What Sunbeam does, who it is for, how it differs from other voice-of-customer tools, and how your data is handled.
Sunbeam is an AI-powered experience management platform that turns unstructured customer and employee feedback into a prioritised, actionable list of issues to fix. It collects feedback from surveys, the Asklet conversational widget, continuously scraped public reviews, and any other source that can arrive via CSV, API, or webhook, then analyses everything in the same platform.
Sunbeam is built for teams that already generate meaningful volumes of open-ended feedback, typically hundreds of responses a month or more, and cannot extract clear insight from it. Typical buyers are CX and Voice of Customer leads, heads of product, and heads of people, often at companies running app stores, support queues, NPS programmes, or recurring employee surveys. Hospitality and DTC brands are particularly natural fits.
Sunbeam is AI-first and unified. Collection and analysis live in the same platform, the analysis is the core product rather than a paid add-on, deployments run in days rather than months, and the price point is a fraction of a typical enterprise XM contract. Qualtrics and Medallia remain strong choices for organisations that want a full survey suite alongside a dedicated services team to run it.
Thematic, Enterpret, and Chattermill are analysis-only platforms that assume feedback is already flowing in from somewhere else, such as Qualtrics, Zendesk, or a custom warehouse. Sunbeam also collects feedback, through surveys, Asklet, and continuous review scraping, and additionally builds an automatic system model of the product from that feedback, attaching volume, sentiment, and impact to each component.
Anything written in a free-text box. Sunbeam handles app store reviews from the Apple App Store and Google Play, reviews from Google Maps, Trustpilot, Booking.com, and Expedia, NPS and CSAT verbatims, employee pulse responses, support ticket text, conversational replies from Asklet, and any other source that can arrive via CSV upload, API, or webhook. Volume scales without per-response charges.
No. Sunbeam runs purpose-built, fine-tuned models for thematic and sentiment analysis rather than calling a generic large language model. The models cluster the same underlying issue even when customers describe it in very different words, attribute sentiment to specific topics rather than the response overall, and feed an impact model that estimates how much each issue is moving the metric you care about.
Asklet is Sunbeam's embeddable conversational feedback widget, with optional voice input. Instead of static form fields, it responds dynamically to what the user says, drawing out richer and more specific feedback than a traditional survey can. A Shopify integration makes it a particularly natural fit for ecommerce and DTC brands. The richer raw data Asklet produces also makes the downstream thematic analysis sharper.
Impact scoring is Sunbeam's estimate of how much each surfaced issue is moving the metric you care about, expressed as a concrete number such as "this checkout bug is costing you 0.56 stars in the App Store." It is the mechanism that turns the output from a list of themes into a ranked, prioritised list of things to actually fix.
System modelling is Sunbeam's automatic discovery of an ontology for your product or service, built directly from feedback with no predefined taxonomy and no manual setup. The model is made up of actors, components, and processes, each annotated with feedback volume, sentiment, impact score, trend, and example verbatims, so a team can see the structural picture of where issues are clustering and where work should go next.
Most teams see useful insight within minutes of bringing in their first batch of feedback, whether that is a CSV export, a connected app store, or a single completed survey. There is no implementation project, no taxonomy to design upfront, and no data team required, because the platform discovers structure from the feedback itself rather than waiting for it to be configured.
All Sunbeam data is hosted on AWS in the Ireland region (eu-west-1) and the platform is built to be GDPR-compliant. Data is encrypted with AES-256 at rest and TLS 1.2 or above in transit, including backups and logs. Customer data is never used to train models, never shared between customers, and never sent to third-party AI services unless the customer explicitly opts in.
