
FinOpsly is an AI-native control plane for managing Cloud, Data, and AI spend at enterprise scale.
Built for organizations operating across multiple clouds and data platforms, FinOpsly shifts FinOps from passive reporting to active, governed execution. The platform connects cost, usage, and business context into a unified operating model—allowing teams to anticipate spend, enforce guardrails, and take automated action with confidence.
FinOpsly brings together infrastructure (AWS, Azure, GCP), data platforms (Snowflake, Databricks, BigQuery), and AI workloads into a single decision and execution layer. With explainable AI agents operating under policy-based controls, teams can safely automate optimization, trace cost drivers to real workloads, and stop budget drift before it becomes a problem.
Key capabilities include:
Business-aware cost attribution across products, teams, and services
Predictive insight into cost drivers with clear, explainable reasoning
Policy-controlled automation to optimize spend without disrupting performance
Early detection and prevention of overruns, inefficiencies, and financial drift
FinOpsly enables engineering, finance, and platform teams to operate from the same source of truth—turning cloud and data spend into a controllable, measurable part of the business.
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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.
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Kubit
Warehouse-Native Customer Journey Analytics—No Black Boxes. No Limits.
Kubit is the leading customer journey analytics platform, built for product, data, and marketing teams who need self-service insights, real-time visibility, and full control of their data—all without engineering dependencies or vendor lock-in.
Unlike traditional analytics tools, Kubit is warehouse-native, enabling you to analyze user behavior directly in your cloud data platform (Snowflake, BigQuery, or Databricks). No data extraction. No hidden algorithms. No black-box logic.
With built-in support for funnel analysis, retention, user paths, and cohort exploration, Kubit makes it easy to understand what’s working—and what’s not—across the entire customer journey. Add real-time anomaly detection and exploratory analytics, and you get faster decisions, smarter optimizations, and more engaged users.
Top enterprises like Paramount, TelevisaUnivision, and Miro trust Kubit for its flexibility, data governance, and unmatched customer support.
Discover the future of customer analytics at kubit.ai
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Astrato
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.
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