Best Embedded Business Intelligence Software - Page 12

Style Intelligence

Supersimple

Supersimple is an AI-native business intelligence platform that answers questions using both your data and your company's knowledge: metrics, tables, and documents, all at once. It connects to your data warehouse, data and code context (dbt, GitHub) and to the tools where your knowledge lives (Slack, Notion, Google Drive, Confluence, and more). Every answer is grounded with citations and no-code steps, instead of difficult-to-read code & queries. Governed semantic data models create a single source of truth, while ensuring flexible and reliable self-service.

Average Rating: 4.4/5.0

Total Reviews: 15

TalkBI

Talk.bi transforms the way teams interact with their data. Instead of writing complex SQL queries or navigating static dashboards, you can simply chat with your database — just like you’d talk to a colleague. Ask questions in plain English, and get instant answers beautifully visualized in interactive dashboards.

Tempo Power BI Connector for ServiceNow

Connect your ServiceNow data to Power BI to turn your operational data into strategic insights without custom development.

Upsolve AI

Upsolve AI is the platform for deploying governed, grounded, and trustworthy AI data agents to your internal teams or external customers. It helps data teams move past the broken self-serve BI promise by combining the conversational power of large language models with the rigor of a robust semantic layer, rich business context, and built-in evaluation and observability to put agent and context improvements on a flywheel. End users get accurate answers while the data team stays in control. The platform has two complementary components: the Upsolve Data Agent and the Upsolve Agent Context Studio. 1. The Upsolve Data Agent. The Upsolve Data Agent does what a good data analyst does. It answers business questions in natural language, asks clarifying questions when a request is ambiguous, generates charts and reports on the fly, and helps users explore the underlying data without writing SQL. These analyst behaviors come built into the agent itself. What the Upsolve Data Agent does: Conversational, natural-language Q&A over your data, with built-in text-to-SQL Multi-step reasoning across datasets, generate interactive charts on-demand(30+ chart types: bar, line, pie, scatter, heatmap, funnel, and more), auto-generated reports and summaries tailored to a user's role (exec, PM, ops, support, finance), conversational drill-down and follow-up turns in the same thread. The Upsolve Data Agent is designed to be easily customizable. We don't believe in an out-of-the-box data agent. Data agents are only useful and reliable with rich context and when assessed against your own performance benchmarks. A generic LLM connected to a database produces generic answers and hallucinated metrics. To produce true, traceable, and transparent answers about your business, the agent needs three more things, and that is where the Data Agent Studio comes in. 2. Upsolve Data Agent Studio. The Data Agent Studio is the place for your team to make the Data Agent accurate, reliable, and trustworthy. It is built on three layers: Data Layer, Context Layer, and Trust and Evals Layer. Data Layer: OOTB database connectors + Cockpit for Semantic Layer construction Database connectors for ClickHouse, Snowflake, BigQuery, Redshift, Databricks, Postgres, MySQL, and other major data warehouses. Robust data governance with Multi-tenant architecture with row- and column-level permissioning. For teams that don't have a unified semantic layer model, the Cockpit tool provides a guided and guardrailed interface that takes your team from fragmented data to a clean, AI-ready semantic layer in a week, instead of the six to eight months a typical V1 takes. Context Layer: your data agent needs a unified, auto-curated, and auto-refreshed context layer. The Context Layer connects your files, docs, and systems (Notion, Confluence, Google Drive, internal wikis, product release notes, dbt files, data catalogs, metric glossaries) and curates the information the agent needs to understand the business behind the numbers. It captures product launches, definition changes, ontology, naming conventions, and team-specific business logic so a query like "usage spiked last week" turn into "usage spiked last week, and this correlates with Tuesday's Pro plan launch". The Context Layer scans for updates across systems of records connected to it, flags context gaps, and suggests updated. Humans always in the loop. Trust and Evals Layer: Testing, end-of-end observability, and evaluations according to your benchmarks. Sandbox environment for pre-deployment testing, plus production logs after launch. Full LLM observability: every prompt, tool call, model used, retrieved context, and reasoning step is logged, traceable, and reviewable. Built-in evaluations: define gold-standard queries and answers, run tests, and catch agent drift with in-built LLM-as-a-judge evaluators before stakeholders. This system then creates a self-improving feedback loop when corrections from your team feed back into the agent's eval set so quality compounds over time. Together, those three Data Agent Studio components turn a generic agent into one that produces accurate, reliable, and trustworthy answers your team can defend. Delivery and deployment: The Upsolve Agentic Dashboard is a conversation-driven exploration surface for end users, with 30+ chart types, interactive filters, drill-down, PDF export, scheduled email, and version history. End users can save generated charts to a personal dashboard or simply tell the agent their role and have it auto-build a full dashboard for that persona, solving the blank-page problem typical of self-serve BI tools. SSO, role-based access control, and audit logging are included. The same Data Agent you customized can be accessed by your users wherever they already work. Embedded inside your own product as customer-facing analytics for B2B SaaS as an iFrame or React component; deploy into Slack and Microsoft Teams as in-channel data bot; access in Claude, ChatGPT, Cursor, and any MCP-compatible client to get data while you work and stage multi-agent workflows; or any custom application via REST API. Common use cases: Internal self-service business intelligence for data teams that don't want to be a ticket queue. Customer-facing embedded analytics for B2B SaaS products. Conversational analytics, generative BI (GenBI), and agentic BI deployments AI-powered reporting and operational analytics for ops, finance, support, and product. Multi-tenant SaaS analytics with row-level security. Looker, Tableau, Power BI alternatives for teams that want an AI-native approach. Why Upsolve AI AI-native architecture. Upsolve was built around the agent from day one, not retrofitted onto a legacy BI tool. Data team in control. The semantic layer, business context, and evals all live with your team, not buried inside a black-box LLM. Fast time-to-value. Cockpit takes you from fragmented data to a working semantic layer in a week. Real evaluation. Most "AI for BI" tools skip evals. Upsolve makes them first-class. Build in Studio, access anywhere. The same agent across internal dashboards, Slack, Teams, your product, and MCP-compatible clients. Enterprise-ready. SSO, role-based access control, multi-tenant governance, audit logging, and full observability included. Built for modern data and AI stacksUpsolve plugs into Snowflake, BigQuery, Redshift, Databricks, Postgres, MySQL. It works alongside dbt, existing semantic layers, and your data catalog. The Data Agent can be invoked from Claude, ChatGPT, Cursor, or any MCP-compatible client, making it easy to compose multi-agent workflows where Upsolve handles the data analysis step. YC W24.

Average Rating: 4.8/5.0

Total Reviews: 15

URSA Product Suite

Our URSA and DQ Software Product Suites connect your applications to disparate data sources across your organization - whether it's application integration, data mart development, or executive reporting, we can help you leverage the value of existing technology and achieve the return on your data assets that you are seeking.

vCube BI Excel Addin

Velory

Velory is the engine that runs IT lifecycle management. It runs hardware, software & SaaS and mobile subscriptions around every employee, from the first order to certified end-of-life. Connect your HR system, identity provider, MDM and suppliers, and Velory takes over the handoffs between them. New hires get their laptop, licences and phone plan before their first day. When someone leaves, devices are returned or bought out, licences revoked and subscriptions closed, so nothing keeps running after they’ve gone. Velory also works with what you already have. Idle devices in storage are offered before anyone buys new, unused licences and AI seats are flagged to reclaim, and renewals show up early enough to act on. Employees order from a store with budgets and approvals built in, from the suppliers you choose, one or several. Your data is processed by EU processors only, and Velory is ISO 27001 certified. Get visibility instantly and scale at your pace.

Average Rating: 5.0/5.0

Total Reviews: 1

ViewZen Analytics

Yurbi

Yurbi is self-hosted, embedded analytics and OEM business intelligence for ISVs and SaaS companies that want to ship dashboards and reporting to their customers — white-labeled as their own product, isolated per tenant, and running entirely on their own servers. Unlike usage-metered or per-seat embedded BI tools, Yurbi uses flat annual pricing from $10,000/year based on named-user tiers, with no per-user overage and no consumption spikes as traffic grows — so costs stay predictable as you scale. Every plan includes the entire platform with no feature paywalls: per-tenant white-label branding, multi-tenant security with row- and column-level data control, a no-code report builder, 20+ chart types, dashboards, dynamic data-source routing, FastCache for fast rendering, scheduled delivery, export, and a full REST API. Because Yurbi is self-hosted on your own Windows, Linux, or Docker servers, your customers' data never leaves your environment — there are no third-party cookies and no phone-home, and it's air-gap capable for high-security deployments. It connects natively to PostgreSQL, SQL Server, MySQL, and Oracle, plus Snowflake, Redshift, and BigQuery via ODBC. Yurbi is built and supported by 5000fish, a bootstrapped company with a codebase rooted since 1999 — so you work directly with the engineers who built it, not a support queue. It's a strong fit for ISVs replacing legacy tools like Crystal Reports, SSRS, or Izenda, or moving off consumption-billed embedded BI.

Zed Analytics

Zed-Analytics enables the creation of intriguing reports and interactive dashboards that deliver actionable data insights in a commercial context. Our clients can get regular updates on their company's success this way. Zed-Power Analytics helps and promotes the construction of persuasion reports and collaborative dashboards that communicate tough data insights in a secure manner.

Zuar Portal

Zuar Portal: build, manage, and deploy branded, white-labeled data experiences — no-code to full-code — for internal teams and external customers.