6 Best Explo Alternatives for Embedded Analytics in 2026

Explo customers have a different decision to make in 2026 than they did when they originally chose the platform.

Omni acquired Explo on October 22, 2025. Omni says Explo remains fully operational during a transition, that it intends to migrate the majority of customers onto Omni and that the Explo platform is planned to be sunset. Existing pricing stays in place through each customer's current contract, while the exact migration timing is handled customer by customer.

That makes searching for Explo alternatives less about replacing one dashboard tool with another. You are deciding whether to take the supported route to Omni or use a migration you already have to plan as a reason to re-evaluate your embedded analytics stack.

This guide compares six realistic alternatives for customer-facing analytics and explains where the Omni migration path fits.

What are the best Explo alternatives in 2026?

For SaaS product teams, the strongest Explo alternatives to evaluate are Luzmo, Embeddable, Qrvey, Reveal, GoodData and Sisense.

Luzmo is a strong fit when customer-facing analytics is the main job and you want visual authoring, developer tooling, self-service and AI in one embedded platform. Embeddable gives frontend teams more native component control. Qrvey is built around multi-tenant SaaS and deployment in your own cloud. Reveal takes an SDK-first route with fixed-pricing messaging. GoodData suits teams that put semantic governance and deployment flexibility first. Sisense belongs on enterprise shortlists that need several embedding and composability options.

Omni should be evaluated too, but it is better understood as Explo's supported migration destination than as an independent Explo alternative.

Explo alternatives at a glance

Platform	Best fit	Embedding / product model	Pricing signal	Main thing to test during migration
Luzmo	Customer-facing analytics in SaaS products	Visual authoring, SDKs and composable analytics	From €1,995/month billed annually + adoption-based usage	How quickly you can recreate tenant-aware dashboards, self-service and AI inside the existing product UX
Embeddable	Engineering teams prioritizing native frontend control	Native Web Components, developer SDKs and repository-centered workflow	Custom quote; fixed monthly subscription with unlimited usage	How much modeling and frontend implementation your team wants to own
Qrvey	Multi-tenant SaaS that wants analytics in its own cloud	Full analytics stack with JavaScript embedding, data layer, automation and AI	Flat-rate, sales-led	Deployment, data-pipeline scope and how much of the broader stack you actually need
Reveal	Teams wanting an SDK-first analytics layer	Embedded analytics SDK with customer-facing dashboards and conversational analytics	Custom quote; fixed-price positioning with unlimited end users	SDK fit, data connectivity and the amount of analytics infrastructure you keep in your own application
GoodData	Governed or regulated embedded deployments	Iframe, Web Components, React SDK and semantic modeling	Quote-based	Workspace/tenant design, semantic-model migration and deployment requirements
Sisense	Enterprise products needing several integration routes	Compose SDK plus broader dashboard and embedding options	Enterprise quote	Engineering effort, deployment architecture and the level of customization needed

Pricing and product status checked September 21, 2026. Always quote the same production scenario to every vendor rather than comparing one public starting price with another vendor's enterprise proposal.

Why are teams looking for Explo alternatives now?

The trigger is the acquisition, but "Explo was acquired" is not enough reason to switch.

Omni's transition page says the Explo product remains available while customers are moved across. It also says current Explo pricing remains unchanged through the end of the existing contract. That gives customers a supported path rather than an immediate shutdown.

The strategic change is that Explo is no longer an independent long-term product decision. If you stay on the vendor-led path, your destination is Omni. If you were already going to spend engineering time validating dashboards, permissions, customer access and commercial terms during a migration, it is reasonable to compare that work with moving somewhere else.

The right question is not "How do I avoid Omni?" It is "Which platform would we choose today if we were making the embedded analytics decision again?"

Is Omni an Explo alternative?

Not in the same way as the six products below.

Omni is the default migration path announced for the Explo customer base. It is also a credible analytics platform in its own right, with a governed semantic layer, internal BI, AI and customer-facing analytics.

That distinction matters because older comparisons sometimes describe Omni as if it still had only a light embedding story. Its 2026 product is broader. Omni has added an AI Dashboard Builder, Omni Apps and frequent AI and MCP releases, and it raised a $120 million Series C at a $1.5 billion valuation in April 2026. In September, its Explo transition page showed an Omni app running inside Claude via MCP.

For teams that want one governed layer across internal analysis, semantic modeling, AI and embedded analytics, moving to Omni may make sense. For teams that chose Explo precisely because they wanted a focused customer-facing analytics product, the acquisition is a useful moment to compare specialized alternatives too.

If your real question is which tools can replace Omni itself, see our separate Omni Analytics alternatives guide rather than mixing the two intents.

1. Luzmo: for product teams that want embedded analytics to stay the primary job

Luzmo is built around analytics delivered inside software products. Product and data teams can create dashboards visually, while developers can use SDKs and composable components when the experience needs to go deeper into the host application.

For an Explo customer, that makes the migration discussion familiar. You still need to map data connections, tenant rules, dashboards, end-user permissions and any self-service workflows, but you are moving to another platform whose center of gravity is customer-facing analytics rather than a broader internal BI estate.

Luzmo's current Embedded Everywhere plan starts at €1,995 per month, billed annually. The full product includes white-labeling, end-user self-service, governed AI and APIs, rather than reserving them for a higher tier. Pricing combines a platform fee with adoption-based usage, measured through monthly active users, AI conversations or both.

That pricing model will not be best for every workload. If unlimited usage under one fixed commercial fee is your leading requirement, compare it directly with Embeddable, Qrvey and Reveal. If you need one semantic platform to run both internal BI and customer-facing analytics, Omni or GoodData may be a better architectural comparison.

Best fit: SaaS teams whose analytics is a customer-facing product feature and that want a mix of visual authoring, developer control, multi-tenancy, self-service and AI.

For a broader market view, see our embedded analytics tools guide, our current embedded analytics pricing comparison, or Luzmo pricing directly.

2. Embeddable: for teams that want more frontend ownership

Embeddable is one of the closest category matches for teams that liked Explo's focus on customer-facing analytics but want developers to own more of the experience.

Its model centers on native Web Components, developer SDKs and extensibility. Embeddable's live pricing page says it uses a flat monthly subscription with unlimited usage, all features and white-labeling included, with the final quote based primarily on project scope rather than MAUs, dashboard views or query volume as the main pricing driver.

The trade-off is ownership. More frontend and repository control can be exactly what a product engineering team wants, but it also means you should test how much work moves into your own frontend and data teams.

During an Explo migration, build one real workflow rather than a sample dashboard. Include routing, shared filters, two tenants, role-based access, mobile behavior and a dashboard change that has to move through staging into production.

Best fit: engineering-led SaaS teams that want analytics to feel native and are comfortable owning more implementation detail.

Our separate Embeddable alternatives guide goes deeper into its component and governance model.

3. Qrvey: for multi-tenant SaaS that wants a larger analytics stack

Qrvey positions itself specifically around analytics for multi-tenant SaaS. Its platform combines data pipelines, a multi-tenant data layer, dashboards, self-service, automation, governance and agentic AI. It also advertises deployment in the customer's own AWS, Azure or GCP environment.

Commercially, Qrvey uses flat-rate positioning rather than per-seat or per-tenant charges. Its public site describes unlimited users, dashboards and tenants under a flat platform fee, although the actual contract is still sales-led.

This makes Qrvey interesting when the Explo replacement project is also an opportunity to rethink the data and analytics infrastructure around the embed. It is less compelling if you want the smallest possible layer between an existing analytics-ready database and your frontend.

Best fit: SaaS companies where multi-tenancy, deployment control and a broader full-stack analytics layer matter more than keeping the replacement narrowly scoped.

4. Reveal: for teams that want an SDK-first replacement and fixed-cost model

Reveal takes a developer-oriented SDK route. It markets customer-facing dashboards, self-service and conversational analytics as components that product teams integrate into their applications.

Its pricing message is deliberately simple: one fixed commercial rate with unlimited end users and dashboards. The exact price is not published, so the important step is getting the same 12- and 36-month workload quoted alongside the other finalists.

Reveal is worth testing when your Explo implementation is engineering-owned and you prefer a toolkit-style boundary over a larger analytics platform. The proof of concept should cover more than rendering charts. Test authentication, tenant filtering, dashboard creation, export behavior, mobile states and any AI workflow you expect customers to use.

Best fit: teams with developer capacity that want an SDK-first embedded layer and prefer fixed-pricing economics.

5. GoodData: for semantic governance and deployment flexibility

GoodData is a stronger fit when the migration is driven as much by governance as by frontend analytics.

Its developer stack includes iframe embedding, Web Components and a React SDK. The platform has long supported multi-tenant distribution and a semantic modeling layer, which can be useful when many customer workspaces need to share governed metrics.

That also means an Explo migration can involve more architecture work than copying dashboards. Model how tenants map to workspaces, where metric definitions live, how permissions flow into embedded components and which team will own the semantic layer after launch.

GoodData becomes especially relevant when deployment or regulatory requirements rule out a simpler managed-only setup. If your requirement is mainly to ship customer-facing dashboards quickly with a smaller platform footprint, a more focused embedded option may involve less operational change.

Best fit: organizations where governed metrics, multi-tenant architecture or deployment requirements carry as much weight as dashboard authoring.

Our GoodData competitors comparison covers the platform in more detail.

6. Sisense: for enterprise teams that need composability and several embedding routes

Sisense belongs on the shortlist when the Explo deployment sits inside a larger enterprise analytics program.

Its Compose SDK offers a code-driven way to query data and build analytics experiences using React, Angular or Vue. Teams can combine programmatic charts, filters and queries with existing Sisense content rather than being limited to one dashboard embedding method.

That flexibility comes with a larger platform and enterprise procurement process. For a team moving away from Explo, the question is whether you need that breadth or would be paying for architecture that the customer-facing use case does not require.

Run the proof of concept with the actual frontend framework, authentication model and performance profile you plan to ship. The value of a composable SDK is difficult to judge from a feature matrix alone.

Best fit: enterprise software companies that want component-level development options alongside a broader analytics platform.

For a deeper look at the field around it, see our Sisense competitors guide.

What should you test before migrating from Explo?

Do not run six vendor demos and compare screenshots. Use one migration-shaped test for every finalist.

Test	What to prove
Dashboard parity	A representative KPI, time series, table, filter, drilldown and export can be rebuilt without losing required behavior
Tenant isolation	Two real tenant patterns and at least two roles cannot see or infer one another's data
Embedded UX	Analytics inherits the product's navigation, state, themes, responsive behavior and error states cleanly
Self-service	Customers can create, edit, save and share only the content they are supposed to control
AI governance	Natural-language answers use the same metric definitions, permissions and tenant boundaries as dashboards
Release workflow	A dashboard or model change can move through development and staging and be rolled back safely
Commercial scale	Pricing is modeled at current adoption, expected 12-month usage and a high-growth scenario
Migration support	Ownership is clear for exports, rebuilds, validation, customer cutover, support and rollback

A migration vendor should be able to explain which assets can be moved, which must be recreated and which behaviors will change. Get that mapping in writing before treating any quoted migration timeline as meaningful.

How to move from Explo without turning it into a customer-facing project

The safest migration is boring from the customer's point of view.

Start with an inventory of what is actually in production: dashboards, report-builder flows, exports, data connections, customer groups, tenant filters, authentication, themes, scheduled delivery and any API or AI functionality.

Then rebuild one representative tenant in the shortlisted platform. Do not migrate the easiest dashboard first. Pick one that exercises the permissions and product interactions that would expose an architectural mismatch early.

Once the destination passes that test, migrate in batches and keep the old and new experiences available internally long enough to compare outputs. Validate data and permissions before UX polish. Customer-facing design differences are visible; tenant leakage is much worse.

Finally, define the cutover and rollback before launch. A migration is not finished when the new dashboard renders. It is finished when the team knows what happens if data, permissions or performance behave differently under real customer load.

Which Explo alternative should you shortlist?

Start with the reason you bought Explo.

If the goal was fast customer-facing analytics with a product-team workflow, compare Luzmo first. If frontend ownership is the priority, test Embeddable. If multi-tenancy and running a broader analytics stack in your own cloud are central, Qrvey deserves a place. Reveal is worth testing for an SDK-first fixed-price model. GoodData makes more sense when semantic governance or deployment constraints lead the architecture. Sisense fits enterprise teams that need several development and embedding routes.

And keep Omni in the same proof of concept if its broader governed analytics model is genuinely useful to your company. The acquisition is a reason to evaluate the decision again, not a reason to dismiss the acquiring platform without testing it.

The bottom line

Explo has not simply disappeared. Omni is supporting a transition and intends to move most customers onto its own platform before Explo is sunset.

But a required migration changes the economics of staying put. Once your team already has to validate dashboards, permissions, customer workflows and future pricing, the incremental cost of testing independent Explo alternatives is much smaller than it would have been a year earlier.

Use that window to compare the destination you would choose today. The right answer may still be Omni. It may be another embedded-first platform. What matters is that the decision comes from the architecture, customer experience and commercial model you need next, not only from the vendor path you inherited.