Last updated 08-09-2026
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Superluminal
Superluminal adds a conversational copilot to product dashboards so end users can ask questions about their data in plain language. You integrate it through a React component or REST API, and it writes Python behind the scenes to filter tables, pivot results, plot charts, and return answers grounded in the dataset already loaded in your app. The target customer is a SaaS team that wants ChatGPT-style data chat without building code generation, sandboxed execution, and prompt tuning in house.
Generic chat widgets summarize text. Superluminal is built specifically for tabular dashboard data: it spins up managed compute to run generated Python, verifies code through reflection, and returns structured answers or charts tied to the user's actual rows. That pipeline (context synthesis, chain-of-thought reasoning, secure execution, and UI customization) is the product, not a thin wrapper around a single model call. It also supports multilingual queries and optional filtered or pivoted views of the underlying data.
Superluminal fits analytics vendors, internal data teams, and any product with an embedded dashboard that wants self-serve exploration. Pricing is pay-as-you-go at $20 per 100 messages after 50 free messages, with enterprise plans for higher volume. Data is encrypted in transit and at rest, purged after each session, and not shared with third-party LLM providers per the company's security page.
First 50 API messages are free before pay-as-you-go billing starts
Standard pricing is $20 per 100 messages with no setup fees listed
Dynamically writes and executes Python to answer questions and build charts from dashboard data
Ships a React component that embeds the copilot panel with a few lines of code
Supports plotting, filtering, pivoting, and multilingual queries across 10+ languages
Session data is purged after each use with zero persistence and no third-party LLM data sharing
Handles Python generation, sandboxed execution, and prompt tuning so dashboard teams avoid months of engineering work
Pay-as-you-go pricing starts with 50 free messages and no setup fees on Standard
React component and API options fit both quick embeds and fully custom UIs
Multilingual query support covers major global languages out of the box
Security model promises zero session persistence and no third-party LLM data sharing
Standard plan bills per message, which can add up for high-volume customer bases
Enterprise features and volume pricing require a sales conversation
Requires engineering integration; it is an API product, not a standalone analytics app
Domain authority is low, which may matter for teams evaluating vendor longevity
Is Superluminal free to try?
Yes. Superluminal includes 50 free messages on the Standard plan before pay-as-you-go billing begins. There are no setup fees or other hidden fees listed on the pricing page.
How much does Superluminal cost?
Superluminal Standard is $20 per 100 messages after the free tier. Enterprise pricing is custom for businesses with large interaction volume or unique models and requires contacting the team.
How do you integrate Superluminal into a dashboard?
Superluminal offers a React component for embedding its chat panel and a REST API for custom front ends. Documentation covers both the React tutorial and direct API usage on superluminal.dev.
Is Superluminal secure for customer data?
Superluminal states that data is encrypted in transit and at rest, purged at the end of each session, never shared with third-party LLM providers, and hosted with top-tier cloud providers in the US and EU.
What languages does Superluminal support?
Superluminal supports multilingual queries including English, Chinese, French, Hindi, Spanish, Japanese, Turkish, Polish, Korean, Thai, and additional languages listed on its homepage.
What can users ask Superluminal about their data?
Users can ask natural-language questions about tabular dashboard data. Superluminal can return ranked lists, filtered views, pivots, and charts, such as identifying top revenue products and offering to visualize the result.