer behavior analytics, ensuring that organizations can efficiently manage a broad spectrum of data. As a result, businesses can achieve enhanced operational efficiency while maintaining flexibility in their storage solutions.

Monitor the performance of your models to identify and respond to data drift, enhancing accuracy for improved business results. Foster trust, ensure regulatory compliance, and promote actionable machine learning outcomes using Arthur’s APIs that prioritize explainability and transparency. Actively supervise for biases, evaluate model results against tailored bias metrics, and enhance your models' fairness. Understand how each model interacts with various demographic groups, detect biases early, and apply Arthur's unique bias reduction strategies. Arthur is capable of scaling to accommodate up to 1 million transactions per second, providing quick insights. Only authorized personnel can perform actions, ensuring data security. Different teams or departments can maintain separate environments with tailored access controls, and once data is ingested, it becomes immutable, safeguarding the integrity of metrics and insights. This level of control and monitoring not only improves model performance but also supports ethical AI practices.

Nebula provides a streamlined solution for deploying and scaling AI projects quickly, efficiently, and at a lower cost on highly reliable, on-demand GPU infrastructure. With Nebula’s cloud, powered by cutting-edge Nvidia GPUs, you can securely train and infer your models while managing your containerized workloads through an intuitive orchestration layer. The platform offers MLOps and low-code/no-code tools that empower business teams to create and implement AI use cases effortlessly, enabling the fast deployment of AI-driven applications with minimal coding required. You have the flexibility to choose between the Nebula containerized AI cloud, your own on-premises setup, or any preferred cloud environment. With Nebula Unify, organizations can develop and scale AI-enhanced business applications in just weeks, rather than the traditional months, making AI adoption more accessible than ever. This makes Nebula an ideal choice for businesses looking to innovate and stay ahead in a competitive marketplace.

Alactic AGI is an AI platform designed for the cloud that streamlines the processes of ingesting, grounding, and transforming unstructured data—including URLs, images, PDFs, and various documents—into datasets that are ready for use with Large Language Models. By providing contextual precision, scalability, and robust enterprise-level security, it empowers teams to create, refine, and implement AI systems more rapidly and with increased assurance. This innovative platform significantly enhances the efficiency of AI workflows, making it easier for organizations to leverage advanced AI capabilities.

Wayve stands out as a pioneering platform for autonomous driving technology, leveraging AI foundation models to fuel the development of future self-driving vehicles with its innovative Embodied AI strategy. The centerpiece of Wayve's advancement is a self-learning “AI driver” that empowers vehicles to interpret, anticipate, and maneuver through intricate real-world scenarios by acquiring knowledge through experience instead of depending on pre-programmed rules or detailed maps. By utilizing primarily camera inputs and deep learning techniques, this system cultivates a versatile driving intelligence capable of adjusting to new roads, urban landscapes, and various vehicle types with minimal need for retraining. Wayve's approach features a mapless and hardware-agnostic framework that allows automobile manufacturers to introduce sophisticated driver assistance and autonomous functions via software updates, accommodating automation levels ranging from L2+ to L4. This innovative design is intended to perpetually learn from both real-world experiences and simulated environments, fostering safe and instinctive driving behavior while enhancing the vehicle's response to unforeseen circumstances. With its focus on adaptability and continuous improvement, Wayve aims to redefine how self-driving technology integrates into everyday transportation.

Prisma AIRS AI Runtime Security is a specialized solution aimed at safeguarding applications, agents, models, and data that utilize LLM technology during their operational phases, providing real-time oversight, assurance, and governance throughout the AI lifecycle. This system continuously observes AI behavior, implementing protective measures that identify and mitigate threats which conventional security tools often overlook, such as prompt injection, harmful code, toxic outputs, data leakage, and unauthorized or unsafe actions. It empowers organizations to uncover all AI assets in operation, including shadow AI, while gaining insights into the interactions among agents, applications, and models across various environments. By consistently evaluating risk through the testing of AI systems, managing permissions, and monitoring the security posture in real-time, it incorporates controls that prevent manipulation and exposure during runtime engagements. With its adaptive defense mechanism, it protects against both evolving threats and zero-day vulnerabilities, leveraging real-time analysis of inputs, outputs, and execution processes. Ultimately, this innovative solution enhances an organization's ability to maintain a secure AI framework while promoting trust and compliance in AI deployments.

NVIDIA Isaac is a comprehensive platform designed for the development of AI-driven robots, featuring an array of CUDA-accelerated libraries, application frameworks, and AI models that simplify the process of creating various types of robots, such as autonomous mobile units, robotic arms, and humanoid figures. A key component of this platform is NVIDIA Isaac ROS, which includes a suite of CUDA-accelerated computing tools and AI models that leverage the open-source ROS 2 framework to facilitate the development of sophisticated AI robotics applications. Within this ecosystem, Isaac Manipulator allows for the creation of intelligent robotic arms capable of effectively perceiving, interpreting, and interacting with their surroundings. Additionally, Isaac Perceptor enhances the rapid design of advanced autonomous mobile robots (AMRs) that can navigate unstructured environments, such as warehouses and manufacturing facilities. For those focused on humanoid robotics, NVIDIA Isaac GR00T acts as both a research initiative and a development platform, providing essential resources for general-purpose robot foundation models and efficient data pipelines, ultimately pushing the boundaries of what robots can achieve. Through these diverse capabilities, NVIDIA Isaac empowers developers to innovate and advance the field of robotics significantly.

Developing a topic model from the ground up requires a high level of programming skill. This specialized knowledge can be costly and often overshadows the essential understanding of the data itself. The process of manually labeling your training data is not only time-consuming but also labor-intensive and expensive. Outsourcing this task to low-wage workers may expedite the process and reduce costs, yet it often sacrifices both accuracy and detail. Each of these methods results in a static taxonomy that can be challenging to adapt over time. It's crucial to transition away from mere tagging and empower subject matter experts to engage with their data for modeling and analysis. With vast amounts of text data at your disposal, brimming with insights ready for exploration, the need for effective tools becomes clear. Pienso is here to assist with this challenge by enabling you to train models using your own data, as we recognize that this approach yields the best results. Regardless of whether your data is unstructured, semi-structured, lengthy, or concise, Pienso is equipped to help you transform it into valuable insights that can drive decision-making. By leveraging Pienso, you can unlock the full potential of your data without the traditional hurdles associated with topic modeling.

Analytic Partners offers a comprehensive commercial analytics solution known as GPS Enterprise (GPS‑E), which seamlessly combines marketing, sales, financial, operational, and external datasets to create a thorough and practical understanding of business performance. This platform is powered by a unique intelligence layer called ROI Genome, leveraging over 25 years of expertise in cross-industry data and analytics to identify the fundamental factors driving growth while also revealing revenue potentials that extend beyond traditional marketing efforts. With GPS-E, organizations can develop continuously adaptive models that surpass conventional Marketing Mix Modeling (MMM) by factoring in non-marketing elements like competitive actions, consumer behaviors, macroeconomic influences, and operational factors, acknowledging that a significant proportion of growth often originates from areas beyond mere advertising expenditure. Additionally, it includes an efficient data orchestration feature named ADAPTA, which facilitates the automation of data collection, validation, and standardization across various agencies and business units, enhancing consistency and accuracy in analytics. This innovative approach empowers companies to make data-driven decisions that are not only informed by marketing but also by a broader spectrum of business dynamics.

We are excited to introduce Jurassic-2, the newest iteration of AI21 Studio's foundation models, which represents a major advancement in artificial intelligence, boasting exceptional quality and innovative features. In addition to this, we are unveiling our tailored APIs that offer seamless reading and writing functionalities, surpassing those of our rivals. At AI21 Studio, our mission is to empower developers and businesses to harness the potential of reading and writing AI, facilitating the creation of impactful real-world applications. Today signifies a pivotal moment with the launch of Jurassic-2 and our Task-Specific APIs, enabling you to effectively implement generative AI in production settings. Known informally as J2, Jurassic-2 showcases remarkable enhancements in quality, including advanced zero-shot instruction-following, minimized latency, and support for multiple languages. Furthermore, our specialized APIs are designed to provide developers with top-tier tools that excel in executing specific reading and writing tasks effortlessly, ensuring you have everything needed to succeed in your projects. Together, these advancements set a new standard in the AI landscape, paving the way for innovative solutions.

Aware converts digital conversation data from platforms such as Slack, Teams, and Zoom into immediate insights that reveal potential risks and enhance organizational intelligence on a large scale. These digital interactions permeate every aspect of your organization; modern teamwork relies heavily on real-time collaboration, making the social connections among employees one of the fastest-growing data sources in your business. This unstructured data features its own unique language and emotional undertones, with genuine and spontaneous messages often consisting of five words or fewer. Users frequently communicate using emojis, abbreviations, and multimedia elements across various private, direct, and public channels on multiple collaboration platforms. Conventional technology struggles to grasp the context and subtleties inherent in this dataset and its distinctive behaviors. By interpreting this complex information, Aware identifies hidden, costly risks and uncovers insights that can drive innovation and enhance business value. Ultimately, Aware delivers contextual intelligence tailored to your organization’s needs, facilitating growth at scale while ensuring that no valuable insight goes unnoticed.

LFM2 represents an advanced series of on-device foundation models designed to provide a remarkably swift generative-AI experience across a diverse array of devices. By utilizing a novel hybrid architecture, it achieves decoding and pre-filling speeds that are up to twice as fast as those of similar models, while also enhancing training efficiency by as much as three times compared to its predecessor. These models offer a perfect equilibrium of quality, latency, and memory utilization suitable for embedded system deployment, facilitating real-time, on-device AI functionality in smartphones, laptops, vehicles, wearables, and various other platforms, which results in millisecond inference, device durability, and complete data sovereignty. LFM2 is offered in three configurations featuring 0.35 billion, 0.7 billion, and 1.2 billion parameters, showcasing benchmark results that surpass similarly scaled models in areas including knowledge recall, mathematics, multilingual instruction adherence, and conversational dialogue assessments. With these capabilities, LFM2 not only enhances user experience but also sets a new standard for on-device AI performance.

DNIF offers a highly valuable solution by integrating SIEM, UEBA, and SOAR technologies into a single product, all while maintaining an impressively low total cost of ownership. The platform's hyper-scalable data lake is perfectly suited for the ingestion and storage of vast amounts of data, enabling users to identify suspicious activities through statistical analysis and take proactive measures to mitigate potential harm. It allows for the orchestration of processes, personnel, and technological initiatives from a unified security dashboard. Furthermore, your SIEM comes equipped with vital dashboards, reports, and response workflows out of the box, ensuring comprehensive coverage for threat hunting, compliance, user behavior tracking, and network traffic anomalies. The inclusion of a detailed coverage map aligned with the MITRE ATT&CK and CAPEC frameworks enhances its effectiveness even further. Expand your logging capabilities without the stress of exceeding your budget—potentially doubling or even tripling your capacity within the same financial constraints. Thanks to HYPERCLOUD, the anxiety of missing out on critical information is now a relic of the past, as you can log everything and ensure nothing goes unnoticed, solidifying your security posture.

Gemini 2.5 Flash is a high-performance AI model developed by Google to meet the needs of businesses requiring low-latency responses and cost-effective processing. It is optimized for real-time applications like customer support and virtual assistants, where responsiveness is crucial. Gemini 2.5 Flash features dynamic reasoning, which allows businesses to fine-tune the model's speed and accuracy to meet specific needs. By adjusting the "thinking budget" for each query, it helps companies achieve optimal performance without sacrificing quality.

NLWeb is a collaborative initiative by Microsoft designed to facilitate the creation of an intuitive, natural language interface for websites, utilizing any chosen model alongside proprietary data. The primary objective of NLWeb, which stands for Natural Language Web, is to provide the quickest and simplest means of transforming a website into an AI application, enabling users to interact with the site's content through natural language queries, akin to engaging with an AI assistant or Copilot. Each instance of NLWeb functions as a Model Context Protocol (MCP) server, giving websites the option to make their information discoverable and accessible to various agents and participants within the MCP framework. By leveraging semi-structured data formats such as Schema.org and RSS, which many websites already employ, NLWeb integrates these with LLM-powered tools to facilitate natural language interfaces that cater to both humans and AI agents, ultimately enhancing user interaction and engagement. This innovative approach not only streamlines the integration process but also broadens the accessibility of web content for a diverse audience.

Dimension Labs provides a cutting-edge platform for customer observability and language data infrastructure that transforms unstructured conversational data from various channels such as chat, email, voice, surveys, and social media into structured insights ready for analytics. By leveraging AI-driven enrichment and dynamic labeling, it removes the necessity for manual tagging, effectively highlighting changing themes, customer sentiments, reasons for escalations, and requests for features. This platform consolidates inputs from multiple channels under a unified model, offering real-time dashboards, drill-down features, and context-aware analytics, which enables teams to investigate root causes, track emerging trends, and link conversation metrics to overall business results. Furthermore, Dimension Labs facilitates integration through APIs or one-click connectors with a variety of tools, including chat applications, CRMs, contact centers, survey systems, and social media platforms, ensuring effortless data ingestion from sources like Intercom, Twilio, and Slack. As a result, organizations can gain deeper insights into customer interactions and enhance their decision-making processes.

Mistral Medium 3 is an innovative AI model designed to offer high performance at a significantly lower cost, making it an attractive solution for enterprises. It integrates seamlessly with both on-premises and cloud environments, supporting hybrid deployments for more flexibility. This model stands out in professional use cases such as coding, STEM tasks, and multimodal understanding, where it achieves near-competitive results against larger, more expensive models. Additionally, Mistral Medium 3 allows businesses to deploy custom post-training and integrate it into existing systems, making it adaptable to various industry needs. With its impressive performance in coding tasks and real-world human evaluations, Mistral Medium 3 is a cost-effective solution that enables companies to implement AI into their workflows. Its enterprise-focused features, including continuous pretraining and domain-specific fine-tuning, make it a reliable tool for sectors like healthcare, financial services, and energy.

Lyric serves as a comprehensive, four-tiered platform for supply chain decision intelligence, allowing organizations to effectively model, plan, and operate their supply chains swiftly. Its foundational data layer ensures robust enterprise-level data management, featuring prebuilt integrations and advanced transformation abilities that facilitate effortless scalability. Meanwhile, the algorithms layer comes equipped with ready-to-use engines designed to model and enhance networks, transportation, and inventory management, while also providing a flexible modeling environment where analysts can merge data, expand scientific insights, and create personalized user interfaces. Users can harness the workflows layer to innovate and streamline their operations through pre-designed applications, customizable processes, and adaptable science-as-a-service integrations that can be seamlessly integrated with existing systems. Lastly, the models & apps layer promotes efficient planning and execution by democratizing access to decision science, presenting tools for forecasting, routing, scheduling, and forensics in formats that are easily understood, thus fostering ongoing enhancement in supply chain performance. This holistic approach positions Lyric as a vital asset for organizations aiming to thrive in an ever-evolving business landscape.

Langtail is a cloud-based development tool designed to streamline the debugging, testing, deployment, and monitoring of LLM-powered applications. The platform provides a no-code interface for debugging prompts, adjusting model parameters, and conducting thorough LLM tests to prevent unexpected behavior when prompts or models are updated. Langtail is tailored for LLM testing, including chatbot evaluations and ensuring reliable AI test prompts. Key features of Langtail allow teams to: • Perform in-depth testing of LLM models to identify and resolve issues before production deployment. • Easily deploy prompts as API endpoints for smooth integration into workflows. • Track model performance in real-time to maintain consistent results in production environments. • Implement advanced AI firewall functionality to control and protect AI interactions. Langtail is the go-to solution for teams aiming to maintain the quality, reliability, and security of their AI and LLM-based applications.

Vectara offers LLM-powered search as-a-service. The platform offers a complete ML search process, from extraction and indexing to retrieval and re-ranking as well as calibration. API-addressable for every element of the platform. Developers can embed the most advanced NLP model for site and app search in minutes. Vectara automatically extracts text form PDF and Office to JSON HTML XML CommonMark, and many other formats. Use cutting-edge zero-shot models that use deep neural networks to understand language to encode at scale. Segment data into any number indexes that store vector encodings optimized to low latency and high recall. Use cutting-edge, zero shot neural network models to recall candidate results from millions upon millions of documents. Cross-attentional neural networks can increase the precision of retrieved answers. They can merge and reorder results. Focus on the likelihood that the retrieved answer is a probable answer to your query.

The Nemotron 3 Nano stands out as the tiniest model within NVIDIA's Nemotron 3 lineup, specifically designed for agentic AI tasks that require robust reasoning and conversational skills while maintaining cost-effective inference. This hybrid Mamba-Transformer Mixture-of-Experts model boasts 3.2 billion active parameters, 3.6 billion when including embeddings, and a total of 31.6 billion parameters. NVIDIA asserts that this model offers greater accuracy compared to its predecessor, the Nemotron 2 Nano, all while utilizing less than half of the parameters during each forward pass, thus enhancing efficiency without compromising on performance. It is also claimed to surpass the accuracy of both GPT-OSS-20B and Qwen3-30B-A3B-Thinking-2507 across various widely-used benchmarks. With an 8K input and 16K output setting utilizing a single H200, the model achieves an inference throughput that is 3.3 times greater than that of Qwen3-30B-A3B and 2.2 times that of GPT-OSS-20B. Additionally, the Nemotron 3 Nano is capable of handling context lengths of up to 1 million tokens, further establishing its superiority over GPT-OSS-20B and Qwen3-30B-A3B-Instruct-2507. This remarkable combination of features positions it as a leading choice for advanced AI applications that demand both precision and efficiency.

NVIDIA's Isaac GR00T (Generalist Robot 00 Technology) serves as an innovative research platform aimed at the creation of versatile humanoid robot foundation models and their associated data pipelines. This platform features models such as Isaac GR00T-N, alongside synthetic motion blueprints, GR00T-Mimic for enhancing demonstrations, and GR00T-Dreams, which generates novel synthetic trajectories to expedite the progress in humanoid robotics. A recent highlight is the introduction of the open-source Isaac GR00T N1 foundation model, characterized by a dual-system cognitive structure that includes a rapid-response “System 1” action model and a language-capable, deliberative “System 2” reasoning model. The latest iteration, GR00T N1.5, brings forth significant upgrades, including enhanced vision-language grounding, improved following of language commands, increased adaptability with few-shot learning, and support for new robot embodiments. With the integration of tools like Isaac Sim, Lab, and Omniverse, GR00T enables developers to effectively train, simulate, post-train, and deploy adaptable humanoid agents utilizing a blend of real and synthetic data. This comprehensive approach not only accelerates robotics research but also opens up new avenues for innovation in humanoid robot applications.