8 Best ThoughtSpot Competitors and Alternatives in 2026

ThoughtSpot is a business intelligence and data visualization tool that has been around for more than a decade. With notable customers like Coca-Cola, T-Mobile, and CVS, it’s gotten a reputation for being an easy-to-use analytics tool for enterprise companies. Even more so once they launched their new AI-based features.

But what if you’re not happy with ThoughtSpot’s user experience, integrations, pricing or customer support? You may be looking into ThoughtSpot competitors and today, we’re rounding up the very best ones to help you make a good choice instead of a guess.

But first…

For customer-facing embedded analytics, Luzmo is the strongest ThoughtSpot alternative because embedding and multi-tenancy are structural rather than configured, with published pricing. For governed semantic modeling, Omni or GoodData fit better. For enterprise internal BI and visualization depth, Tableau still leads.

ThoughtSpot alternatives at a glance

Tool	Best for	Embedded-first?	Public pricing?	AI approach
Luzmo	Customer-facing embedded analytics in SaaS	Yes, built for embedding from day one	Yes, published plans	Luzmo IQ conversational analyst
Tableau	Enterprise visual analysis	No, enterprise BI first	Partially, role-based and varies by product	AI-assisted analysis features
Qlik Sense	Associative exploration for data professionals	No, internal BI first	No, enterprise pricing is quote-based	AI and automation features
Power BI	Microsoft-stack reporting at scale	Separate Power BI Embedded product	Partially, Embedded uses Azure capacity	Copilot features
Sisense	Component-level embedding for developer teams	Yes, repositioned around embedding	No, enterprise pricing is quote-based	AI features in Fusion
Domo	All-in-one cloud BI with ETL bundled	No, internal BI first	No, consumption-based quote	Domo.AI agents and NLQ
GoodData	Regulated enterprises needing self-hosting	Yes, purpose-built for embedding	No, platform fee plus per-workspace quote	AI-assisted analytics
Looker	Governed semantic modeling on Google Cloud	No, internal BI first	No, annual contracts through Google Cloud	Gemini conversational analytics

ThoughtSpot pricing in 2026

ThoughtSpot publishes entry prices for its lower tiers and quotes Enterprise through sales. Here's the structure as of August 5, 2026:

Plan	Entry price	Users	Data volume	Notable inclusions
Essentials	From $25 per user/month, billed annually	5 to 50	Up to 25M rows	Interactive dashboards, actionable insights
Pro, per user	From $50 per user/month, billed annually	Up to 1,000	Up to 250M rows	Natural-language search, Spotter AI Agents at 25 queries/user/month
Pro, usage-based	From $0.10 per credit	Up to 1,000	Up to 250M rows	Spotter AI Agents with unlimited LLM tokens, Analyst Studio
Enterprise	Talk to sales	Custom	Custom	Custom

Four things are easy to misread here, and most comparison articles get at least one of them wrong.

"Starting as low as" is a floor, not a rate. Both published figures are entry points, so treat them as the best case for your smallest possible configuration rather than what you'll actually be quoted.

Pro is an either/or choice, not a single plan. You can buy Pro per user at $50 per user per month, or on a usage basis at $0.10 per credit. Those behave completely differently as you scale: per-user cost is predictable and rises with headcount, while credit-based cost tracks how hard people actually use the platform. Which is cheaper depends entirely on your usage profile, so model both.

The credit price is per credit, not per query. This gets garbled constantly, including in older comparisons. A credit is a unit of platform consumption, so you can't convert $0.10 into a per-question cost without understanding how credits are consumed.

The Spotter AI allowance differs between the two Pro options. Per-user Pro caps Spotter AI Agents at 25 queries per user per month. The usage-based option includes Spotter with unlimited LLM tokens. If AI-led exploration is the reason you're buying, that cap is the detail to check first. Worth noting that ThoughtSpot doesn't meter or charge for LLM tokens itself, though if you bring your own LLM provider that provider's fees still apply.

For the embedded product specifically, there's a developer offer that's free for the first year, described as supporting up to ten users and 25 million rows. Useful for prototyping, not a production plan. Our ThoughtSpot pricing breakdown goes deeper, and Enterprise still needs a quote for your real user count and data volume.

Why look for ThoughtSpot competitors?

Maybe you’ve been using ThoughtSpot in 2026 and feel it no longer fits your needs. Or perhaps you’re looking for alternatives because you’re choosing your next analytics and business intelligence tool. Either way, it’s worth taking a closer look at some of the challenges users face with this self-service BI platform.

The pricing gap:

The jump between tiers is the specific complaint. Essentials starts as low as $25 per user per month but caps at 50 users and 25 million rows, and the moment you outgrow either limit you're into Pro at $50 per user per month, double the entry rate. Above 1,000 users or 250 million rows you're into Enterprise, which is quoted through sales with no published figure at all. So the cost curve isn't smooth, it's a set of steps, and the step you land on depends on limits you may hit sooner than you expect. Our ThoughtSpot review digs into where teams typically hit the wall.

The pricing for embedded analytics:

If you want to create and share real-time dashboards for end-users, billing can be harder to predict. ThoughtSpot Embedded starts with a developer offer that's free for the first year, described as supporting up to ten users and 25 million rows, but production deployments move to Pro or Enterprise pricing. If you go the usage-based route at $0.10 per credit, cost scales with how heavily your customers interact with dashboards, which is exactly the variable you control least in a customer-facing product. The free developer tier won't tell you much about what production actually costs.

The AI features:

ThoughtSpot has invested heavily in AI, and its Spotter agents handle natural-language questions and analysis. That's a genuine differentiator rather than marketing. The honest caveat is that answer quality depends heavily on how well your data is modeled, so getting reliable results for complex analysis usually needs someone comfortable with SQL and data management. Our write-up on ThoughtSpot Sage covers how the natural-language layer behaves in practice.

If you're evaluating ThoughtSpot mainly for AI-led exploration, it's worth reading that caveat twice. Search-led analytics doesn't remove the modeling work, it relocates it. You still need governed metrics underneath, and if you skip that step you get answers that are confidently wrong, which is worse than no answer.

Limited visualization options:

Compared to top BI tools such as Tableau Server, Tableau Cloud, or Sigma, ThoughtSpot lacks variety in its visualization types. It doesn’t give much flexibility in chart sizing or dashboard customization, especially for embedded use. That limits how non-technical users can explore data and find insights using AI.

While ThoughtSpot remains a strong analytics platform designed for associative data, there are plenty of competitors and alternatives to ThoughtSpot worth testing.

From Google’s data exploration tool to other AI and ML solutions, you’ll find many top ThoughtSpot alternatives that allow users to explore data from multiple sources and uncover richer insights.

Below, we’ll cover 8 alternatives to consider if you’re ready to get a better analytics experience.

Spotter AI versus embedded AI: a distinction worth understanding

These sound like the same capability and they solve different problems, which is the single most useful thing to get straight before you shortlist.

Search-first analytics, which is ThoughtSpot's core bet, is designed for an internal user who wants to interrogate a governed dataset. The interaction model is a search box, the audience knows roughly what questions to ask, and the value is removing the analyst from the request queue.

Embedded AI is designed for your customer, inside your product, who probably doesn't know your data model exists. They aren't going to phrase a well-formed analytical question. The value is surfacing the insight in context, within a tenant boundary, styled as part of your application, with guardrails so nobody can wander into another customer's data.

The reason this matters commercially: search-first tools optimize for breadth of exploration, while embedded platforms optimize for safety and polish within a narrow scope. Ask a search-first tool to be your product's analytics layer and you inherit its interface conventions, its tenant model and its licensing assumptions. Ask an embedded platform to replace your internal analyst tooling and you'll find it deliberately narrower.

Most teams evaluating ThoughtSpot actually need one of these two and are being sold the other. Work out which you are first.

Top 8 ThoughtSpot alternatives in 2026

We chose these tools based on user reviews, features, the range of integrations and data sources, embedded analytics capabilities and more.

How we evaluated

• Semantic grounding. Whether AI answers rest on a governed model, since this decides whether they're trustworthy.
• Embedding depth. SDK versus iframe, plus tenant isolation, row-level security and white-labeling.
• Visualization flexibility. A recurring ThoughtSpot complaint, and it matters more once dashboards are customer-facing.
• Pricing transparency. Whether you can model cost before contacting sales.
• Audience fit. Internal analysts versus your own customers, which is the fork that decides everything else.

Research date. Product and pricing facts were checked against current vendor documentation on August 5, 2026. Treat specifics as a starting point for your own quote.

Our bias, stated plainly. Luzmo builds embedded analytics and competes with ThoughtSpot on customer-facing product analytics. We recommend Luzmo for that job specifically, not as a replacement for internal search-led BI, and where Tableau, Power BI, GoodData or Omni fit better we say so below. ThoughtSpot's search-led approach is genuinely good at what it was designed for.

Luzmo - best for embedded SaaS dashboards

Create interactive dashboards for your end-users and help them make confident decisions with real-time metrics. Luzmo remains easy to use, both for developers embedding analytics and for end-users exploring insights. From sign-up to embedding your first dashboard, it can take only a few hours.

You can now go beyond dashboards.
✔ Luzmo Flex lets you embed individual charts, metrics, or entire data experiences directly into your app’s UI.
✔ Luzmo IQ adds natural-language exploration since users can type a question and get instant visual answers.
✔ Luzmo Studio is where you design, preview, and manage all your analytics experiences in one place.

We love our APIs, Luzmo Agent APIs take that even further. They connect Luzmo’s analytics with your own AI assistants or automation workflows, helping you turn data into action automatically.

Connect Luzmo to almost any data source: Amazon Redshift, AWS Athena, Azure Synapse, BigQuery, ClickHouse, Databricks, and more. The API also works with the business tools you already use, from CRMs to communication platforms.

With true self-service analytics, end-users can drill down, explore, and create ad-hoc reports without writing a single line of SQL. Embedded directly into your app, fresh insights are always a few clicks away.

Pricing is transparent and built to scale with your product. Plans start at €995/month for Starter, €2,495/month for Premium, with Enterprise options for advanced needs - so you always know what to expect as you grow. The intuitive interface helps you design user-friendly dashboards that look and feel like a natural part of your product. Add data analytics automation and AI-generated visualizations with our one-click AI chart generator.

In short, Luzmo in 2026 is faster, smarter, and more flexible. You get natural-language data exploration, fine-grained visualization control, and a modular setup that fits every SaaS product.

Ready to build your next data experience? Start your free trial today.

Tableau - best for internal dashboard analytics

Owned by Salesforce, Tableau’s been around the block and remains one of the more mature choices for on-premise and cloud-based dashboard reporting. You’ll get a very wide choice of visualisations, strong integrations with data warehouses and third-party apps, and quite a user-friendly experience when it comes to dashboard consumption.

What’s new in 2026:

- A major upgrade that brings agentic analytics and AI-driven insights via its “Tableau Next” architecture.

- More secure connectivity (private links to AWS, on-prem options) and stronger data integration capabilities.

- Enhancements like keyboard-accessible interactivity, new visualization controls and improved mobile/embedded metric discovery.

Still solid, but with some cons:

- While the consumer side (viewing dashboards) is smoother than ever, building dashboards, especially advanced ones, still takes time and skill. If your dev team isn’t experienced, there’s a learning curve.

- While embedding has improved, the experience isn’t always seamless - large data sets can still load slowly and fine-customisation remains tougher than simpler tools.

- Tableau works best when you’ve already built analytics maturity. If you’ll only use it for minimal sharing or have small, non-technical teams, the investment may feel heavy.

If your team has a specialist or two, needs deep analytics, strong governance, and either on-premise or cloud deployment, Tableau remains a superb choice. If you’re looking for a very lightweight, fast-to-deploy tool for a non-technical audience, you might want to compare it with some newer, more agile alternatives.

On pricing, note that Tableau can't be reduced to one number: it's role-based and varies across Tableau Cloud, Tableau Server and Tableau Next, and Tableau Next separates user-role pricing from Data 360 storage costs that may apply. So comparing it with ThoughtSpot means modeling your full role mix rather than lining up two headline figures.

Check this out: Tableau vs ThoughtSpot. If you want the wider field, our roundup of Tableau alternatives beyond traditional dashboards covers where visual BI is heading.

Qlik Sense - best for experienced data professionals

Qlik takes a different approach to data analytics: instead of purely focusing on static dashboards, you can pull together “Stories”. As your data changes over time, Qlik captures snapshots and links them in a Story-flow, letting you tell a real narrative with your data.

In the latest 2025 updates, Qlik has added stronger support for AI-driven workflows, reusable scripting, automation and more seamless connectivity across data sources. For example, the July 2025 release adds new ML workflow support, reusable load-scripts, expanded SAP-report integration, and enhanced governance features.

What’s improved:

- The May 2025 release added custom tool-tips, improved straight/pivot tables, map-chart styling and a refreshed interface for editing and navigation.

- Qlik now supports modular scripts (includes/ reusable logic) in its Cloud offering, making it easier to manage complex load-logic across apps.

- The June 2025 updates introduced renamed components (e.g., Qlik Automate, Qlik Predict), enhanced machine-learning recommendations, automation limits enforcement and improved administration.

What still holds true (and where you’ll want to watch out):

- While the “story-telling” model and snapshot approach is novel and powerful, many users find Qlik still requires experienced users. If you’re hoping a business user can just jump right in, you may run into friction - despite the brand’s promise of ease, the platform often demands trained content creators or developers.

- Embedded dashboards and apps are improving, but compared to the core analytics features, embedding still tends to be more complex (especially when performance, styling or custom-UX are required).

- Pricing remains on the higher end for enterprise-grade capability, and enterprise licensing is supplied through sales rather than a public grid, so you'll need a quote for your own deployment size and usage model.

If your organisation values a “story with data” mindset, works with complex data flows, needs strong governance, script-based data modelling and is ready to invest in power and flexibility,  Qlik remains a compelling choice. If you’re after a ultra-simple drag-and-drop tool for non-technical staff and very fast time-to-value, it might still be worth comparing lighter alternatives.

Power BI - best for users in the Microsoft ecosystem

Microsoft’s Power BI is one of the most technologically advanced data analytics solutions in the market today and for a good reason. It comes with a wide range of data integrations, such as databases like Azure SQL or SQL server. It also supports a variety of local file uploads like JSON, Excel, or XML files. It’s based on a proprietary language called DAX.

It’s incredibly powerful in the right set of hands, and that’s precisely the problem. You’ll need a Power BI expert to get the most out of this tool and unlock every functionality you need for your business users. Speaking of which, Power BI embedded analytics features are fairly slow and unintuitive. 

On cost, be aware that customer-facing analytics is a separate purchase. Power BI Embedded bills through Azure capacity on a pay-as-you-go basis rather than a per-viewer fee: you pay for the selected node or SKU and its actual running time, and capacity can be paused when idle. Total cost depends on region, capacity tier and utilization, and it shouldn't be confused with Power BI Pro or Premium Per User, which are separate internal products.

If you’re already deep in the Microsoft ecosystem and you only need internal reporting, this is a solid choice. See ThoughtSpot vs Power BI for the direct comparison.

Sisense - for beginners in the world of BI

Sisense is available both on-premise and as a cloud-based BI platform with a strong reputation for usability. You don’t need to know SQL or another programming language to start since the drag-and-drop builder makes it friendly for beginners and non-technical users.
It allows you to explore data from varied sources using the Elasticube engine and plug-in a variety of data sources.

What’s new in 2026:

- Sisense has launched Sisense Intelligence, a unified suite of AI-powered analytics features: natural-language queries, automatic narrative summaries, forecasting, trend detection and explanation of drivers.

- You get "connect data from multiple sources” kind of support: over 400 connectors and live-data options.

- The new approach to analytics emphasises an Analytics Platform as a Service (AnPaaS) mindset: embedding analytics, co-authoring dashboards, collaboration.

Where Sisense still has trade-offs:

- When it comes to embedded analytics, the experience still demands significant developer input. Embedding dashboards is possible, but users often report performance or design limitations.

- If you want to analyze data in real time scenarios, setup and data-model optimization are still important. If your use case is simple dashboards for casual users, you may face unnecessary complexity.

- While great for because it allows you to explore complex data models, the learning curve for self-service may be steeper than you think,  especially if you expect zero training.

If your organisation needs a robust platform that supports advanced analytics features, connects data from many sources, and is ready for AI-powered exploration and modelling, Sisense is a strong contender. On the other hand, if your priority is quick set-up dashboards for non-technical users with minimal overhead, you might want to compare other best alternatives that prioritise speed over power.

Domo - for enterprise businesses that need all the tools in one place

Domo is a cloud-based BI platform that really aims to replace several tools at once: ETL, data-warehouse, data-visualization. You can streamline one chain instead of grabbing three different apps.

For real-time data analytics, Domo stands out. As of 2026 the platform offers an experience AI analytics layer, letting users ask questions about your data in plain English, build custom AI agents and connect data from hundreds of sources.

That being said:

- The breadth of features means Domo comes at a cost-  both financially and in setup time. Many users find that the learning curve is steep and that onboarding takes effort.

- Even though it supports advanced analytics features, the smoothness of embedding for end-users or non-technical teams can still be harder to achieve compared to more lightweight tools.

- For organisations with strict data privacy or compliance requirements, Domo offers governance, security and monitoring features. But you’ll need to ensure your implementation still aligns with your policies.

What it now offers (2026 updates):

- Domo’s platform offers AI-powered search, natural-language queries, and a semantic layer so that you can monitor key business metrics, ask questions about your data, explore complex data, and share insights more broadly.

- It allows you to connect data from multiple sources: cloud data warehouses, on-prem databases, SaaS systems, delivering a more unified analytics experience.

What to watch out for:

- Even though you can explore data and build dashboards, the tool may feel like more of an enterprise “swiss-army-knife” instead of something super lightweight for small teams.

- The cost and complexity can make Domo a heavier choice if your priority is fast time-to-value rather than full scale. Many reviews highlight “steep learning curve” and “pricing unclear.”

- While embedding dashboards and analytics is possible, for many SaaS or product-embedded use cases the implementation effort might make other platforms more attractive.

If your organisation is dealing with complex data, wants a platform designed for analytics and data products (not just dashboards), and has the budget and team to support it, Domo remains a powerful contender.

On cost, Domo uses consumption-based pricing where user seats are free and you buy a pool of credits consumed by storage, compute and product activity, typically on a one to three year contract. There's no public rate card, which is why reviews keep flagging “pricing unclear”.

There's also a corporate development to factor in. On July 22, 2026, Domo signed a definitive agreement to sell substantially all of its operating business to Progress Software for $400 million in cash. That transaction hadn't closed as of August 5, 2026, remaining subject to regulatory approvals and customary closing conditions, with closing expected before the end of Progress' fiscal year on November 30, 2026. The companies still operate separately until then, so nothing about the product has changed, but a multi-year commitment now carries more roadmap uncertainty.

If you're mostly after a simple BI tool for non-technical users, with fast setup and minimal overhead, it's worth reviewing the Domo competitors for AI-led enterprise analytics before you commit.

GoodData - for businesses that need AI features

GoodData is similar to ThoughtSpot in that it’s focused on AI-based features and advanced analytics. With this BI platform you can explore data using natural language processing and the platform offers plenty of built-in templates and dashboards - handy for beginners who want to ask questions about your data and make insights more accessible.

However: getting those AI features to work takes initial setup. You’ll need a seasoned team of developers or analysts before non-technical users can use plain English to explore real insight and start to get value from your data. In practice the steep learning curve remains.

On capability, GoodData is a genuine embedded platform rather than a repurposed BI tool: iframe embedding, Web Components and a React SDK, with white-labeling, multitenancy and role-based access controls, plus managed cloud or self-hosted deployment. That self-hosting option keeps it on shortlists for regulated industries where ThoughtSpot's managed-cloud model doesn't fit.

On pricing, transparency remains weak. The public pricing page describes Professional as a platform fee plus per-workspace pricing with unlimited users and data, and the exact figure is quote-based. Note what that means for a multi-tenant product: "unlimited users" doesn't mean unlimited workspaces or a flat total, so map how your tenants translate into workspaces first. If composable embedding is your priority, compare the GoodData competitors with composable embedding side by side.

In 2026 GoodData emphasises its AI-native analytics platform built for scale and real-time deployment, with composable architecture, the ability to connect data from multiple sources (cloud data, on-premise), and support for organisations with strict data privacy and governance.

If you’re evaluating competitors and alternatives to ThoughtSpot, GoodData is definitely one of the top alternatives to consider. It allows users, once set up, to explore data, ask questions about your data in plain language, and supports embedded workflows for end users. But if you’re after ultra-lightweight self-service BI for non-technical users without heavy setup, you may still feel the “platform offers” more than you need.

Looker - best for businesses with a heavy focus on security

Looker uses its proprietary LookML language for building dashboards and workflows. This BI tool has long been known for a rich feature set: data preparation, data modelling, predictive/advanced analytics, strong visualisations - essentially a platform designed for data and analytics.

It’s built on top of Google Cloud and offers row-level security (RLS), SSO authorisation, and a semantic layer that can serve as your source of truth. Business users often raise two recurring issues: LookML has a steep learning-curve, and embedding is more of an after-thought than a core feature.

What’s new in 2026? In 2026 Looker has stepped up. The platform now supports conversational analytics (natural-language queries) via the Gemini model and a new Conversational Analytics API. It also connects data from multiple sources including BigQuery, Snowflake, Redshift and more,  giving a more unified analytics experience. The Embed SDK has been revamped (version 2.0) to enhance embedding, though some users still find the embedding workflow less polished than the core product.

Strengths for organisations with strict data privacy/security needs:

- The data-and-analytics architecture supports multi-cloud/hybrid, meaning you can connect data from multiple sources and keep governance tight.

- With its semantic modelling layer, you get a trusted source of truth which makes value from your data more achievable.

- Named a Leader in the 2025 Gartner Magic Quadrant for Analytics & Business Intelligence Platforms, which signals the product’s maturity and enterprise credentials.

Caveats worth knowing:

- While the AI-powered search and natural language features are now part of the product, they are still early in terms of complexity — for very custom or complicated data-applications you’ll likely need data engineers.

- For embedding analytics (into your applications or for end customer portals) the experience has improved but may still lack the polish of some dedicated embedded analytics platforms.

- Pricing remains high for many businesses. Looker is sold through Google Cloud on a sales-led, annual-commitment basis at the premium end of the market, so you can't model spend without a quote. See ThoughtSpot vs Looker for the direct comparison.

- For purely simple dashboards or smaller teams of non-technical users, the learning curve (especially around LookML) may make it harder to quickly achieve self-service BI.

If your organisation has strict data privacy, high governance demands, and you’re working with complex data from numerous sources, then Looker remains one of the best alternatives in the “top BI tools” category. That said, if you’re primarily looking for embedding analytics for non-technical users, or want a very lightweight tool with minimal setup, you might want to check other options.

Warehouse-native and semantic layer alternatives

If your real objection to ThoughtSpot is that you'd rather own the semantic model than adopt someone else's, there's a category worth knowing that doesn't appear in most ThoughtSpot comparisons.

Omni combines a governed semantic model with SQL-first ad hoc exploration, which is a different answer to the same problem ThoughtSpot's search box solves. It moved seriously into embedded analytics after acquiring Explo in October 2025, and raised a $120 million Series C in April 2026 at a $1.5 billion valuation. Pricing is sales-led with no stable public grid, so it's not more transparent than ThoughtSpot on that front. If governed warehouse analytics is your priority, compare the Omni alternatives for governed warehouse analytics rather than assuming a search-led tool is the only modern option.

Sigma sits directly on your cloud warehouse with a spreadsheet-style interface, which suits analyst teams who think in formulas rather than search queries. Embedded use is more of an add-on, and embedded terms need confirming with sales.

Embeddable and DataBrain are worth a look if your interest in ThoughtSpot was purely the embedded product. Embeddable is built on native Web Components with a Cube-based semantic layer and a flat monthly custom quote. DataBrain publishes pricing, with Growth at $999 per month including unlimited seats and embeds for one data source, and Pro at $1,995 per month adding unlimited sources, SSO and permissions. Both are more predictable to budget than a sales-led enterprise quote.

Best option by user experience

Match the interaction model to who's actually using it:

• Your customers, inside your product: Luzmo. Tenant isolation and white-labeling are defaults, and end users never see a query interface.
• Internal analysts who want to ask questions in plain language: ThoughtSpot is still the strongest expression of this idea, provided you invest in the model underneath.
• Internal analysts who want visual exploration: Tableau.
• Analysts who think in spreadsheets: Sigma.
• Data teams who want to own governed metrics: Omni, or GoodData if you also need self-hosting.
• Developers assembling analytics into an existing UI: Embeddable, Sisense Compose SDK or Luzmo Flex.
• Microsoft-stack internal reporting: Power BI.

Wrapping up competitors and alternatives to ThoughtSpot

Empowering your team or users for data-driven decision-making should be one of the key goals for every business in 2026. But the business intelligence platform you choose needs to have it all: ease of use, great data integration options, superb embedding capabilities, great security, transparency and predictability in pricing, AI and machine learning tools…

Which sounds like a lot when you put it all in one sentence. But the truth is, we have a platform that offers all that and fixes the issues ThoughtSpot may be causing for you and your end-users.

Get a free demo today and find out how we can help you!