Kubit vs June
Side-by-side trajectory, velocity, and editorial themes.
Kubit pivots from query builder to agentic analytics with the Lumos AI chat.
Kubit is a product-analytics platform that has spent the last quarter shifting from a manual report-builder model toward an agentic one. The headline move is Lumos Agentic AI Chat, which lets users describe reports in natural language instead of clicking through a builder. Alongside it, an AI Readiness framework continually scores how well a customer's metadata is prepared for that workflow.
Every directional release this quarter either ships agentic capability or removes blockers in front of it. AI Readiness keeps expanding its assessment surface (virtual events, breakdown fields) so customers can see exactly what gaps would limit Lumos. Enterprise-readiness work like granular Slack permissions and partial caching is clearing the path for production rollout rather than chasing new categories.
Expect Lumos to extend past chat into scheduled agent runs and proactive insights surfaced on dashboards, with a Slack or Teams entry point built on the new fine-grained permission model.
June's last visible push was a tight May 2025 B2B sprint — Custom Objects, SQL traits, PostHog integration.
June is product analytics for B2B SaaS, and the only visible release activity in the input is a concentrated four-week sprint in May 2025: SQL computed traits, PostHog as a data source, increased computed-trait limits, and the GA of Custom Objects after a two-month rollout. Each release is paired with small fixes (Slack alerts, HubSpot reverse sync) suggesting a stable maintenance cadence around the headline launches.
The May 2025 batch is internally consistent: every release widens what June can model (Custom Objects), how flexibly customers can compute on it (SQL traits), or how easily it slots into existing data plumbing (PostHog source). All three target the B2B-SaaS persona that wants more than user/account analytics. After this burst the changelog goes quiet in the input — it's not clear from the entries alone whether the product moved to a slower cadence, switched publishing channels, or paused.
The entries don't support a confident prediction about what comes next. If publishing resumes from the same direction, the obvious extensions are deeper integrations with reverse-ETL or warehouse-native sources and richer pre-built health-score templates on top of SQL computed traits.
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