Top 10 AI Tools for Embedded Analytics and Reporting (May 2025)

Embedded analytics refers to integrating interactive dashboards, reports, and AI-driven data insights directly into applications or workflows. This approach lets users access analytics in context without switching to a separate BI tool. It’s a rapidly growing market – valued around $20 billion in 2024 and projected to achieve $75 billion by 2032 (18% CAGR).

Organizations are embracing embedded analytics to empower end-users with real-time information. These trends are fueled by demand for self-service data access and AI features like natural language queries and automatic insights, which make analytics more accessible.

Below we review top tools that provide AI-powered embedded analytics and reporting. Each tool includes an outline, key pros and cons, and a breakdown of pricing tiers.

AI Tools for Embedded Analytics and Reporting (Comparison Table)

Explo is an embedded analytics platform designed for product and engineering teams to quickly add customer-facing dashboards and reports to their apps. It offers a no-code interface for creating interactive charts and supports white-labeled embedding, so the analytics mix into your product’s UI.

Explo focuses on self-service: end-users can explore data and even construct ad hoc reports without having developer intervention. A standout feature is Explo AI, a generative AI capability that lets users ask free-form questions and get back relevant charts routinely.

This makes data exploration as easy as typing a question in natural language. Explo integrates with many databases and is built to scale from startup use cases to enterprise deployments (it’s SOC II, GDPR, and HIPAA compliant for security).

Pricing:

• Launch – Free: Internal BI use only; unlimited internal users/dashboards.
• Growth – from $795/month: For embedding in apps; includes 3 embedded dashboards, 25 customer accounts.
• Pro – from $2,195/month: Advanced embedding; unlimited dashboards, full white-label, scales with usage.
• Enterprise – Custom: Custom pricing for big scale deployments; includes priority support, SSO, custom features.

Visit Explo →

ThoughtSpot is an AI-driven analytics platform renowned for its search-based interface. With ThoughtSpot’s embedded analytics, users can type natural language queries (or use voice) to explore data and immediately get visual answers.

This makes analytics accessible to non-technical users – essentially a Google-like experience for your small business data. ThoughtSpot’s in-memory engine handles large data volumes, and its AI engine (SpotIQ) routinely finds insights and anomalies.

For embedding, ThoughtSpot provides low-code components and robust REST APIs/SDKs to integrate interactive Liveboards (dashboards) and even just the search bar into applications. It’s popular for customer-facing analytics in apps where end-users need ad-hoc querying ability.

Businesses in retail, finance, and healthcare use ThoughtSpot to let frontline employees and customers ask data questions on the fly. The platform emphasizes ease-of-use and fast deployment, though it also offers enterprise features like row-level security and scalability across cloud data warehouses.

Pricing:

• Essentials – (billed annually): For larger deployments; increased data capability and features.
• ThoughtSpot Pro: Custom quote. Full embedding capabilities for customer-facing apps (as much as ~500 million data rows).
• ThoughtSpot Enterprise: Custom quote. Unlimited data scale and enterprise SLA. Includes multi-tenant support, advanced security, etc.

Visit ThoughtSpot →

Tableau (a part of Salesforce) is a number one BI platform known for its powerful visualization and dashboarding capabilities. Tableau Embedded Analytics allows organizations to integrate Tableau’s interactive charts and reports into their very own applications or web sites.

Developers can embed Tableau dashboards via iFrames or using the JavaScript API, enabling wealthy data visuals and filtering in-app. Tableau’s strength lies in its breadth of out-of-the-box visuals, drag-and-drop ease for creating dashboards, and a big user community.

It also has introduced AI features – for instance, in 2024 Salesforce announced , which uses generative AI to deliver automated insights and natural language summaries to users. This augments embedded dashboards with proactive explanations.

Tableau works with a wide selection of information sources and offers live or in-memory data connectivity, ensuring that embedded content can display up-to-date info. It’s well-suited for each internal embedded use (e.g. inside an enterprise portal) and external customer-facing analytics, though licensing cost and infrastructure should be planned accordingly.

Pricing:

• Creator – $70 per user/month: Full authoring license (data prep, dashboard creation). Needed for developers constructing embedded dashboards.
• Explorer – $35 per user/month: For users who explore and edit limited content. Suitable for internal power users interacting with embedded reports.
• Viewer – $12 per user/month: Read-only access to view dashboards. For end viewers of embedded analytics.

Visit Tableau →

Microsoft Power BI is a widely-used BI suite, and Power BI Embedded refers back to the Azure service and APIs that permit you embed Power BI visuals into custom applications. That is attractive for developers constructing customer-facing analytics, because it combines Power BI’s robust features (interactive reports, AI visuals, natural language Q&A, etc.) with flexible embedding options.

You possibly can embed full reports or individual tiles, control them via REST API, and apply row-level security for multi-tenant scenarios. Power BI’s strengths include tight integration with the Microsoft ecosystem (Azure, Office 365), strong data modeling (via Power BI Desktop), and growing AI capabilities (e.g. the Q&A visible that permits users to ask questions in plain English).

Pricing:

• Power BI Pro – $14/user/month: Enables creating and sharing reports. Required for developers and any internal users of embedded content.
• Power BI Premium Per User – $24/user/month: Enhanced features (AI, larger datasets) on a per-user basis. Useful if a small variety of users need premium capabilities as a substitute of a full capability.
• Power BI Embedded (A SKUs) – for A1 capability (3 GB RAM, 1 v-core). Scales as much as ~$23,500/month for A6 (100 GB, 32 cores) for high-end needs. Billed hourly via Azure, with scale-out options.

Visit Power BI →

Looker is a contemporary analytics platform now a part of Google Cloud. It is thought for its unique data modeling layer, LookML, which lets data teams define business metrics and logic centrally.

For embedded analytics, Looker provides a sturdy solution: you may embed interactive dashboards or exploratory data tables in applications, leveraging the identical Looker backend. One in every of Looker’s core strengths is consistency – due to LookML, all users (and embedded views) use trusted data definitions, avoiding mismatched metrics.

Looker also excels at integrations: it connects natively to cloud databases (BigQuery, Snowflake, etc.), and since it’s within the Google ecosystem, it integrates with Google Cloud services (permissions, AI/ML via BigQuery, etc.).

Pricing:

Visit Looker →

Sisense is a full-stack BI and analytics platform with a powerful deal with embedded analytics use cases. It enables corporations to infuse analytics into their products via flexible APIs or web components, and even allows constructing custom analytic apps.

Sisense is thought for its ElastiCube in-chip memory technology, which might mash up data from multiple sources and deliver fast performance for dashboards. Lately, Sisense has incorporated AI features (e.g. NLQ, automated insights) to remain competitive.

A key advantage of Sisense is its ability to be fully white-labeled and its , which is why many SaaS providers select it to power their in-app analytics. It offers each cloud and on-premises deployment options, catering to different security requirements.

Sisense also provides a variety of customization options: you may embed entire dashboards or individual widgets, and use their JavaScript library to deeply customize feel and look. It’s fitted to organizations that need an end-to-end solution – from data preparation to visualization – specifically tailored for embedding in external applications.

Pricing:

• Starter (Self-Hosted) – Starts around $10,000/yr for a small deployment (few users, basic features). This may typically be an on-prem license for internal BI or limited OEM use.
• Cloud (SaaS) Starter – ~$21,000/yr for ~5 users on Sisense Cloud (cloud hosting carries ~2× premium over self-host).
• Growth/Enterprise OEM – Costs scale significantly with usage; mid-range deployments often range $50K-$100K+ per yr. Large enterprise deals can reach several hundred thousand or more if there are very high numbers of end-users.

Visit Sisense →

Qlik is a long-time leader in BI, offering Qlik Sense as its modern analytics platform. Qlik’s embedded analytics capabilities mean you can integrate its associative data engine and wealthy visuals into other applications.

Qlik’s differentiator is its Associative Engine: users can freely explore data associations (making selections across any fields) and the engine immediately updates all charts to reflect those selections, revealing hidden insights.

In an embedded scenario, this implies end-users can get powerful interactive exploration, not only static filtered views. Qlik provides APIs (Capability API, Nebula.js library, etc.) to embed charts and even construct fully custom analytics experiences on top of its engine. It also supports standard embed via iframes or mashups.

Qlik has incorporated AI as well – the Insight Advisor can generate insights or chart suggestions routinely. For developers, Qlik’s platform is sort of robust: you may script data transformations in its load script, use its security rules for multi-tenant setups, and even embed Qlik into mobile apps.

Pricing:

• Starter – $200 / month (billed annually): Includes 10 users + 25 GB “data for evaluation.” No extra data add-ons available.
• Standard – $825 / month: Starts with 25 GB; buy more capability in 25 GB blocks. Unlimited user access.
• Premium – $2,750 / month: Starts with 50 GB, adds AI/ML, public/anonymous access, larger app sizes (10 GB).
• Enterprise – Custom quote: Begins at 250 GB; supports larger app sizes (as much as 40 GB), multi-region tenants, expanded AI/automation quotas.

Visit Qlik →

Domo is a cloud-first business intelligence platform, and Domo In all places is its embedded analytics solution aimed toward sharing Domo’s dashboards outside the core Domo environment. With Domo In all places, corporations can distribute interactive dashboards to customers or partners via embed codes or public links, while still managing every little thing from the central Domo instance.

Domo is thought for its end-to-end capabilities within the cloud – from data integration (500+ connectors, built-in ETL called Magic ETL) to data visualization and even a built-in data science layer.

For embedding, Domo emphasizes ease of use: non-technical users can create dashboards in Domo’s drag-and-drop interface, then simply embed them with minimal coding. It also offers robust governance so you may control what external viewers see.

Pricing:

• Basic Embedded Package – roughly $3,000 monthly for a limited-user, limited-data scenario. This might include a handful of dashboards and a moderate variety of external viewers.
• Mid-size Deployment – roughly $20k–$50k per yr for mid-sized businesses. This may cover more users and data; e.g., a couple of hundred external users with regular usage.
• Enterprise – $100k+/yr for large-scale deployments. Enterprises with 1000’s of external users or very high data volumes can expect costs in six figures. (Domo often structures enterprise deals as unlimited-user but metered by data/query credits.)

Visit Domo →

Yellowfin is a BI platform that has carved a distinct segment in embedded analytics and data storytelling. It offers a cohesive solution with modules for dashboards, data discovery, automated signals (alerts on changes), and even a novel Story feature for narrative reporting.

For embedding, Yellowfin Embedded Analytics provides OEM partners a versatile licensing model and technical capabilities to integrate Yellowfin content into their applications. Yellowfin’s strength lies in its balanced focus: it’s powerful enough for enterprise BI but in addition streamlined for embedding, with features like multi-tenant support and white-labeling.

It also has NLP query (natural language querying) and AI-driven insights, aligning with modern trends. A notable feature is Yellowfin’s data storytelling – you may create slide-show style narratives with charts and text, which could be embedded to offer end-users contextual evaluation, not only raw dashboards.

Yellowfin is commonly praised for its collaborative features (annotations, discussion threads on charts) which could be helpful in an embedded context where you would like users to interact with the analytics.

Pricing:

Visit Yellowfin →

Mode is a platform geared towards advanced analysts and data scientists, combining BI with notebooks. It’s now a part of ThoughtSpot (acquired in 2023) but still offered as a standalone solution.

Mode’s appeal in an embedded context is its flexibility: analysts can use SQL, Python, and R in a single environment to craft analyses, then publish interactive visualizations or dashboards that could be embedded into web apps. This implies in case your application’s analytics require heavy custom evaluation or statistical work, Mode is well-suited.

It has a contemporary HTML5 dashboarding system and recently introduced “Visual Explorer” for drag-and-drop charting, plus AI assist features for query suggestions. Corporations often use Mode to construct wealthy, bespoke analytics for his or her customers – for instance, a software company might use Mode to develop a fancy report, after which embed that report of their product for every customer with the info filtered appropriately.

Mode supports white-label embedding, and you may control it via their API (to provision users, run queries, etc.). It’s popular with data teams on account of the seamless workflow from coding to sharing insights.

Pricing: 

• Studio (Free) – $0 without end for as much as 3 users. This includes core SQL/Python/R analytics, private data connections, 10MB query limit, etc. Good for initial development and testing of embedded ideas.
• Pro (Business) – Starts around ~$6,000/yr (estimated). Mode doesn’t list fixed prices, but third-party sources indicate pro plans within the mid four-figure range annually for small teams.
• Enterprise – Custom pricing, typically five-figure annually as much as ~$50k for big orgs. Includes all Pro features plus enterprise security (SSO, advanced permissions), custom compute for heavy workloads, and premium support.

Visit Mode →

Find out how to Select the Right Embedded Analytics Tool

Choosing an embedded analytics solution requires balancing your organization’s needs with each tool’s strengths. Start along with your use case and audience: Consider who shall be using the analytics and their technical level. When you’re embedding dashboards for non-technical business users or customers, a tool with a simple UI might be necessary. Conversely, in case your application demands highly custom analyses or you’ve a powerful data science team, a more flexible code-first tool is perhaps higher.

Also evaluate whether you would like a completely managed solution (more plug-and-play, e.g. Explo or Domo) or are willing to administer more infrastructure for a potentially more powerful platform (e.g. self-hosting Qlik or Sisense for complete control). The dimensions of your organization (and engineering resources) will influence this trade-off – startups often lean towards turnkey cloud services, while larger enterprises might integrate a platform into their existing tech stack.

Integration and scalability are critical aspects. Take a look at how well the tool will integrate along with your current systems and future architecture. Finally, weigh pricing and total cost of ownership against your budget and revenue model. Embedded analytics tools vary from per-user pricing to usage-based and stuck OEM licenses. Map out a rough projection of costs for 1 yr and three years as your user count grows.

FAQs (Embedded Analytics and Reporting)

1. What are the foremost differences between Tableau and Power BI?

Tableau focuses on advanced visual design, cross-platform deployment (on-prem or any cloud), and a big viz library, nevertheless it costs more per user. Power BI is cheaper, tightly integrated with Microsoft 365/Azure, and great for Excel users, though some features require an Azure capability and Windows-centric stack.

2. How does Sisense handle large datasets in comparison with other tools?

Sisense’s proprietary ElastiCube “in-chip” engine compresses data in memory, letting a single node serve hundreds of thousands of rows while maintaining fast query response; benchmarks show 500 GB cubes on 128 GB RAM. Competing BI tools often depend on external warehouses or slower in-memory engines for similar workloads.

3. Which embedded analytics tool offers one of the best customization options?

Sisense and Qlik are stand-outs: each expose full REST/JavaScript APIs, support deep white-labeling, and let dev teams construct bespoke visual components or mashups—ideal if you need analytics to feel and look 100 % native in your app.

4. Are there any free alternatives to Tableau and Sisense?

Yes—open-source BI platforms like Apache Superset, Metabase, Redash, and Google’s free Looker Studio deliver dashboarding and basic embedded options at zero cost (self-hosted or SaaS tiers), making them good entry-level substitutes for smaller teams or tight budgets.