5 Best AI Platforms for Embedded Analytics in 2025

If you’re building a product in 2025, chances are you’ve realized one thing: data isn’t optional anymore; your users expect insights at their fingertips.

But here’s the challenge:

• Which AI embedded analytics platform will actually handle complex data without slowing your app?
  
  

• Should you go for an open-source solution or invest in a premium one?
  
  

• Can your non-technical team set it up without months of developer time?

These decisions aren’t small. They directly impact user experience, costs, and scalability.

Pick the wrong tool, and you might end up spending more time fixing dashboards than delighting customers.

In this blog, I’ve analysed dozens of options and narrowed them down to the 5 best AI platforms for embedded analytics in 2025.

You’ll discover:

• What makes each platform stand out
  
  

• Where they shine and where they fall short
  
  

• How they compare on performance, pricing, and usability

By the end, you’ll know exactly which platform can help you deliver smarter insights, retain customers, and grow faster.

TL;DR - 5 Best AI Tools for Embedded Analytics

If you’re short on time, here are the top picks:

• Upsolve – Best all-in-one platform for turnkey AI-powered embedded analytics with multi-stakeholder support.
  
  

• ThoughtSpot – Best for search-driven analytics with natural language queries and AI-powered insights.
  
  

• Looker Embedded (Google Cloud) → Best for advanced data modelling and enterprise-level scalability.
  
  

• Sisense – Best for enterprises needing advanced analytics, scalability, and compliance.
  
  

• Power BI Embedded – Best for teams already in the Microsoft ecosystem looking for cost-effective embedding.

How to Choose the Right Embedded Analytics Platform

Before investing in an Embedded Analytics Platform, you need to be clear about what truly impacts your business. 

Your goal isn’t just to add dashboards, it’s to deliver better insights, improve user experience, and grow faster. Here’s what matters most:

• Easy Integration → Choose a platform that connects seamlessly with your existing tech stack to save engineering time.
  
  

• Scalability → Ensure it can handle growing data, users, and dashboards as your product scales.
  
  

• User Experience → Prioritize tools that deliver clean, simple dashboards your customers actually use.
  
  

• Customization → Pick a solution that matches your brand, workflows, and product experience.
  
  

• AI-Driven Insights → Go beyond reports select platforms that provide predictive analytics and smarter decision-making.
  
  

• Security & Compliance → Ensure data protection and support for standards like GDPR, SOC 2, or HIPAA.
  
  

• Pricing & ROI → Look for transparent pricing that aligns with your budget and growth plans.

The right platform should reduce engineering effort, empower your users, and support long-term business growth.

5 Best AI Platforms for Embedded Analytics in 2025

1. Upsolve AI – Best Overall Embedded Analytics Platform

Upsolve.ai is an embedded GenBI (Generative Business Intelligence) platform.

Instead of building static dashboards and wiring filters, you embed a component (React/iFrame) into your app, and users can query data in natural language. 

It’s designed for customer-facing analytics, where you don’t control the user persona and can’t predict all their reporting needs in advance.

Features

• Role-based dashboards out of the box – Dashboards auto-adapt based on user roles (CFO, Product Manager, Sales Director).
  
  

• Natural language to dashboard – Users type “Show me Q1 revenue by state” and get a dashboard in seconds.
  
  

• AI-driven insights – The system surfaces anomalies and push alerts, not just descriptive charts.
  
  

• White-label embedding – Theming to your company’s design system with CSS and components.
  
  

• Multi-tenant support – Useful for SaaS with many customer accounts.
  
  

• Export options – CSV/PDF downloads, scheduled email reports.

Pros

• Cuts engineering lift  embedding is weeks faster than building Looker/Metabase equivalents.
  
  

• Persona-based dashboards reduce training/support burden for your customer success teams.
  
  

• The natural language layer removes the need for SQL-trained ops teams.
  
  

• Good fit for startups scaling into enterprise without hiring a full BI team.

Cons

• Pricing starts high ($1,000+/month), not accessible for smaller startups.
  
  

• Still evolving enterprise features (HIPAA, advanced governance) compared to older incumbents.
  
  

• Heavy reliance on AI-driven workflows may feel like a black box for teams wanting strict control.

Pricing

• Growth Plan: $1,000+/month (3+ dashboard templates, 50 tenants).
  
  

• Professional Plan: $2,000+/month (unlimited templates, usage analytics, dedicated support).
  
  

• Enterprise Plan: Custom pricing, includes SSO, unlimited tenants, and advanced compliance.

Our Evaluation:

Use Cases

• SaaS companies adding customer-facing analytics without spinning up a full BI team.
  
  

• Platforms needing white-labeled dashboards that follow their design system.
  
  

• Teams that want to shift away from static reporting and give users “ask-anything” style analytics.
  
  

• B2B companies where every customer expects tailored dashboards (supply chain, fintech, healthcare).

Why Choose Upsolve.ai?

If your product needs AI-driven, hyper-personalized analytics that scale across many customer tenants, Upsolve.ai is built for that. 

It’s less about replacing your internal BI stack (Snowflake + Looker) and more about embedding an adaptive analytics layer into your product. 

Engineering teams save months, and users get dashboards that feel like part of your app rather than a bolted-on BI tool.

Evaluation Table

For fast-growing SaaS products, speed and simplicity matter.

Upsolve AI makes it easy to embed dashboards and reports directly inside the product without complex setup or heavy coding.

Designed for scalability and efficiency, it helps teams focus on building the product rather than managing BI infrastructure.

2. ThoughtSpot Embedded – Best for AI-Driven Search Analytics 

ThoughtSpot Embedded is built for AI-driven, search-first analytics.

Instead of forcing users to learn SQL or navigate static dashboards, it lets them simply type questions in natural language like “Top 10 customers by revenue this quarter and instantly get interactive charts and insights.

It’s designed for self-service analytics in customer-facing or internal products, where users need flexibility and speed without relying on data teams.

Features

• Natural language search (SpotIQ) – Users ask questions in plain English, and ThoughtSpot generates answers as visual dashboards.
  
  

• AI-driven insights – Automatic anomaly detection, trend forecasting, and personalized alerts.
  
  

• Liveboards – Interactive dashboards with drill-down and real-time exploration.
  
  

• White-label embedding – Seamlessly integrates into apps with theming and branding options.
  
  

• APIs & SDKs – Supports embedding via JavaScript/React for flexible developer control.
  
  

• Enterprise-grade security – Role-based access, SSO, and compliance support.

Pros

• Makes analytics simple for non-technical users with natural language queries.
  
  

• Reduces dependency on BI or data teams for reporting.
  
  

• AI-powered features highlight anomalies and trends automatically.
  
  

• Embeds cleanly with branding and customization support.

Cons

• Pricing can be high, especially for scaling SaaS products.
  
  

• Natural language works best for simple queries; complex analysis may still need data experts.
  
  

• Advanced features may feel overkill for smaller startups.

Pricing

• Developer Plan: Free for testing with limited users.
  
  

• Essentials Plan: Starts at ~$1,250/month (20 users, 25M rows).
  
  

• Pro & Enterprise Plans: Custom pricing, based on queries, users, and data volume.

Our Evaluation

Use Cases

• SaaS platforms that want to offer Google-like search analytics inside their apps.
  
  

• B2B products where customers expect on-demand, flexible reporting.
  
  

• Teams that want to cut dependence on SQL-trained ops or BI teams.
  
  

• Enterprises looking to empower non-technical users with AI-driven insights.

Why Choose ThoughtSpot Embedded?

If the priority is to give users instant answers without relying on data teams, ThoughtSpot stands out.

It’s built for companies that want to deliver self-service, AI-powered search analytics directly inside their product.

While the pricing is higher, it can save months of BI support costs and unlock faster decision-making for end users.

3. Looker Embedded (Google Cloud) – Best for Data Modeling

Looker Embedded is Google Cloud’s analytics platform known for its powerful data modeling.

Instead of building one-off dashboards, it lets teams define business rules and metrics in a single layer (LookML), ensuring consistency across every report.

It’s designed for enterprises that need governed, reusable data models and want to deliver analytics that scale across large teams or customer bases.

Features

• LookML semantic modeling – Define KPIs once and reuse across dashboards.
  
  

• API-first embedding – Build fully custom analytics with APIs, SDKs, and iframes.
  
  

• Real-time insights – Connects live to data sources like BigQuery for always-fresh metrics.
  
  

• AI-powered workflows – Supports natural language queries and auto-generated reports.
  
  

• Enterprise controls – Role-based access, SSO, and compliance features.
  
  

• Integration with Google Cloud – Optimized for BigQuery and the Google ecosystem.

Pros

• Strong data governance with consistent business logic across apps.
  
  

• Deep embedding capabilities with APIs and developer tools.
  
  

• Seamless integration with BigQuery and Google Cloud services.
  
  

• Scales well for enterprise-grade workloads.

Cons

• Steep learning curve for LookML; requires data engineers.
  
  

• Limited flexibility in UI customization.
  
  

• Pricing is high and less transparent compared to newer players.

Pricing

• No public pricing; requires a custom quote.
  
  

• Typically ranges from $35,000/year for smaller deployments to $100k+ annually for enterprise.
  
  

• Pricing depends on number of users, queries, and usage scale.

Our Evaluation

Use Cases

• Enterprises that need governed analytics across multiple apps and teams.
  
  

• SaaS companies managing complex data models at scale.
  
  

• Organizations already invested in the Google Cloud ecosystem.
  
  

• Businesses where consistency of KPIs and compliance is critical.

Why Choose Looker Embedded?

Looker is best suited for companies that need trusted, consistent analytics at enterprise scale.

Its data modeling layer ensures accuracy across reports and reduces metric confusion. 

While it demands technical expertise and a higher budget, it delivers a strong foundation for long-term, enterprise-grade analytics.

4. Sisense – Best for Developer-Friendly Customization

Sisense is built for companies that want maximum control over their analytics experience.

Instead of being limited to standard dashboards, developers can use APIs and SDKs to fully customize how analytics look and work inside the product.

It’s designed for SaaS products where deep customization, scalability, and flexibility matter more than quick setup.

Features

• Compose SDK & Sisense.js – Developers can create custom components and workflows.
  
  

• AI-powered insights – Automatic trend spotting, anomaly detection, and predictive analytics.
  
  

• White-label embedding – Full branding and theming to match the product design.
  
  

• Multi-tenant support – Built for SaaS platforms serving multiple customer accounts.
  
  

• Data mashups – Combine cloud, on-prem, and API-based sources in one dashboard.
  
  

• Enterprise security – Role-based access, SSO, and compliance support.

Pros

• Gives developers full flexibility to design analytics experiences.
  
  

• Strong scalability for multi-tenant SaaS environments.
  
  

• AI features reduce manual reporting and surface insights automatically.
  
  

• Mature enterprise-grade security and compliance.

Cons

• Requires developer resources; not ideal for teams seeking no-code simplicity.
  
  

• Complex setup and maintenance compared to newer platforms.
  
  

• Pricing is opaque and high, making it less accessible for startups.

Pricing

• No public pricing available; all plans require a custom quote.
  
  

• Typical estimates range from $25,000–$50,000/year for smaller deployments, scaling into six figures for enterprise.

Use Cases

• SaaS companies that want fully branded, custom analytics experiences.
  
  

• Products needing multi-tenant analytics across many clients.
  
  

• Enterprises with strong developer resources to manage integrations.
  
  

• Industries like healthcare, fintech, or logistics, where compliance and customization are critical.

Why Choose Sisense?

Sisense is ideal for teams that want deep customization and full developer control over their embedded analytics.

It’s built for SaaS products that need to deliver tailored analytics experiences at scale.

While pricing and complexity may be hurdles, for companies with the resources, it offers one of the most powerful and flexible platforms in the market.

5. Power BI Embedded – Best for Microsoft Ecosystem

Power BI Embedded is Microsoft’s answer to embedded analytics, built to work seamlessly with the Azure ecosystem.

It lets companies embed interactive dashboards and reports directly into their apps, with the advantage of staying inside Microsoft’s trusted infrastructure.

It’s best for businesses already running on Azure or Office 365, where tight integration and cost alignment with Microsoft services add real value.

Features

• Interactive reports & dashboards – Rich visuals embedded directly into apps.
  
  

• APIs & SDKs – Flexible customization using Microsoft developer tools.
  
  

• Pay-as-you-go capacity model – Scales usage by demand without upfront licensing.
  
  

• Real-time analytics – Connects to live data sources for always-fresh dashboards.
  
  

• Wide data source support – From SQL Server and Azure to Excel and third-party apps.
  
  

• Enterprise security – Role-based access, SSO, and Azure Active Directory integration.

Pros

• Seamless integration for companies already using Microsoft stack.
  
  

• Pay-as-you-go pricing makes it flexible for scaling usage.
  
  

• Strong visualization capabilities familiar to many business users.
  
  

• Enterprise-grade security and compliance backed by Azure.

Cons

• Embedding requires developer effort; setup is not plug-and-play.
  
  

• Performance can drop if capacity isn’t scaled properly.
  
  

• Pricing can grow quickly with heavy usage.

Pricing

• Capacity-based pricing (A1–A8 nodes).
  
  

• Starts at around $1/hour (A1) and scales up to $16/hour (A5+) depending on compute power.
  
  

• No viewer licenses required; only creators need Power BI Pro.

Our Evaluation

Use Cases

• SaaS products built on Azure or tightly integrated with Microsoft services.
  
  

• Enterprises where teams are already familiar with Power BI.
  
  

• B2B apps needing secure, scalable reporting without user licensing costs.
  
  

• Companies looking for predictable cost scaling tied to usage.

Why Choose Power BI Embedded?

Power BI Embedded is a natural fit for teams already in the Microsoft ecosystem.

It offers secure, scalable, and cost-flexible analytics with visuals users already know. 

While it needs developer setup and careful workload management, it’s one of the most practical and cost-efficient options for Microsoft-native SaaS products.

5 Best Power BI Embedded Analytics Alternatives & Competitors

How to Choose the Right Platform for Embedded Analytics

Choosing the right Embedded Analytics Platform depends on your business model, team needs, and long-term goals. Here’s a quick guide to help you decide:

1. Startups & SaaS-First Products → Upsolve AI

If speed and simplicity are your top priorities, Upsolve AI is a great choice.

It lets you launch dashboards fast, without heavy coding or long setup times perfect for growing SaaS products.

2. AI-First Search Analytics → ThoughtSpot

If you want users to ask questions in plain language and get instant AI-powered insights, ThoughtSpot is the way to go.

Best for self-service analytics and empowering non-technical users.

3. Enterprise Modeling Needs → Looker

For products needing strong data modeling, governance, and scalability, Looker Embedded is ideal.

Best suited for enterprises that want consistent, reusable metrics across apps.

4. Developers Seeking Control → Sisense

If your product needs deep customization and full developer control, Sisense is the right pick.

Ideal for SaaS teams looking to create customised analytics experiences.

5. Microsoft-Native SaaS → Power BI Embedded

If your product already uses Azure, Power BI, or other Microsoft tools, Power BI Embedded integrates seamlessly.

It’s cost-effective within the Microsoft ecosystem and offers strong visualization capabilities.

Conclusion

Choosing the right Embedded Analytics Platform comes down to your product goals, tech stack, and growth plans.

If you want speed, simplicity, and scalability, Upsolve AI is the best choice for startups and SaaS-first products.

It helps you embed powerful dashboards quickly, reduce development effort, and deliver a better user experience.

Ready to transform your product with seamless embedded analytics?

Try Upsolve AI today and get started in minutes.

FAQs

1. What are embedded analytics platforms?

Embedded analytics platforms let you add dashboards, reports, and AI-driven insights directly inside your product or app.

They help users access data without needing to switch to separate BI tools.

2. Which platform is best for SaaS?

For SaaS-first products and startups, Upsolve AI is the best choice.

It offers fast setup, no-code dashboards, and easy integration, making it perfect for growing products.

3. Do these tools support white-label dashboards?

Yes, platforms like Upsolve AI, ThoughtSpot, and Sisense offer white-label customisation, allowing you to match the dashboards with your brand’s look and feel.

4. Which one offers the fastest integration?

Upsolve AI offers the quickest integration, enabling you to launch dashboards in hours instead of weeks, thanks to its straightforward APIs and no-code setup.

5. Are these platforms secure & compliant?

Yes, all five platforms Upsolve AI, ThoughtSpot, Looker, Sisense, and Power BI Embedded offer enterprise-grade security and comply with standards such as GDPR, SOC 2, and HIPAA.