Business Software for Google Cloud BigQuery

A user-friendly, serverless service for change data capture and replication that provides access to streaming data from a variety of databases including MySQL, PostgreSQL, AlloyDB, SQL Server, and Oracle. This solution enables near real-time analytics in BigQuery, allowing for quick insights and decision-making. With a straightforward setup that includes built-in secure connectivity, organizations can achieve faster time-to-value. The platform is designed to scale automatically, eliminating the need for resource provisioning or management. Utilizing a log-based mechanism, it minimizes the load and potential disruptions on source databases, ensuring smooth operation. This service allows for reliable data synchronization across diverse databases, storage systems, and applications, while keeping latency low and reducing any negative impact on source performance. Organizations can quickly activate the service, enjoying the benefits of a scalable solution with no infrastructure overhead. Additionally, it facilitates seamless data integration across the organization, leveraging the power of Google Cloud services such as BigQuery, Spanner, Dataflow, and Data Fusion, thus enhancing overall operational efficiency and data accessibility. This comprehensive approach not only streamlines data processes but also empowers teams to make informed decisions based on timely data insights.

A live data platform based on Change Data Capture (CDC) facilitates the replication of diverse databases, supports real-time data integration, and assists in constructing a real-time data warehouse. By implementing CDC to synchronize production line information stored in DB2 and Oracle with a modern database, TapData has empowered an AI-enhanced real-time dispatch application that streamlines the semiconductor manufacturing process. The availability of real-time data has enabled prompt decision-making within the RTD application, resulting in quicker turnaround times and increased production yield. As a major telecommunications provider, the client operates numerous regional systems designed to serve local users effectively. By consolidating and integrating data from multiple sources and locations into a single centralized data repository, the client successfully established an order center that aggregates orders from various applications. Additionally, TapData integrates inventory data from over 500 stores, delivering real-time insights into stock availability and customer preferences, thereby significantly boosting supply chain efficiency. This innovative approach not only enhances operational performance but also positions the client to respond swiftly to market demands.

Leverage Airfold to accelerate your AI development by breaking down data silos and streamlining your architectural frameworks, allowing your organization to operate with the agility and scale required in today’s fast-paced environment, all through a single innovative platform. Current solutions fall short in addressing the needs of the modern AI landscape. With Airfold, you can dismantle barriers, cut costs, and achieve faster results like never before. Harness generative AI to create smarter applications at an unprecedented pace. Say goodbye to the hassle of managing multiple tools and scripts, as everything you need is now integrated into one solution. Enable every member of your organization to extract vital insights from data using natural language processing. Enhance your efficiency by utilizing AI to refine your data workflows in ways that were previously unimaginable. Convert text data, documents, images, and transcripts into actionable insights by having AI intelligently categorize information according to your specifications. Additionally, streamline operations by automating the generation of insights across vast datasets, thereby eliminating tedious manual tasks. This transformation not only improves productivity but also fosters a culture of data-driven decision-making throughout your organization.

AI engineering can be transparent rather than opaque. With a suite of tools for tracing, assessment, prompt management, and more, HoneyHive emerges as a comprehensive platform for AI observability and evaluation, aimed at helping teams create dependable generative AI applications. This platform equips users with resources for model evaluation, testing, and monitoring, promoting effective collaboration among engineers, product managers, and domain specialists. By measuring quality across extensive test suites, teams can pinpoint enhancements and regressions throughout the development process. Furthermore, it allows for the tracking of usage, feedback, and quality on a large scale, which aids in swiftly identifying problems and fostering ongoing improvements. HoneyHive is designed to seamlessly integrate with various model providers and frameworks, offering the necessary flexibility and scalability to accommodate a wide range of organizational requirements. This makes it an ideal solution for teams focused on maintaining the quality and performance of their AI agents, delivering a holistic platform for evaluation, monitoring, and prompt management, ultimately enhancing the overall effectiveness of AI initiatives. As organizations increasingly rely on AI, tools like HoneyHive become essential for ensuring robust performance and reliability.

DataChain serves as a bridge between unstructured data found in cloud storage and AI models alongside APIs, facilitating immediate data insights by utilizing foundational models and API interactions to swiftly analyze unstructured files stored in various locations. Its Python-centric framework significantly enhances development speed, enabling a tenfold increase in productivity by eliminating SQL data silos and facilitating seamless data manipulation in Python. Furthermore, DataChain prioritizes dataset versioning, ensuring traceability and complete reproducibility for every dataset, which fosters effective collaboration among team members while maintaining data integrity. The platform empowers users to conduct analyses right where their data resides, keeping raw data intact in storage solutions like S3, GCP, Azure, or local environments, while metadata can be stored in less efficient data warehouses. DataChain provides versatile tools and integrations that are agnostic to cloud environments for both data storage and computation. Additionally, users can efficiently query their unstructured multi-modal data, implement smart AI filters to refine datasets for training, and capture snapshots of their unstructured data along with the code used for data selection and any associated metadata. This capability enhances user control over data management, making it an invaluable asset for data-intensive projects.

The system automatically tracks and monitors all data points in your MMP on a daily basis. Daily notifications are provided for any campaigns and creatives that affect your ROAS or exhibit unusual behavior. It oversees campaign and creative metrics, sending alerts whenever these metrics exceed predefined thresholds. Regardless of your data storage location, Segwise enables effortless, no-code integration with all data sources. Among its key features are anomaly detection, alerting capabilities, and monitoring of cost-per-custom-event, which collectively offer a thorough insight into campaign performance. Additionally, Segwise evaluates the effects of product updates and LiveOps changes—such as new app versions, tests, and promotional offers—providing a well-rounded view of both revenue and retention metrics. Users have the opportunity to begin with a 14-day free trial that requires no credit card or engineering resources, allowing them to set up in just two minutes. The platform’s seamless integration with a variety of data sources ensures a user-friendly, no-code experience that eliminates the need for technical intervention while empowering users to optimize their campaigns effectively.

AWS Marketplace serves as a carefully organized digital platform that allows users to explore, buy, implement, and oversee third-party software, data products, AI agents, and services seamlessly within the AWS environment. This marketplace offers a vast array of options spanning various categories, including security, machine learning, business applications, and DevOps tools. By featuring adaptable pricing structures like pay-as-you-go, annual subscriptions, and free trials, AWS Marketplace makes it easier for customers to manage procurement and billing by consolidating expenses into a single AWS invoice. Additionally, it facilitates quick deployment of pre-configured software that can be easily launched on AWS infrastructure. This efficient model not only empowers businesses to spur innovation and reduce time-to-market but also enhances their ability to control software utilization and costs effectively. Ultimately, AWS Marketplace stands as an essential tool for organizations looking to optimize their software management and procurement processes.

Fabi.ai, an AI-powered platform for collaborative data analysis, is a collaborative data analysis platform. It helps data teams transform data into insights through a seamless integration of SQL, Python and AI. Fabi.ai allows data teams to create and share interactive dashboards, reports, data apps or lightweight data pipelines. Insights are then sent directly to Google Sheets and Slack.

GrowthCues, an automated product analytics tool, is a tool that provides instant product growth insights to B2B SaaS growth-focused teams. GrowthCues, unlike conventional product analytics tools that require complex dashboards and tedious analysis, automatically surfaces issues and opportunities related to user engagement and activation. It also identifies the drivers and blocks influencing product growth. GrowthCues, powered by generative AI and machine learning, delivers product growth insights to the Slack of your product team in plain English so that you and your team don't get lost in product data.

Google Earth Engine serves as a cloud-centric platform designed for the scientific examination and visualization of geospatial data, granting users access to an extensive public archive containing over 90 petabytes of analysis-ready satellite imagery alongside more than 1,000 carefully curated geospatial datasets. This rich collection boasts over five decades of historical imagery that is refreshed daily, with pixel resolutions reaching as fine as one meter, showcasing datasets from sources such as Landsat, MODIS, Sentinel, and the National Agriculture Imagery Program (NAIP). Through its web-based JavaScript Code Editor and Python API, Earth Engine empowers users to perform analyses on Earth observation data while employing machine learning techniques, thereby enabling the creation of sophisticated geospatial workflows. The platform's seamless integration with Google Cloud facilitates large-scale parallel processing, allowing for thorough analyses and efficient visualization of Earth data. Furthermore, Earth Engine's compatibility with BigQuery enhances its capabilities, making it a versatile tool for users in various fields. This unique combination of features positions Google Earth Engine as an essential resource for researchers and professionals working with geospatial information.

Satori serves as a LiveOps platform aimed at improving player retention, engagement, and monetization within live service games. It provides a robust array of tools, such as event capture, dynamic event calendars, remote configuration, experimentation, analytics, and tailored player messaging. Game studios and publishers can seamlessly create and implement live events, battle passes, promotional offers, notifications, and messages through Satori. The platform allows for personalized rewards, granting players premium incentives based on their achievements, purchases, and platform-specific exclusives. Furthermore, Satori supports the dynamic unlocking of new content, enriching the gameplay experience by unveiling additional material as players accomplish objectives or make purchases. It also enhances targeted player interaction, enabling studios to focus on specific player segments or individuals to provide exclusive content and encourage a sense of community. This comprehensive approach fosters stronger connections between players and games, ultimately driving higher engagement and satisfaction.

The Medical Imaging Suite from Google Cloud is crafted to revolutionize the way organizations handle imaging diagnostics by ensuring that imaging data is not only accessible but also interoperable and beneficial. This suite provides a secure, compliant, and fully managed service to oversee healthcare data in various formats such as FHIR, HL7v2, and DICOM, alongside unstructured text in natural language. Utilizing a cloud infrastructure simplifies the process of storing and sharing extensive collections of medical images that are prevalent in the healthcare sector, making it both efficient and economical. The Cloud Healthcare API facilitates operations to read DICOM instances, studies, and series in alignment with the DICOMweb standard. Furthermore, the suite enhances research capabilities and improves the overall patient experience in healthcare by providing comprehensive solutions for data storage and analysis, among other functionalities. Additionally, it offers guidance on concepts and best practices for the integration of third-party medical imaging viewers with the Cloud Healthcare API, ensuring a seamless experience for users. This holistic approach not only streamlines workflow but also fosters innovation in the medical imaging landscape.

Orchestra serves as a Comprehensive Control Platform for Data and AI Operations, aimed at empowering data teams to effortlessly create, deploy, and oversee workflows. This platform provides a declarative approach that merges coding with a graphical interface, enabling users to develop workflows at a tenfold speed while cutting maintenance efforts by half. Through its real-time metadata aggregation capabilities, Orchestra ensures complete data observability, facilitating proactive alerts and swift recovery from any pipeline issues. It smoothly integrates with a variety of tools such as dbt Core, dbt Cloud, Coalesce, Airbyte, Fivetran, Snowflake, BigQuery, Databricks, and others, ensuring it fits well within existing data infrastructures. With a modular design that accommodates AWS, Azure, and GCP, Orchestra proves to be a flexible option for businesses and growing organizations looking to optimize their data processes and foster confidence in their AI ventures. Additionally, its user-friendly interface and robust connectivity options make it an essential asset for organizations striving to harness the full potential of their data ecosystems.

FeatureByte acts as your AI data scientist, revolutionizing the entire data lifecycle so that processes that previously required months can now be accomplished in mere hours. It is seamlessly integrated with platforms like Databricks, Snowflake, BigQuery, or Spark, automating tasks such as feature engineering, ideation, cataloging, creating custom UDFs (including transformer support), evaluation, selection, historical backfill, deployment, and serving—whether online or in batch—all within a single, cohesive platform. The GenAI-inspired agents from FeatureByte collaborate with data, domain, MLOps, and data science experts to actively guide teams through essential processes like data acquisition, ensuring quality, generating features, creating models, orchestrating deployments, and ongoing monitoring. Additionally, FeatureByte offers an SDK and an intuitive user interface that facilitate both automated and semi-automated feature ideation, customizable pipelines, cataloging, lineage tracking, approval workflows, role-based access control, alerts, and version management, which collectively empower teams to rapidly and reliably construct, refine, document, and serve features. This comprehensive solution not only enhances efficiency but also ensures that teams can adapt to changing data requirements and maintain high standards in their data operations.

OpenMetadata serves as a comprehensive, open platform for unifying metadata, facilitating data discovery, observability, and governance through a single interface. By utilizing a Unified Metadata Graph alongside over 80 ready-to-use connectors, it aggregates metadata from various sources such as databases, pipelines, BI tools, and ML systems, thereby offering an extensive context for teams to effectively search, filter, and visualize assets throughout their organization. The platform is built on an API- and schema-first architecture, which provides flexible metadata entities and relationships, allowing organizations to tailor their metadata structure with precision. Comprising only four essential system components, OpenMetadata is crafted for straightforward installation and operation, ensuring scalable performance that empowers both technical and non-technical users to work together seamlessly on discovery, lineage tracking, quality assurance, observability, collaboration, and governance tasks without the need for intricate infrastructure. This versatility makes it an invaluable tool for organizations aiming to harness their data assets more effectively.

Reiterate OS is a finance automation platform that connects data, automates operations, and transforms manual finance processes into agentic workflows. It sits alongside your existing tools and files and takes care of the repetitive, manual work that slows you down the most: - Data collection from ERPs, payment processors, and banks - Data pre-processing and validation - Core accounting operations - Financial close processes Reiterate OS uses AI for gathering data and generating workflow configurations, but the workflows run deterministically based on your processes for 100% accurate results every time. Unlike traditional RPA or AI automation tools, it’s designed to handle large amounts of data, prioritizing modularity, accuracy, and auditability. It preserves what makes Excel trusted (transparency, auditability, control) while evolving with the demands of modern finance operations. Reiterate is a great tool for complex finance operations that require high-volume data processing, multi-system data integration, and customizable automation that scales with the business.

Aleph is a finance platform designed for AI, facilitating financial planning and analysis by merging data consolidation, spreadsheets, dashboards, and intelligent automation to enhance finance processes. It seamlessly integrates with over 150 systems, including ERP, HRIS/ATS, CRM, and various databases, utilizing no-code solutions to ensure real-time data synchronization. The platform adeptly transforms raw data through mapping, table combinations, and applying specific calculations, while securely storing essential metrics. Users can access Aleph via a web interface, complemented by spreadsheet add-ins that allow for the preservation of existing models, all while leveraging more accurate and live data. With features like dashboards and drill-down capabilities, it enables users to identify variances, expedite reporting and closing procedures, engage in forecasting and budget planning, model various scenarios, manage headcount effectively, and share visualized metrics across teams. Additionally, it incorporates robust security measures (SOC 2 Type II) and compliance features, ensuring clients receive immediate value from the platform; many report achieving operational readiness and generating reports within just a few days or weeks after implementation. This rapid onboarding and user-friendly design make Aleph an appealing choice for organizations looking to optimize their finance workflows.

Codd AI addresses a major challenge in the analytics landscape: transforming data into a format that is genuinely suitable for business purposes. Rather than having teams dedicate weeks to the tedious tasks of manually mapping schemas, constructing models, and establishing metrics, Codd leverages generative AI to automatically generate a context-aware semantic layer that connects technical data with the language of the business. As a result, business users can pose inquiries in straightforward English and receive precise, governed responses instantly—whether through BI tools, conversational AI, or various other platforms. Additionally, with built-in governance and auditability, Codd not only accelerates the analytics process but also enhances clarity and reliability. Ultimately, this innovative approach empowers organizations to make more informed decisions based on trustworthy data insights.

Replenit is an innovative replenishment platform powered by artificial intelligence that automates repeat purchases and enhances customer loyalty by understanding each individual's buying patterns and product connections, sending tailored reminders exactly when they are likely to need a product instead of relying on one-size-fits-all schedules. Utilizing an advanced AI decision-making engine, it forecasts the rate of consumption for various items, determines the optimal time for restocking or upselling, and effortlessly manages millions of personalized customer journeys across diverse channels such as email, SMS, app notifications, and messaging platforms, all while boosting conversion rates through well-timed interventions and minimizing manual oversight. By adjusting to real-world purchasing habits, Replenit creates dynamic, behavior-driven replenishment processes that improve subscription models and decrease customer churn, effectively generating more consistent revenue while sidestepping the limitations of fixed subscription timelines. Additionally, it offers smooth integration with existing commerce and customer data systems and is tailored for specific industry needs, ensuring a comprehensive solution for businesses aiming to optimize their sales strategies.

Enrich.sh is an advanced platform as a service that specializes in high-performance data enrichment infrastructure, crafted to facilitate real-time data workflows with remarkable scalability, low latency, and impressive throughput. This solution empowers both businesses and developers to efficiently enrich, process, and transform vast amounts of data, handling over 500 requests per second while maintaining sub-millisecond response times, thus making it ideal for applications that demand optimal performance and are designed for edge computing. Tailored for handling big data at the edge, Enrich.sh offers a backend service that adeptly manages enrichment workloads without imposing heavy operational burdens, enabling teams to concentrate on their core product development rather than the intricacies of infrastructure upkeep. With its comprehensive APIs, Enrich.sh allows users to seamlessly ingest, augment, and deliver enriched data at remarkable speeds, facilitating complex enrichment strategies and swift data pipelines suitable for both analytical and transactional scenarios. Furthermore, its user-friendly interface ensures that even those with limited technical expertise can leverage its capabilities to enhance their data processes efficiently.

Solid is a data intelligence platform enhanced by AI, aimed at ensuring enterprise data is both dependable and accessible for applications in AI, analytics, and interactive data queries. It automatically identifies, documents, and constructs business-relevant semantic models utilizing a company's existing data, queries, and tools, thereby establishing a reliable foundation that AI systems can depend upon. By assessing the actual usage of data within the organization, it produces validated tables, metrics, relationships, and SQL logic that correspond with genuine business definitions. With offerings like Solid Build and Solid Analyze, teams can streamline semantic modeling, convert natural language inquiries into production-ready SQL, and ensure models are continually refreshed in response to data changes. The platform prioritizes transparency and human involvement, permitting data teams to review, adjust, and confirm AI-generated models instead of merely depending on unclear automation. This approach fosters a collaborative environment where data professionals can enhance the quality and accuracy of the models they work with.

Motileo is an innovative platform focused on enhancing sales performance and fostering team engagement through gamification, which reimagines routine business activities and key performance indicators (KPIs) as engaging and competitive experiences aimed at boosting productivity and outcomes. By integrating seamlessly with existing tools like CRM systems, it automatically gathers essential performance metrics such as calls made, meetings scheduled, deals finalized, and revenue earned, transforming these figures into dynamic competitions, achievements, and progress tracking for both individuals and entire teams. Moreover, Motileo incorporates game-inspired mechanics into the work environment, recasting targets as accomplishments, milestones, and missions that lead employees toward quantifiable results while maintaining their involvement in the process. Teams have the opportunity to engage in tailored competitions or direct challenges that cultivate a spirit of friendly competition and promote ongoing effort, all while automated recognition features grant participants points or coins that can be exchanged for rewards. This unique approach not only motivates employees but also enhances collaboration and camaraderie among team members, making work more enjoyable and productive.

Milo serves as a robust AI data analyst, empowering teams to query, analyze, and interpret their data through natural language interactions. Rather than requiring the construction of intricate dashboards or the writing of SQL queries, users can effortlessly pose questions and receive immediate responses, along with visualizations and valuable insights. This innovative platform integrates seamlessly with company data sources, converting raw information into coherent analyses in mere seconds. It caters specifically to business teams, analysts, and product managers who require swift access to insights, minimizing the reliance on labor-intensive reporting or conventional business intelligence systems. Central to Milo's design are security and data governance, ensuring that the platform is suitable for enterprise-level environments with stringent access protocols to safeguard sensitive corporate information. By streamlining the manner in which teams engage with data, Milo not only accelerates organizational processes but also lessens the reliance on manual reporting practices, ultimately facilitating improved decision-making through real-time, AI-enhanced analysis. As a result, companies can leverage data more effectively and swiftly adapt to changing business dynamics.

Matia serves as a comprehensive DataOps platform aimed at streamlining contemporary data management by merging essential functions into a cohesive system. By integrating ETL, reverse ETL, data observability, and a data catalog, it removes the reliance on various isolated tools, thereby simplifying the challenges associated with managing disjointed data environments. This platform empowers teams to efficiently and reliably transfer data from diverse sources into data warehouses, utilizing sophisticated ingestion features that include real-time updates and effective error management. Furthermore, it facilitates the return of dependable data to operational tools for practical business applications. Matia prioritizes inherent observability throughout the data pipeline, offering capabilities such as monitoring, anomaly detection, and automated quality assessments to maintain data integrity and reliability, ultimately preventing potential issues from affecting downstream processes. As a result, organizations can achieve a more streamlined workflow and enhanced data utilization across their operations.

Astrato Analytics is a modern, warehouse-native business intelligence platform designed to help organizations create, embed, and share interactive dashboards and data-driven applications. It connects directly to leading cloud data warehouses such as Snowflake, BigQuery, Databricks, ClickHouse, Supabase, Amazon Redshift, PostgreSQL, and Dremio. By leveraging a zero-copy architecture, Astrato enables users to access and analyze data in real time without moving or duplicating it. Its live-query engine ensures that every dashboard and report reflects the most current data available. This eliminates the need for complex ETL processes or maintaining cached data layers. The platform also reduces operational overhead by simplifying data workflows and infrastructure requirements. Security is seamlessly managed, as Astrato inherits governance policies like row-level security and PII masking from the underlying data warehouse. This ensures compliance while minimizing manual configuration for IT teams. Users can build highly interactive and customizable analytics experiences directly on top of their existing data stack. The platform is designed to improve collaboration and data accessibility across teams. Overall, Astrato Analytics delivers a streamlined, real-time approach to business intelligence with strong performance and governance.