Databricks

Databox is an agentic analytics platform for agencies and teams. It connects data from tools, spreadsheets, databases, and APIs, defines governed metrics through a semantic layer, and combines dashboards, reports, goals, and KPIs with AI analysis. Its AI Analyst answers questions using live data, while agents and automations run recurring analysis and follow-up workflows; its MCP capability grounds AI tools in Databox data and business context. The platform states that data is encrypted and access-controlled and is not used to train AI models.

A Databricks product used for automated security detections.

Data Agent Kit is an editor extension for working with data operations. It supports viewing data jobs, executing saved queries, monitoring data-flow and Spark jobs, running notebooks, and accessing data services.

Apache Spark is a unified analytics engine for large-scale data processing, developed as an Apache project. It provides high-level APIs in Scala, Java, Python, and R, and executes general computation graphs for data analysis. Its higher-level components include Spark SQL and DataFrames, the pandas API on Spark, MLlib for machine learning, GraphX for graph processing, and Structured Streaming for stream processing. Spark can run locally or submit workloads to clusters through Spark, YARN, or Kubernetes integrations, and is used in large-scale data pipelines such as those underlying Poolside's model factory.

Helical Insight is an open-source business intelligence and embedded analytics platform for self-hosted, cloud, on-premises, and hybrid deployments. It combines natural-language, chat-driven AI analytics with bring-your-own-LLM support, automatic SQL generation, report summarization, and insight discovery; interactive dashboards with filters, KPI widgets, drill-down and drill-through interactions, maps, charts, pivot tables, and custom JavaScript visualizations; and paginated, pixel-perfect reports for invoices, financial statements, operational reports, and regulatory reporting. Dashboards, reports, and the AI chatbot can be embedded in web applications, SaaS platforms, customer portals, and enterprise applications. Reports and dashboards can be exported to PDF, Excel, CSV, Word, HTML, JSON, and XML, scheduled for delivery by email, and distributed as personalized reports. The platform supports white labeling, multi-tenancy, row-, column-, and table-level security based on user context, and SSO through JWT, Okta, Keycloak, OAuth, and custom token-based mechanisms. It connects to relational databases, NoSQL and big-data systems, flat files, cloud storage, and APIs through native connectors, JDBC, REST APIs, custom integrations, and uploaded JDBC drivers. Docker, Kubernetes, caching, pagination, virtualization, load balancing, clustering, and REST APIs support deployment and extension, while developers can customize it with Java, JavaScript, CSS, HTML, Liquid Template Language, plugins, and custom workflows. The project states that its enterprise features are available in the free open-source version.