Your SaaS product needs customer-facing analytics. Your customers are asking for dashboards, usage reports, and performance insights, and you know that bolting on a basic charting library is not going to cut it. So you went looking for an embedded analytics platform, and Explo kept coming up. 

It’s quick to implement with minimum coding and has decent visualization.

But now the ground has shifted. Explo was acquired by Omni Analytics in October 2025 and is being dismantled. If you are an existing Explo customer, you are being migrated to Omni whether you chose it or not. 

And if you are evaluating embedded analytics software for the first time, Explo is no longer a long-term option.

That raises a more urgent question: what should you actually build your embedded analytics on? 

This article compares Astrato and Explo across architecture, embedded capabilities, AI, and pricing so you can see what Explo did, where it fell short, and why Astrato is the stronger path forward for teams that need customer-facing analytics that scale.

Quick Comparison: Astrato vs Explo

What Is Astrato?

Astrato is a warehouse-native BI platform that delivers embedded analytics, internal dashboards, and AI-powered insights from a single platform, all running live on Snowflake, BigQuery, or Databricks.

Built for the cloud native era and the modern data stack, Astrato leverages the data cloud to provide scalable, real-time analytics and modern BI capabilities for organizations adapting to a cloud-first world.

For embedded use cases specifically Astrato lets you drop fully white-labeled dashboards, individual charts, or groups of visual objects directly into your SaaS product, customer portal, or internal tools.

Every embed runs live against your warehouse, so customers always see current data without refresh delays. Astrato uses a pure pushdown architecture that runs queries directly against the live warehouse, with no staging tables or hidden compute surprises, ensuring real-time analytics without data movement.

Astrato's architecture ensures that data never leaves the warehouse, maintaining security and compliance with industry standards. This centralized approach also reduces duplication by allowing shared logic and governance across all analytics assets.

The no-code drag-and-drop builder means your analytics team (not just engineers) can design, customize, and ship customer-facing dashboards without writing code. Astrato's no-code execution layer allows users of any technical skillset to consume and act on data in real time.

Astrato also offers a built-in AI Copilot that lets end users ask questions in natural language and get instant visualizations.

Writeback capabilities allow users to update forecasts and trigger workflows directly inside dashboards. Astrato treats every dashboard as a living application that can execute actions directly from the analytics layer, streamlining analytics workflows and enabling automation of business processes.

Built-in telemetry tracks how your customers actually use the analytics you ship, so you can optimize adoption and prove ROI. Astrato helps close the gap between data insights and action by enabling real-time, interactive data apps that empower decision-making.

What Is Explo?

Explo is a specialized embedded-analytics platform designed to help SaaS companies embed dashboards, reports, and data visualizations into their own products. Its core value proposition is speed of implementation: product and engineering teams can spin up customer-facing analytics with minimal coding and ship them in days.

Explo offers a dashboard builder, white-label styling, and pre-built components that reduce development time. It runs live SQL queries against the source database, and its SQL-first approach gives developers direct control over data modeling. 

However, traditional BI tools and modeling approaches often lead to duplication of effort, as teams must rebuild similar relationships, calculations, and data joins across multiple dashboards. While Explo and Sigma attempt to address this with reusable datasets and shared logic, they still face challenges in creating a fully unified system.

Explo also introduced an AI Report Builder that lets users generate dashboards from natural-language prompts, and a free AI visualization builder for quick CSV-based visualizations.

Despite these features, there remains a gap between data insights and effective action in traditional reporting, and Explo’s approach may not fully close this gap, especially for teams seeking integrated, real-time, and storytelling-oriented reporting. Explo and Sigma both have limitations in scalability, flexibility, and presentation, particularly when compared to modern, cloud-native BI platforms. Legacy BI tools and some modern platforms can also be slow due to data silos, fragmentation, and lack of real-time access, which impacts analytics speed and decision-making.

Explo offers a dashboard builder, white-label styling, and pre-built components that reduce development time. It runs live SQL queries against the source database, and its SQL-first approach gives developers direct control over data modeling. 

Explo also introduced an AI Report Builder that lets users generate dashboards from natural-language prompts, and a free AI visualization builder for quick CSV-based visualizations.

However, Explo is purpose-built for embedded analytics only. It is not a full BI platform for internal analytics, lacks writeback and operational workflow capabilities, and its AI is positioned as an add-on to its embedded suite rather than integrated across a full BI layer. 

Use Case Comparison

Customer-Facing Embedded Analytics

This is the use case Explo was built for and where the comparison matters most for teams evaluating alternatives.

Astrato delivers fully white-labeled embedded analytics where you control every detail of the look and feel. You can embed a single visualization, a group of objects, or a complete dashboard into your SaaS app, customer portal, or website. 

Every embed pulls live data from the warehouse, so customers see real-time insights without manual refreshes. 

The no-code builder means your BI team can design and iterate on customer-facing dashboards without pulling engineering resources. And with built-in telemetry, you can track exactly how customers engage with the analytics you ship.

Explo offers a similar embed-and-white-label workflow with pre-built components and a style editor. Users praise the intuitive builder and fast time-to-deployment. 

However, anything beyond basic dashboards requires SQL expertise, the visualization library is limited, and there is no built-in usage tracking. And with Explo now being discontinued, the platform is a short-term solution at best.

Internal + External on One Platform

Astrato runs both internal BI and customer-facing embedded analytics on the same warehouse foundation. One platform, one governance model, one source of truth. For organizations that need both, this eliminates the dual-stack complexity of running Explo for external embeds and a separate BI tool for internal reporting.

Explo does not handle internal BI at all. Teams using Explo always needed a second tool for internal analytics.

Operational Workflows and Writeback

Most BI tools treat analytics as read-only. 

Astrato breaks that pattern with writeback capabilities that let users update forecasts, trigger approval workflows, and make operational adjustments directly inside dashboards. This turns business intelligence from a reporting layer into an operational tool.

Explo does not support writeback. Analytics are consumption-only: users view dashboards but cannot interact with data in a way that feeds back into business processes.

AI-Powered Analytics

Astrato’s GenAI module plugs directly into dashboards. It automatically highlights trends, anomalies and key drivers, to give contextual insights without manual digging. Insights can be delivered on screen or via email and chat channels.

Users can type questions like “What’s driving sales growth this quarter?” and the BI Copilot fetches the data, applies filters and produces the appropriate visualisation. 

Astrato’s AI is integrated across its warehouse‑native BI platform, helping both internal and external users explore data, build dashboards and trigger workflows.

Plus, organisations bring their own large language models through Snowflake Cortex or Azure OpenAI.

Explo introduced an “AI Report Builder” that lets users generate dashboards and reports by typing natural‑language prompts and create AI summaries. Explo’s AI assistant allows non‑technical users to converse with their data and receive tailored answers. 

For quick visualisations, Explo offers a free AI visualization builder where users upload a CSV file, type a prompt and receive an automatically generated block.

Explo positions its AI as an add‑on to its embedded analytics suite—useful for generating customer‑facing reports but not a replacement for a full BI layer.

Architectural Differences: Warehouse-Native vs Embedded-First

1. Data Execution Model

Astrato and Explo both avoid the extract-cache-reload cycle that plagues legacy BI tools like Tableau or Power BI, but they do so for very different reasons and at very different scales.

Astrato treats your cloud data warehouse as the single compute and governance layer. Every dashboard query runs live on Snowflake, BigQuery, or Databricks. Because the warehouse handles compute, Astrato inherits the performance, scalability, and cost controls you have already built into your cloud infrastructure. 

There are no extracts to manage, no reloads to schedule, and no stale data windows.

Explo also runs live queries, but against the source database directly rather than through a warehouse-native integration. Several reviewers note that Explo has no caching layer, which means performance tuning is less controllable and multi-tenant scaling requires careful planning. 

For a SaaS team looking to embed a few dashboards this may be acceptable, but for enterprise-scale analytics it becomes a constraint.

2. Governance and Logic Location

Where business logic lives is one of the most important architectural decisions in modern analytics, and this is where the two platforms diverge sharply.

Astrato keeps governance in the warehouse. The semantic layer, RBAC policies, dbt models, security, and auditability controls all stay where your data platform team has defined them. 

Dashboards consume governed data rather than duplicating logic inside visualization layers. This means a single source of truth across every report, dashboard, and AI-generated insight.

Explo governs data at the dashboard and dataset level through SQL. Dataset modeling happens within Explo itself, and you need SQL proficiency to define and manage data relationships. 

Community feedback consistently highlights this as a barrier: one reviewer noted that unlike tools such as Sigma, Explo requires strong SQL skills for data manipulation. 

For teams without dedicated SQL expertise, this creates bottlenecks rather than self-service.

3. Performance and Cost Predictability

This is a high-intent comparison point for teams evaluating BI modernization.

Astrato offloads compute to the warehouse, which means you pay for warehouse usage rather than blurred per-user or per-dashboard fees that balloon as adoption grows. Performance scales with your warehouse tier, and cost is predictable because you control the compute layer directly.

Explo pricing starts at roughly $1,995 per month and scales based on the number of embedded dashboards or end users. Multiple reviewers describe this as expensive for early-stage teams, and several sources caution that costs can grow quickly as customer bases expand. 

Because Explo runs queries directly against the source database without caching, performance tuning is limited and depends heavily on database optimization outside of Explo itself.

Who Should Choose Astrato?

Astrato Is Best For:

• SaaS and product teams that need white-labeled, customer-facing embedded analytics at scale
• Organizations that want internal BI and embedded analytics on one platform instead of two
• Teams running on Snowflake, BigQuery, or Databricks who want analytics that run live on the warehouse
• Companies using dbt, semantic layers, and warehouse governance who need embeds that respect those workflows
• Teams that want AI-powered insights integrated across their entire analytics layer, not bolted on
• Organizations that need scheduled reporting, writeback, and telemetry in their embedded dashboards. Astrato offers a framework to build interactive data apps with buttons and triggers to launch workflows.

Explo May Have Been a Fit For:

• SaaS teams needing basic embedded dashboards shipped quickly with minimal engineering lift
• Teams with strong SQL expertise that only needed embedded analytics and had a separate internal BI tool

When to Switch from Explo to Astrato

If you are an Explo customer today, the decision is no longer optional. Explo is being discontinued, and your team will be migrated to Omni. But before you accept that default path, consider whether Astrato is a better fit:

• You want embedded analytics that run live on your warehouse, not on a third-party query layer
• You need internal and external analytics on one platform instead of managing two solutions
• Your team is investing in warehouse governance, dbt, and semantic layers and wants embeds that align
• You want AI-powered insights included in your entire BI, not just for report generation
• Writeback, scheduled reporting, and usage telemetry are on your embedded analytics roadmap
• You want predictable costs that scale with warehouse compute, not per-dashboard pricing

Explo Is Now Omni. Here’s Why You Should Consider Astrato Instead

With Explo’s acquisition, existing customers are being migrated to Omni Analytics, a BI platform that combines internal analytics with embedded capabilities. Omni has strong foundations: it was built by former Looker engineers, offers a proprietary semantic data model, and supports dbt integration. It is a capable internal BI tool.

But for teams whose primary need is embedded, customer-facing exploration, the comparison with Astrato reveals important gaps.

Embedded Analytics: Native vs Layered

Omni’s embedded analytics are layered on top of its internal BI artifacts. Dashboards are embedded via iframe or secure links, and multiple technical comparisons note that Omni’s embeds retain the platform’s own layout and interaction patterns with limited pixel-level control. Deep UI customization and product-level integration are more constrained than in purpose-built embedded tools.

Astrato was designed for embedded analytics as a core use case from the start. You can embed single visualizations, object groups, or fully white-labeled dashboards with complete control over styling, branding, and user experience. Embeds feel native to your product, not like a BI tool dropped into an iframe.

Warehouse-Native Architecture

Both Astrato and Omni connect to cloud data warehouses. 

However, Astrato’s architecture is cloud-native: every query, every dashboard, every AI insight runs directly on your warehouse. Governance, compute, and cost control stay where you have already invested. 

Omni uses its own in-database and in-memory caching layer, which adds performance benefits for internal BI but also introduces an additional layer between your warehouse and your end users.

AI Integration

Astrato’s GenAI is integrated across the full platform, with a BI Copilot, automated insight generation, trend and anomaly detection, and BYO LLM support via Snowflake Cortex and Azure OpenAI. 

Omni also offers AI-powered querying, but its AI capabilities are still developing and reviewers have noted that advanced predictive analytics features are less mature than some competitors.

Writeback and Operational Workflows

Astrato supports writeback natively: users can update forecasts, input data, and trigger workflows inside dashboards. This applies to both internal and embedded use cases. Omni offers a Data Input feature for adding external data, but it does not provide the same depth of operational writeback that Astrato delivers.

Customer Stories

PetScreening, the leading pet policy management software serving over 24,000 property management firms, was struggling with manual reporting that couldn't scale. Customers demanded real-time, self-service insights, but their legacy BI tool required specialized skills and was too costly to extend to thousands of end users. 

After switching to Astrato, PetScreening embedded self-service dashboards directly into its customer-facing platform, running live on Snowflake. 

The result: 75%+ cost reduction in BI, customers who can explore data and export reports without SQL, and a path to doubling their user base. As their Director of BI put it: "Astrato is helping us win new customers. We are on target to double the number of units this year."

IAG Loyalty, a leader in customer loyalty programs, has harnessed the power of Astrato Analytics to elevate its customer-facing analytics. By embedding Astrato’s analytics directly into its SaaS product, IAG Loyalty provides customers with real-time insights and personalized recommendations that drive engagement and foster loyalty. 

Now, IAG Loyalty’s customers can access actionable analytics within the same platform they use every day, eliminating friction and enabling data-driven decision-making at every touchpoint.

The result is a more dynamic and interactive customer experience, where users can explore data, uncover trends, and receive tailored insights without leaving the application. 

Frequently Asked Questions

Is Astrato better than Explo for embedded analytics?

Yes, for teams that need embedded analytics at scale. Astrato Analytics offers fully white-labeled embeds, AI-powered insights, writeback, and built-in telemetry, all running live on your warehouse. Explo covered basic embedded dashboards well but lacked internal business intelligence, writeback, and deeply incorporated AI insights. And with Explo now discontinued, Astrato is the stronger long-term choice.

What happened to Explo?

Explo was acquired by Omni Analytics on October 22, 2025. The Explo product is being discontinued, and existing customers are being migrated to Omni over a 12-month transition period. During this time, Explo continues to function as-is, but no new development is planned.

Does Astrato support white-labeled embedded dashboards?

Yes. Astrato lets you embed a single table, graph, groups of objects, or fully branded dashboards into your software product, customer portal, or internal tools. Every embed is fully customizable to match your product’s look and feel.

Does Astrato use live queries?

Yes. Astrato queries your warehouse live. It connects directly to all your live data so both internal and embedded dashboards always reflect current data without scheduled reloads or extract jobs.

How does Astrato compare to Omni for embedded analytics?

Omni is primarily an internal business intelligence platform with embedding capabilities layered on top. Astrato was designed for embedded analytics as a core use case. Astrato offers deeper white-label customization, native writeback, integrated GenAI with BYO LLM support, and built-in usage telemetry. See the full comparison in the Omni section above.

Does Explo support AI-powered analytics?

Explo introduced an AI Report Builder for generating dashboards from natural-language prompts and a free CSV visualization builder. However, Explo’s AI functions as an add-on to its embedded analytics suite. Astrato’s AI is integrated across the full platform, with a BI Copilot, automated insights, and BYO LLM support via Snowflake Cortex and Azure OpenAI.

Who should use warehouse-native embedded BI?

Teams that have committed to Snowflake, BigQuery, or Databricks as their single source of truth and want customer-facing analytics that leverage warehouse compute, governance, and cost controls. This includes SaaS companies building data products, organizations modernizing from legacy business intelligence, and teams adopting dbt and semantic layer workflows.

Final Verdict: Astrato or Explo

Explo served a real need: fast, embeddable customer-facing dashboards for SaaS teams. But with its acquisition and discontinuation, that option is off the table. The question is no longer whether to stick with Explo. It is where to go next.

If you are being defaulted into Omni, take the time to evaluate whether a platform built for embedded analytics from the ground up might be a better fit. Astrato delivers white-labeled embedded dashboards, internal business intelligence, AI-powered insights, writeback, and usage telemetry, all running live in your warehouse. One platform, one source of truth, no compromises.

Ready to see how Astrato delivers embedded analytics directly on your warehouse? Book a demo.