Scuba
Winter 2013AcquiredAnalytics for impatient people.
Pressure-test this opportunity
Turn this teardown into a decision-ready prompt for ChatGPT, Claude, or your agent.
Analytics for impatient people.
Turn this teardown into a decision-ready prompt for ChatGPT, Claude, or your agent.
If you only have a few minutes to spare, here’s what investors, operators, and founders should know about Scuba (W13).
Scuba began as Interana, an attempt to turn Facebook-scale event analysis into a product that ordinary business teams could use. Its defining idea was speed as part of the interface: a user could ask a follow-up question against raw behavioral data while the question was still useful.
The ending is less clear than YC's acquired label suggests. Interana renamed itself Scuba in 2021, product documentation continued through 2025, and a 2024 patent was assigned to Scuba Analytics. The current Scuba domain redirects to Behavure AI and says Scuba is now part of that company. No announcement describing a buyer, legal structure, effective date, price, or terms was found.
Ann Johnson, Bobby Johnson, and Lior Abraham founded Interana in 2013. Bobby had helped scale Facebook's infrastructure; Lior created SCUBA, an internal tool that let employees inspect high-volume event data interactively. Ann brought operating experience from Intel.
They saw a gap between dashboards and investigation. Dashboards could show a metric had moved, but the next question often required an analyst, a new query, and a wait. Interana paired a purpose-built event store with a visual query interface so more employees could examine sequences, cohorts, retention, and conversion directly.
Interana built a distributed columnar store optimized for timestamped events, a query engine designed for fast exploratory work, and a visual interface. Instead of requiring a precomputed dashboard for every question, users could filter populations, compare cohorts, inspect sequences, and move from one question to the next.
Under the Scuba name, the product added scheduled query alerts, embedded links, configurable time comparisons, privacy deletion, and a version 5 interface. Multi-cluster controls let customers query across regions while restricting sensitive property values.
The same technical lineage now appears in Behavure AI's pitch for behavioral event correlation and AI-system monitoring. The reviewed sources do not explain whether that shift was an acquisition, reorganization, brand change, or another arrangement.
Interana targeted product managers, analysts, engineers, and business teams at companies producing large event streams. The value increased when questions changed quickly and a central data team could not build every report.
The company sat between business intelligence, product analytics, data warehousing, and observability. That created a broad market but also a demanding product boundary: customers compared it with specialized analytics tools, cloud warehouses, dashboards, and internal systems.
Interana competed with Tableau, Looker, Mixpanel, Hadoop-based stacks, and custom data platforms. Later, cloud warehouses made raw compute more accessible and product-analytics tools improved self-service exploration. Scuba's distinction remained a tightly coupled engine and interface for event questions at high scale.
The product was enterprise software, likely priced around deployment scale, data volume, or capacity. Customers needed ingestion work, identity and schema decisions, infrastructure, training, and ongoing support. Public sources do not disclose price, gross margin, revenue, retention, or current customer count.
Read the complete post-mortem, the rebuild playbook, and the exact reasons Scuba is still worth studying now.