Lucerna is a Slack-native analytics assistant that answers product questions directly from connected data sources using plain English. It eliminates context switching by letting teams tag the bot in existing threads, then automatically records decisions and incidents into searchable organizational memory. The platform includes a control plane for tracking usage, auditing actions, and reviewing or redacting what the org remembers.
Funding
Funding not disclosed
Founders
Product
Problem
Product teams frequently interrupt their workflow to switch between chat, analytics tools, and documentation when answering questions about metrics, past decisions, or service ownership. Critical context—such as the rationale behind technical choices or incident postmortems—gets scattered across threads and lost, forcing teams to re-answer the same questions repeatedly.
Solution
Lucerna is a Slack-native AI teammate that answers product questions directly from connected analytics data without requiring users to leave their conversation. Teams mention the bot in any thread or DM, and it queries live data to provide answers on funnels, retention, and metric changes, with results delivered in-thread. After each interaction, Lucerna automatically writes the decision, rationale, and outcome into a persistent organizational memory, making historical context queryable. A dedicated control plane gives administrators usage and cost ledgers, an exportable audit log, and tools to review, correct, or redact stored memories.
Target Audience
Primary customers are product, engineering, and data teams at mid-sized technology companies that rely on Slack for daily collaboration and need faster access to product metrics and institutional knowledge.
Features
- Slack-native interaction via mentions in threads or DMs, requiring no separate application for end users
- Plain-English querying of connected analytics tools for funnels, retention, and change detection across live data
- Automatic documentation of decisions and incidents into org memory, capturing who made the callches, the originating thread, and what has changed since
- Memory querying for questions like service ownership, on-call rotation, past incidents, and technical rationale
- Usage and cost ledger attributing every request to the specific teammate who asked
- Full audit log of all bot actions with thread context and export capability
- Memory review interface allowing admins to see, correct, or redact stored organizational knowledge
- Waitlist-based onboarding with capacity for only a few teams per week