Customer-Facing Analytics
Analytics your customers actually experience as fast.
Building embedded analytics into your product means serving thousands of users, each with their own data, simultaneously. PhoenixAI is built for exactly this — multi-tenant, sub-second, at any scale.
The problem
Serving analytics to users is a different problem than internal BI.
What breaks at scale
Latency and cost blow up as users grow
- Dashboard load times degrade as concurrent users increase
- Tenant data isolation requires complex workarounds
- Pre-aggregation pipelines multiply as product features grow
- Infrastructure cost scales faster than revenue
With PhoenixAI
Fast for every user, isolated by design
- Sub-second dashboard loads at any concurrency level
- Row-level security enforces tenant isolation at the database layer
- Multi-warehouse design — isolate workloads without copying data
- Predictable cost as user count and data volume scale
Capabilities
Built for products, not just analysts.
The features that matter when analytics is a core part of your product.
Sub-second at any concurrency
Maintain consistent dashboard load times whether you have 100 or 100,000 concurrent users. PhoenixAI's architecture doesn't degrade under load.
Native multi-tenant isolation
Cell-level security enforces tenant data boundaries at query execution time. Multi-warehouse design adds hard compute isolation so noisy tenants can't starve quiet ones.
Live data in product dashboards
Your customers see data that's seconds old, not hours. Event streams feed directly into the query layer — no ETL delay between action and insight.
Build with standard SQL
Standard JDBC/ODBC, REST API, and MySQL-compatible wire protocol. Integrate PhoenixAI into your application stack without changing your query patterns.
Fits your application stack
PhoenixAI connects to the tools product engineering teams already use for data pipelines, embedding, and visualization.
Data ingestion
- Apache Kafka
- Apache Flink
- Change Data Capture
- REST API
Application integration
- JDBC / ODBC
- MySQL protocol
- REST API
Embedded analytics
- Superset
- Metabase
- Grafana
- Custom UI
In production
Real results from teams building on PhoenixAI.
10s data freshness
The migration reduced the p90 latency by 50% with only 32% of the instances required by the previous set up. This resulted in a 3-fold increase in cost-performance efficiency. The data ingestion process was also streamlined, achieving a data freshness of just 10 seconds.
Build faster analytics for your users.
Tell us your use case. We'll show you what PhoenixAI looks like for your product.