Alternatives to SiaSearch

BigQuery is a serverless, multicloud data warehouse that makes working with all types of data effortless, allowing you to focus on extracting valuable business insights quickly. As a central component of Google’s data cloud, it streamlines data integration, enables cost-effective and secure scaling of analytics, and offers built-in business intelligence for sharing detailed data insights. With a simple SQL interface, it also supports training and deploying machine learning models, helping to foster data-driven decision-making across your organization. Its robust performance ensures that businesses can handle increasing data volumes with minimal effort, scaling to meet the needs of growing enterprises. Gemini within BigQuery brings AI-powered tools that enhance collaboration and productivity, such as code recommendations, visual data preparation, and intelligent suggestions aimed at improving efficiency and lowering costs. The platform offers an all-in-one environment with SQL, a notebook, and a natural language-based canvas interface, catering to data professionals of all skill levels. This cohesive workspace simplifies the entire analytics journey, enabling teams to work faster and more efficiently.

dbt Labs is redefining how data teams work with SQL. Instead of waiting on complex ETL processes, dbt lets data analysts and data engineers build production-ready transformations directly in the warehouse, using code, version control, and CI/CD. This community-driven approach puts power back in the hands of practitioners while maintaining governance and scalability for enterprise use. With a rapidly growing open-source community and an enterprise-grade cloud platform, dbt is at the heart of the modern data stack. It’s the go-to solution for teams who want faster analytics, higher quality data, and the confidence that comes from transparent, testable transformations.

Accelerate your data journey with AnalyticsCreator—a metadata-driven data warehouse automation solution purpose-built for the Microsoft data ecosystem. AnalyticsCreator simplifies the design, development, and deployment of modern data architectures, including dimensional models, data marts, data vaults, or blended modeling approaches tailored to your business needs. Seamlessly integrate with Microsoft SQL Server, Azure Synapse Analytics, Microsoft Fabric (including OneLake and SQL Endpoint Lakehouse environments), and Power BI. AnalyticsCreator automates ELT pipeline creation, data modeling, historization, and semantic layer generation—helping reduce tool sprawl and minimizing manual SQL coding. Designed to support CI/CD pipelines, AnalyticsCreator connects easily with Azure DevOps and GitHub for version-controlled deployments across development, test, and production environments. This ensures faster, error-free releases while maintaining governance and control across your entire data engineering workflow. Key features include automated documentation, end-to-end data lineage tracking, and adaptive schema evolution—enabling teams to manage change, reduce risk, and maintain auditability at scale. AnalyticsCreator empowers agile data engineering by enabling rapid prototyping and production-grade deployments for Microsoft-centric data initiatives. By eliminating repetitive manual tasks and deployment risks, AnalyticsCreator allows your team to focus on delivering actionable business insights—accelerating time-to-value for your data products and analytics initiatives.

It takes only days to wrap any data source with a single reference Data API and simplify access to reporting and analytics data across your teams. Make it easy for application developers and data engineers to access the data from any source in a streamlined manner. - The single schema-less Data API endpoint - Review, configure metrics and dimensions in one place via UI - Data model visualization to make faster decisions - Data Export management scheduling API Our proxy perfectly fits into your current API management ecosystem (versioning, data access, discovery) no matter if you are using Mulesoft, Apigee, Tyk, or your homegrown solution. Leverage the capabilities of Data API and enrich your products with self-service analytics for dashboards, data Exports, or custom report composer for ad-hoc metric querying. Ready-to-use Report Builder and JavaScript components for popular charting libraries (Highcharts, BizCharts, Chart.js, etc.) makes it easy to embed data-rich functionality into your products. Your product or service users will love that because everybody likes to make data-driven decisions! And you will not have to make custom report queries anymore!

Harness the power of AutoML Vision or leverage pre-trained Vision API models to extract meaningful insights from images stored in the cloud or at the network's edge, allowing for emotion detection, text interpretation, and much more. Google Cloud presents two advanced computer vision solutions that utilize machine learning to provide top-notch prediction accuracy for image analysis. You can streamline the creation of bespoke machine learning models by simply uploading your images, using AutoML Vision's intuitive graphical interface to train these models, and fine-tuning them for optimal performance in terms of accuracy, latency, and size. Once perfected, these models can be seamlessly exported for use in cloud applications or on various edge devices. Additionally, Google Cloud’s Vision API grants access to robust pre-trained machine learning models via REST and RPC APIs. You can easily assign labels to images, categorize them into millions of pre-existing classifications, identify objects and faces, interpret both printed and handwritten text, and enhance your image catalog with rich metadata for deeper insights. This combination of tools not only simplifies the image analysis process but also empowers businesses to make data-driven decisions more effectively.

A visual inspection platform that manages data, speeds troubleshooting, scales deployment, and more. LandingLens is an AI visual inspection platform that works for businesses. Your labeling process is faster by as much as half and model deployment times by up to 67%. You can manage a few thousand to thousands of models using very little resources. Smart labeling and data generation improve the accuracy of your machine-learning models. You can track and manage the efficiency and current data assets of AI projects and deploy solutions across all company sites. Alerts you when the model drifts. You can easily update and adjust your solutions without having to rely on a third-party AI team. Allow manufacturers to develop, deploy, manage and monitor industrial AI projects using a single integrated platform.

Fivetran is a comprehensive data integration solution designed to centralize and streamline data movement for organizations of all sizes. With more than 700 pre-built connectors, it effortlessly transfers data from SaaS apps, databases, ERPs, and files into data warehouses and lakes, enabling real-time analytics and AI-driven insights. The platform’s scalable pipelines automatically adapt to growing data volumes and business complexity. Leading companies such as Dropbox, JetBlue, Pfizer, and National Australia Bank rely on Fivetran to reduce data ingestion time from weeks to minutes and improve operational efficiency. Fivetran offers strong security compliance with certifications including SOC 1 & 2, GDPR, HIPAA, ISO 27001, PCI DSS, and HITRUST. Users can programmatically create and manage pipelines through its REST API for seamless extensibility. The platform supports governance features like role-based access controls and integrates with transformation tools like dbt Labs. Fivetran helps organizations innovate by providing reliable, secure, and automated data pipelines tailored to their evolving needs.

At Vaex.io, our mission is to make big data accessible to everyone, regardless of the machine or scale they are using. By reducing development time by 80%, we transform prototypes directly into solutions. Our platform allows for the creation of automated pipelines for any model, significantly empowering data scientists in their work. With our technology, any standard laptop can function as a powerful big data tool, eliminating the need for clusters or specialized engineers. We deliver dependable and swift data-driven solutions that stand out in the market. Our cutting-edge technology enables the rapid building and deployment of machine learning models, outpacing competitors. We also facilitate the transformation of your data scientists into proficient big data engineers through extensive employee training, ensuring that you maximize the benefits of our solutions. Our system utilizes memory mapping, an advanced expression framework, and efficient out-of-core algorithms, enabling users to visualize and analyze extensive datasets while constructing machine learning models on a single machine. This holistic approach not only enhances productivity but also fosters innovation within your organization.

Delta Lake serves as an open-source storage layer that integrates ACID transactions into Apache Spark™ and big data operations. In typical data lakes, multiple pipelines operate simultaneously to read and write data, which often forces data engineers to engage in a complex and time-consuming effort to maintain data integrity because transactional capabilities are absent. By incorporating ACID transactions, Delta Lake enhances data lakes and ensures a high level of consistency with its serializability feature, the most robust isolation level available. For further insights, refer to Diving into Delta Lake: Unpacking the Transaction Log. In the realm of big data, even metadata can reach substantial sizes, and Delta Lake manages metadata with the same significance as the actual data, utilizing Spark's distributed processing strengths for efficient handling. Consequently, Delta Lake is capable of managing massive tables that can scale to petabytes, containing billions of partitions and files without difficulty. Additionally, Delta Lake offers data snapshots, which allow developers to retrieve and revert to previous data versions, facilitating audits, rollbacks, or the replication of experiments while ensuring data reliability and consistency across the board.

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.

Dremio provides lightning-fast queries as well as a self-service semantic layer directly to your data lake storage. No data moving to proprietary data warehouses, and no cubes, aggregation tables, or extracts. Data architects have flexibility and control, while data consumers have self-service. Apache Arrow and Dremio technologies such as Data Reflections, Columnar Cloud Cache(C3), and Predictive Pipelining combine to make it easy to query your data lake storage. An abstraction layer allows IT to apply security and business meaning while allowing analysts and data scientists access data to explore it and create new virtual datasets. Dremio's semantic layers is an integrated searchable catalog that indexes all your metadata so business users can make sense of your data. The semantic layer is made up of virtual datasets and spaces, which are all searchable and indexed.

Clarifai is a leading AI platform for modeling image, video, text and audio data at scale. Our platform combines computer vision, natural language processing and audio recognition as building blocks for building better, faster and stronger AI. We help enterprises and public sector organizations transform their data into actionable insights. Our technology is used across many industries including Defense, Retail, Manufacturing, Media and Entertainment, and more. We help our customers create innovative AI solutions for visual search, content moderation, aerial surveillance, visual inspection, intelligent document analysis, and more. Founded in 2013 by Matt Zeiler, Ph.D., Clarifai has been a market leader in computer vision AI since winning the top five places in image classification at the 2013 ImageNet Challenge. Clarifai is headquartered in Delaware

Our Industrial AI platform adopts a data science-centric approach, providing applications that are seamlessly built upon our robust industrial AI and IoT infrastructure. By leveraging advanced AI and machine learning algorithms alongside pre-trained data science models and tailored industry content, we transform vast amounts of data into meaningful insights. Talpacortex stands out as a dependable device for positioning and data processing in industrial settings, offering a range of customizable options. Its installation process is straightforward, allowing it to connect effortlessly to a variety of vehicles and industrial systems. Furthermore, Talpacortex features a GNSS module that can be upgraded to RTK when a fixed base station is present. Data transfer is facilitated through 3G/4G or WLAN connections, ensuring reliable communication. On request, machine-to-machine (M2M) capabilities are available to enhance connectivity. An integrated processing unit simplifies web-based management via the service interface, while multiple CAN bus interfaces enable quick and effective machine integration, including support for embedded sensors and retrofitting. This versatility positions Talpacortex as an essential tool for modern industrial operations, enhancing efficiency and data utilization across the board.

Effortlessly monitor thousands of tables through machine learning-driven anomaly detection alongside a suite of over 50 tailored metrics. Ensure comprehensive oversight of both data and metadata while meticulously mapping all asset dependencies from ingestion to business intelligence. This solution enhances productivity and fosters collaboration between data engineers and consumers. Sifflet integrates smoothly with your existing data sources and tools, functioning on platforms like AWS, Google Cloud Platform, and Microsoft Azure. Maintain vigilance over your data's health and promptly notify your team when quality standards are not satisfied. With just a few clicks, you can establish essential coverage for all your tables. Additionally, you can customize the frequency of checks, their importance, and specific notifications simultaneously. Utilize machine learning-driven protocols to identify any data anomalies with no initial setup required. Every rule is supported by a unique model that adapts based on historical data and user input. You can also enhance automated processes by utilizing a library of over 50 templates applicable to any asset, thereby streamlining your monitoring efforts even further. This approach not only simplifies data management but also empowers teams to respond proactively to potential issues.

Imubit’s artificial intelligence platform provides instantaneous, closed-loop optimization of processes in heavy industries by integrating a dynamic process simulator, a reinforcement-learning neural controller, and performance monitoring dashboards. The dynamic simulator utilizes extensive historical plant data and is informed by fundamental principles to create a virtual representation of actual processes, facilitating what-if analyses regarding variable interactions, changes in constraints, and adjustments in operational strategies. Meanwhile, the reinforcement-learning controller, which has been trained offline using millions of trial-and-error scenarios, is employed to continuously optimize control variables, thereby enhancing profit margins while adhering to safety constraints. Real-time dashboards monitor the availability of the model, user engagement, and operational uptime, while also providing interactive visual representations of boundary conditions, operational limits, and trends in key performance indicators. Applications of this technology include synchronizing economic strategies with real-time operational data and identifying instances of process deterioration, ensuring enhanced efficiency and safety across operations. This comprehensive approach empowers industries to adapt swiftly and effectively to changing conditions.

The machine learning platform designed to integrate data and streamline intelligent actions across teams focused on revenue generation offers seamless attribution and actionable insights. QFlow.ai efficiently handles the vast amounts of data collected in the activity table of your Salesforce.com account. By normalizing, trending, and analyzing sales efforts, it empowers you to create more opportunities and successfully close more deals. Utilizing advanced data engineering, QFlow.ai dissects outbound activity reporting by evaluating a key aspect: the productivity of those activities. Additionally, it automatically highlights essential metrics, such as the average time from the initial activity to opportunity creation and the average duration from opportunity creation to closing. Users can filter sales effort data by team or individual, allowing for a comprehensive understanding of sales activities and productivity patterns over time, leading to enhanced strategic decision-making. This level of insight can be instrumental in refining sales strategies and driving improved performance.

Lightly intelligently identifies the most impactful subset of your data, enhancing model accuracy through iterative improvements by leveraging the finest data for retraining. By minimizing data redundancy and bias while concentrating on edge cases, you can maximize the efficiency of your data. Lightly's algorithms can efficiently handle substantial datasets in under 24 hours. Easily connect Lightly to your existing cloud storage solutions to automate the processing of new data seamlessly. With our API, you can fully automate the data selection workflow. Experience cutting-edge active learning algorithms that combine both active and self-supervised techniques for optimal data selection. By utilizing a blend of model predictions, embeddings, and relevant metadata, you can achieve your ideal data distribution. Gain deeper insights into your data distribution, biases, and edge cases to further refine your model. Additionally, you can manage data curation efforts while monitoring new data for labeling and subsequent model training. Installation is straightforward through a Docker image, and thanks to cloud storage integration, your data remains secure within your infrastructure, ensuring privacy and control. This approach allows for a holistic view of data management, making it easier to adapt to evolving modeling needs.

A platform designed for ML engineers that generates synthetic data, facilitating the creation of more advanced AI models. With straightforward APIs, users can quickly generate a wide variety of perfectly-labeled, photorealistic images as needed. This highly scalable, cloud-based system can produce millions of accurately labeled images, allowing for innovative data-centric strategies that improve model performance. The platform offers an extensive range of pixel-perfect labels, including segmentation maps, dense 2D and 3D landmarks, depth maps, and surface normals, among others. This capability enables rapid design, testing, and refinement of products prior to hardware implementation. Additionally, it allows for prototyping with various imaging techniques, camera positions, and lens types to fine-tune system performance. By minimizing biases linked to imbalanced datasets while ensuring privacy, the platform promotes fair representation across diverse identities, facial features, poses, camera angles, lighting conditions, and more. Collaborating with leading customers across various applications, our platform continues to push the boundaries of AI development. Ultimately, it serves as a pivotal resource for engineers seeking to enhance their models and innovate in the field.

Visual Layer is a production-grade platform built for teams handling image and video datasets at scale. It enables direct interaction with visual data—searching, filtering, labeling, and analyzing—without needing custom scripts or manual sorting. Originally developed by the creators of Fastdup, it extends the same deduplication capabilities into full dataset workflows. Designed to be infrastructure-agnostic, Visual Layer can run entirely on-premise, in the cloud, or embedded via API. It's model-agnostic too, making it useful for debugging, cleaning, or pretraining tasks in any ML pipeline. The system flags anomalies, catch mislabeled frames, and surfaces diverse subsets to improve generalization and reduce noise. It fits into existing pipelines without requiring migration or vendor lock-in, and supports engineers and ops teams alike.

ClearML is an open-source MLOps platform that enables data scientists, ML engineers, and DevOps to easily create, orchestrate and automate ML processes at scale. Our frictionless and unified end-to-end MLOps Suite allows users and customers to concentrate on developing ML code and automating their workflows. ClearML is used to develop a highly reproducible process for end-to-end AI models lifecycles by more than 1,300 enterprises, from product feature discovery to model deployment and production monitoring. You can use all of our modules to create a complete ecosystem, or you can plug in your existing tools and start using them. ClearML is trusted worldwide by more than 150,000 Data Scientists, Data Engineers and ML Engineers at Fortune 500 companies, enterprises and innovative start-ups.

Synetic AI is an innovative platform designed to speed up the development and implementation of practical computer vision models by automatically creating highly realistic synthetic training datasets with meticulous annotations, eliminating the need for manual labeling altogether. Utilizing sophisticated physics-based rendering and simulation techniques, it bridges the gap between synthetic and real-world data, resulting in enhanced model performance. Research has shown that its synthetic data consistently surpasses real-world datasets by an impressive average of 34% in terms of generalization and recall. This platform accommodates an infinite array of variations—including different lighting, weather conditions, camera perspectives, and edge cases—while providing extensive metadata, thorough annotations, and support for multi-modal sensors. This capability allows teams to quickly iterate and train their models more efficiently and cost-effectively compared to conventional methods. Furthermore, Synetic AI is compatible with standard architectures and export formats, manages edge deployment and monitoring, and can produce complete datasets within about a week, along with custom-trained models ready in just a few weeks, ensuring rapid delivery and adaptability to various project needs. Overall, Synetic AI stands out as a game-changer in the realm of computer vision, revolutionizing how synthetic data is leveraged to enhance model accuracy and efficiency.

We make BI and Big Data analytics easier and more efficient. Our goal is to empower business users, make BI specialists and always-busy business more independent when solving data-driven business problems. Querona is a solution for those who have ever been frustrated by a lack in data, slow or tedious report generation, or a long queue to their BI specialist. Querona has a built-in Big Data engine that can handle increasing data volumes. Repeatable queries can be stored and calculated in advance. Querona automatically suggests improvements to queries, making optimization easier. Querona empowers data scientists and business analysts by giving them self-service. They can quickly create and prototype data models, add data sources, optimize queries, and dig into raw data. It is possible to use less IT. Users can now access live data regardless of where it is stored. Querona can cache data if databases are too busy to query live.

Connecting every data source with analytics services on a single AI-powered platform will transform how people access, manage, and act on data and insights. All your data. All your teams. All your teams in one place. Create an open, lake-centric hub to help data engineers connect data from various sources and curate it. This will eliminate sprawl and create custom views for all. Accelerate analysis through the development of AI models without moving data. This reduces the time needed by data scientists to deliver value. Microsoft Teams, Microsoft Excel, and Microsoft Teams are all great tools to help your team innovate faster. Connect people and data responsibly with an open, scalable solution. This solution gives data stewards more control, thanks to its built-in security, compliance, and governance.

SKY ENGINE AI provides a unified Synthetic Data Cloud designed to power next-generation Vision AI training with photorealistic 3D generative scenes. Its engine simulates multispectral environments—including visible light, thermal, NIR, and UWB—while producing detailed semantic masks, bounding boxes, depth maps, and metadata. The platform features domain processors, GAN-based adaptation, and domain-gap inspection tools to ensure synthetic datasets closely match real-world distributions. Data scientists work efficiently through an integrated coding environment with deep PyTorch/TensorFlow integration and seamless MLOps compatibility. For large-scale production, SKY ENGINE AI offers distributed rendering clusters, cloud instance orchestration, automated randomization, and reusable 3D scene blueprints for automotive, robotics, security, agriculture, and manufacturing. Users can run continuous data iteration cycles to cover edge cases, detect model blind spots, and refine training sets in minutes instead of months. With support for CGI standards, physics-based shaders, and multimodal sensor simulation, the platform enables highly customizable Vision AI pipelines. This end-to-end approach reduces operational costs, accelerates development, and delivers consistently high-performance models.

FlowFuse is an advanced industrial application software that leverages Node-RED to enable teams to seamlessly integrate machines and protocols, gather and model data, and manage applications on a large scale, all while incorporating AI-driven support to streamline both development and deployment processes. By enhancing the user-friendly low-code, visual programming capabilities of Node-RED, FlowFuse introduces enterprise-level functionalities such as secure device communication, comprehensive operational management, centralized remote deployment options, collaborative team features, and extensive security measures. The solution also boasts interactive and adaptive dashboards, AI-supported flow creation and improvement aids, and tools for converting unprocessed data into structured models using natural language inputs. Furthermore, it incorporates DevOps-style pipelines for effective management of staged environments and version control, allows for remote fleet management via a device agent, and provides sophisticated observability features to ensure performance monitoring across multiple instances. This combination of capabilities positions FlowFuse as a powerful tool for optimizing industrial operations and accelerating innovation.

AUTOSOL’s software solution is crafted to integrate industrial data communications by securely gathering, accessing, and distributing real-time, historical, and edge data from various industrial devices and control systems into a cohesive, actionable information stream. At its heart lies the AUTOSOL Communication Manager, a sophisticated multi-protocol polling engine and OPC server that interfaces with an array of field devices like RTUs, PLCs, and meters using their original protocols, subsequently providing standardized data to SCADA systems, HMIs, databases, and analytic tools for improved operational oversight and management. This platform is capable of supporting multiple telemetry types at the same time while effectively bridging the gap between legacy systems and modern IIoT devices, which allows organizations to prolong the usability of their existing infrastructure while integrating new technologies for enhanced operational efficiency. By leveraging such advanced capabilities, businesses can ensure a smoother transition into the digital age of industry.

The Archon Data Store™ is a robust and secure platform built on open-source principles, tailored for archiving and managing extensive data lakes. Its compliance capabilities and small footprint facilitate large-scale data search, processing, and analysis across structured, unstructured, and semi-structured data within an organization. By merging the essential characteristics of both data warehouses and data lakes, Archon Data Store creates a seamless and efficient platform. This integration effectively breaks down data silos, enhancing data engineering, analytics, data science, and machine learning workflows. With its focus on centralized metadata, optimized storage solutions, and distributed computing, the Archon Data Store ensures the preservation of data integrity. Additionally, its cohesive strategies for data management, security, and governance empower organizations to operate more effectively and foster innovation at a quicker pace. By offering a singular platform for both archiving and analyzing all organizational data, Archon Data Store not only delivers significant operational efficiencies but also positions your organization for future growth and agility.

alwaysAI offers a straightforward and adaptable platform for developers to create, train, and deploy computer vision applications across a diverse range of IoT devices. You can choose from an extensive library of deep learning models or upload your custom models as needed. Our versatile and customizable APIs facilitate the rapid implementation of essential computer vision functionalities. You have the capability to quickly prototype, evaluate, and refine your projects using an array of camera-enabled ARM-32, ARM-64, and x86 devices. Recognize objects in images by their labels or classifications, and identify and count them in real-time video streams. Track the same object through multiple frames, or detect faces and entire bodies within a scene for counting or tracking purposes. You can also outline and define boundaries around distinct objects, differentiate essential elements in an image from the background, and assess human poses, fall incidents, and emotional expressions. Utilize our model training toolkit to develop an object detection model aimed at recognizing virtually any object, allowing you to create a model specifically designed for your unique requirements. With these powerful tools at your disposal, you can revolutionize the way you approach computer vision projects.

Qwen2.5-VL marks the latest iteration in the Qwen vision-language model series, showcasing notable improvements compared to its predecessor, Qwen2-VL. This advanced model demonstrates exceptional capabilities in visual comprehension, adept at identifying a diverse range of objects such as text, charts, and various graphical elements within images. Functioning as an interactive visual agent, it can reason and effectively manipulate tools, making it suitable for applications involving both computer and mobile device interactions. Furthermore, Qwen2.5-VL is proficient in analyzing videos that are longer than one hour, enabling it to identify pertinent segments within those videos. The model also excels at accurately locating objects in images by creating bounding boxes or point annotations and supplies well-structured JSON outputs for coordinates and attributes. It provides structured data outputs for documents like scanned invoices, forms, and tables, which is particularly advantageous for industries such as finance and commerce. Offered in both base and instruct configurations across 3B, 7B, and 72B models, Qwen2.5-VL can be found on platforms like Hugging Face and ModelScope, further enhancing its accessibility for developers and researchers alike. This model not only elevates the capabilities of vision-language processing but also sets a new standard for future developments in the field.

Founded in 2018, Pecan is a predictive analytics platform that leverages its pioneering Predictive GenAI to remove barriers to AI adoption, making predictive modeling accessible to all data and business teams. Guided by generative AI, companies can obtain precise predictions across various business domains without the need for specialized personnel. Predictive GenAI enables rapid model definition and training, while automated processes accelerate AI implementation. With Pecan's fusion of predictive and generative AI, realizing the business impact of AI is now far faster and easier.

Canvass AI provides solutions that enable every team to tackle their current challenges effectively. The integrated AI consistently gathers data along with users' experiential insights to enhance decision-making and extend its benefits to additional assets. With modular solutions that offer a validated path for adoption, teams can implement, thrive, and expand AI from a single asset to the entire facility. By facilitating the extraction of value from data, Canvass AI allows process engineers to achieve a more profound comprehension of their processes, spanning historical, present, and future states. This approach streamlines problem-solving, equipping engineers with the tools for quicker and more impactful decisions that aid in complex troubleshooting, seize daily opportunities, and navigate both current and future challenges. Furthermore, Canvass AI transforms the journey from data to insights, empowering industrial engineers and operators to make informed decisions that enhance the profitability, health, and resilience of operations, ultimately fostering a culture of continuous improvement and innovation.

Whether your data exists in isolated environments or is being produced at the edge, Sentrana offers you the versatility to establish AI and data engineering pipelines wherever your information resides. Furthermore, you can easily share your AI, data, and pipelines with anyone, regardless of their location. With Sentrana, you gain unparalleled agility to transition seamlessly between various computing environments, all while ensuring that your data and projects automatically replicate to your desired destinations. The platform features an extensive collection of components that allow you to craft personalized AI and data engineering pipelines. You can quickly assemble and evaluate numerous pipeline configurations to develop the AI solutions you require. Transforming your data into AI becomes a straightforward task, incurring minimal effort and expense. As Sentrana operates as an open platform, you have immediate access to innovative AI components that are continually being developed. Moreover, Sentrana converts the pipelines and AI models you build into reusable blocks, enabling any member of your team to integrate them into their own projects with ease. This collaborative capability not only enhances productivity but also fosters creativity across your organization.

Engineering teams turn to Instrumental to accelerate their product launches while minimizing quality concerns. This platform offers AI-driven proactive defect detection, comprehensive failure analysis tools, and remote real-time monitoring of builds, all integrated into a straightforward cloud solution. With Instrumental, you gain a cohesive and traceable data history that aids in identifying and addressing problems from the onset of your earliest EVT builds. By consolidating your product data, you can act swiftly and utilize AI to tackle issues that were once deemed too complex to resolve on your production line. The platform ensures that your product data is streamlined, providing essential information precisely when and where you require it, enabling quick identification and rectification of issues. Instrumental's Industrial AI efficiently detects and prioritizes every defect, accelerates failure analysis, and ensures your builds remain on schedule. Initiating faster issue resolution begins with having the right data readily accessible, which Instrumental provides by delivering a comprehensive product data record that includes parametric tests, images, and measurements at your convenience. Ultimately, this empowers teams to enhance their operational efficiency and improve product quality consistently.

WowYow has developed a patented technology that accelerates the processing of visual content by a factor of eight and is as much as ten times more economical compared to leading computer vision companies, showcasing the strength of affordable and accessible AI. Our approach not only utilizes Computer Vision and Metadata to decode visual content but also integrates distinctive business logic tailored to meet specific organizational requirements. From the outset, WowYow has been dedicated to designing innovative products that propel industries into the future. With offerings ranging from contextual advertising to streaming metadata, we create solutions that are truly one of a kind in the marketplace. By continuously refining our technology, we ensure that our clients are equipped with the most advanced tools available.

Tailor your outcomes by choosing specific categories of interest and enhancing detection sensitivity. Merge our detection components to create robust conditions, then align them with your personalized data labels for seamless integration into your current systems. Identify new custom attributes like SKU or item condition, even with limited data available. Thanks to our model's profound comprehension of object categories, we offer exceptional real-world accuracy using only a handful of images. Furthermore, all modifications occur on the server, ensuring immediate deployment. When combined with intelligent or deep links within your application, you can continuously enhance features and introduce new functionalities as needed. This capability allows for a dynamic and responsive approach to data management.

Valiot Al empowers plant managers to swiftly identify and resolve production bottlenecks without the need to disassemble their current infrastructure or equipment. By leveraging advanced AI algorithms in conjunction with a System Dynamics methodology, Valiot equips manufacturers with innovative tools to transform their production processes into smart, interconnected, and autonomous operations, unlocking unprecedented operational benefits. We integrate the capabilities of AI with the adaptability of IoT, enabling manufacturers to significantly improve their operational efficiency. Our FactoryOS solution interfaces seamlessly with both your shop floor and administrative systems, collecting data directly from your PLCs, drivers, IoT sensors, and other sources of information. This comprehensive approach ensures that every aspect of production is optimized, ultimately driving greater productivity and performance across the board.

The Video Explorer Platform serves as a comprehensive solution for the development and deployment of video analytics applications, leveraging computer vision technology. It features an adaptable application framework that can be tailored to meet specific business needs, facilitating seamless integration with existing customer systems. This platform allows enterprises to implement video analytics solutions swiftly and efficiently. When combined with the IBM Visual Builder (IVB), users gain advantages from a streamlined, single-stop process for developing and deploying video analytics applications, which encompasses tasks such as image labeling, image augmentation, and model training. Additionally, it offers robust features for managing data sources, including video devices, images, and offline video materials, alongside functionalities for real-time video browsing, image extraction, storage solutions, model mapping, and event processing rule configuration. Overall, the Video Explorer Platform is designed to empower businesses with the tools necessary for effective video analytics implementation.

At the core of our offerings lies Jidoka, a principle that promotes "intelligent automation," which we leverage to fuse artificial intelligence with industrial automation for innovative solutions. Jidoka Technologies specializes in providing advanced engineering solutions within the industrial automation sector, addressing a wide array of challenges. Our focus is on merging our knowledge in manufacturing, machine vision, deep learning, and software to create tailored automation solutions. One of our key specialties is automating the detection of visual defects, a task that is often subjective and varies greatly across different industries. We invite you to explore a comprehensive pathway toward achieving Jidoka in your operations. Our approach involves teaching machines to recognize patterns by example, allowing them to understand the complexities of visual variations in components and defects while also adapting to process fluctuations. The pursuit of perfect imaging for diverse applications, combined with our image processing techniques, enhances our AI capabilities and stands as a fundamental aspect of our innovative solutions. As we continue to evolve, we remain committed to pushing the boundaries of what automation can achieve in various sectors.

Quantarium leverages advanced AI to deliver innovative and transparent solutions that enhance decision-making across various domains, including valuations, analytics, propensity models, and portfolio optimization. It provides immediate access to the most precise insights regarding property values and market trends. The company boasts a robust and scalable next-generation cloud infrastructure that supports its operations effectively. Utilizing its adaptive AI-driven computer vision technology, which has been trained on a vast array of real estate images, Quantarium integrates this intelligence into its suite of QVM-based solutions. At the core lies the Quantarium Data Lake, which houses the most extensive and dynamic data set in the real estate sector. This AI-generated and enhanced data repository is meticulously curated by a team of AI scientists, data specialists, software developers, and industry professionals, establishing a new benchmark for real estate information. Furthermore, Quantarium's unique approach merges profound industry knowledge with self-evolving technology, paving the way for groundbreaking advancements in computer vision applications.

LTI's Mosaic serves as a unified platform that integrates data engineering, sophisticated analytics, automation driven by knowledge, IoT connectivity, and an enhanced user experience. This innovative platform empowers organizations to achieve significant advancements in business transformation, adopting a data-centric methodology for informed decision-making. It provides groundbreaking analytics solutions that bridge the gap between the physical and digital realms. Additionally, it acts as a catalyst for the adoption of enterprise-level machine learning and artificial intelligence. The platform encompasses features such as Model Management, Training at Scale, AI DevOps, MLOps, and Multi-Tenancy. LTI's Mosaic AI is specifically crafted to deliver a user-friendly experience for constructing, training, deploying, and overseeing AI models on a large scale. By amalgamating top-tier AI frameworks and templates, it facilitates a smooth and tailored transition for users from the “Build-to-Run” phase of their AI workflows, ensuring that organizations can efficiently harness the power of artificial intelligence. Furthermore, its adaptability allows businesses to scale their AI initiatives according to their unique needs and objectives.

Profet AI’s No-Code AutoML Platform, which is end-to-end and can be used by manufacturers as their Virtual Data Scientist, provides a complete solution for data analysis. It allows IT/domain experts to quickly build high-quality predictive models and deploy Industrial AI apps to solve their daily production and digitalization challenges. Profet AI AutoML Platform has been widely adopted by leading companies in the world across industries. These include leading EMS, Semi OSAT, PCB design houses, IC design houses, display panel and material solution providers. We use the successful cases of industry leading companies to benefit our customers and implement AI within a week.

A powerful solution to accelerate computational experiments. This allows non-developers or non-ML researchers obtain results quickly and effectively. It optimizes resource usage and streamlines scientific experiment orchestration for maximum efficiency. It facilitates team collaboration, computational modeling, and instant result sharing with its intuitive low-code interface. The platform's optimized resources management ensures seamless orchestration of hybrid infrastructure, integrating HPC hardware and on-prem servers for scientific use. It also improves experiment reproducibility, and allows interactive result sharing to improve research transparency and collaboration.

Peliqan.io provides a data platform that is all-in-one for business teams, IT service providers, startups and scale-ups. No data engineer required. Connect to databases, data warehouses, and SaaS applications. In a spreadsheet interface, you can explore and combine data. Business users can combine multiple data sources, clean data, edit personal copies, and apply transformations. Power users can use SQL on anything, and developers can use Low-code to create interactive data apps, implement writing backs and apply machine intelligence.

FiftyOne, developed by Voxel51, stands out as a leading platform for visual AI and computer vision data management. The effectiveness of even the most advanced AI models diminishes without adequate data, which is why FiftyOne empowers machine learning engineers to thoroughly analyze and comprehend their visual datasets, encompassing images, videos, 3D point clouds, geospatial information, and medical records. With a remarkable count of over 2.8 million open source installations and an impressive client roster that includes Walmart, GM, Bosch, Medtronic, and the University of Michigan Health, FiftyOne has become an essential resource for creating robust computer vision systems that function efficiently in real-world scenarios rather than just theoretical environments. FiftyOne enhances the process of visual data organization and model evaluation through its user-friendly workflows, which alleviate the burdensome tasks of visualizing and interpreting insights during the stages of data curation and model improvement, tackling a significant obstacle present in extensive data pipelines that manage billions of samples. The tangible benefits of employing FiftyOne include a notable 30% increase in model accuracy, a savings of over five months in development time, and a 30% rise in overall productivity, highlighting its transformative impact on the field. By leveraging these capabilities, teams can achieve more effective outcomes while minimizing the complexities traditionally associated with data management in machine learning projects.

Develop your own models, access a variety of pre-trained computer vision frameworks and application templates, and discover how to build AI applications or tackle business challenges using computer vision in just a few hours. Begin by creating a dataset for object detection by uploading images relevant to your training needs, with the capability to include as many as 5,000 images in each dataset. Once you have uploaded the images, they will automatically enter the training process, and you will receive a notification upon the completion of the model training. After this, you can easily download your model for detection purposes. Furthermore, you have the option to integrate your model with our existing application templates, facilitating swift coding solutions. Additionally, our mobile application, compatible with both Android and iOS platforms, harnesses the capabilities of computer vision to assist individuals who are completely blind in navigating daily challenges. This app can alert users to dangerous objects or signs, identify everyday items, recognize text and currency, and interpret basic situations through advanced deep learning techniques, significantly enhancing the quality of life for its users. The integration of such technology not only fosters independence but also empowers those with visual impairments to engage more fully with the world around them.