Products

PhoenixAI Cloud Fully managed. Cloud or self-hosted. Pricing Flexible plans for every scale.

Use Cases

AI & Agents Real-time data for agentic AI workloads. Real-Time Analytics Sub-second queries on live data streams. Customer-Facing Analytics Embedded analytics built for your product. Lakehouse Analytics Query Iceberg and Delta Lake at sub-second speed.

Industries

Finance & Banking Logistics & Transportation Manufacturing Healthcare Retail & E-Commerce Energy & Utilities Telecommunications Public Safety & Government

Comparisons

PhoenixAI vs. Databricks Real-time OLAP vs. batch-first lakehouse. PhoenixAI vs. ClickHouse Managed, governed, and built for AI workloads. PhoenixAI vs. Snowflake Real-time freshness vs. warehouse latency.

Learn

Blog AI agents, real-time analytics, and data engineering. Docs Full technical documentation. Glossary Key terms in real-time analytics and AI data.

Assets & Events

Whitepapers Deep technical reads on performance and architecture. Events Conferences, meetups, and online sessions. Customer Case Studies Real-life customers stories of how they transformed their data stack.

Latest whitepaper

Real-Time Analytics for Customer-Facing Applications Whitepaper

Analytics is no longer just a tool for internal decision-makers.

Download free

About

About PhoenixAI Who we are and why we built this. Partners AWS, Confluent, Databricks, and more. Newsroom Press coverage and announcements.

Join us

Careers Open roles at PhoenixAI. Contact Talk to our team directly.

Customer story

How Coinbase cut dashboard load time from 8s to 80ms

Real numbers from a production deployment at scale.

Read the story

Industry / Retail & E-Commerce

Personalization agents
acting in the moment.

A customer’s intent changes session by session. Inventory positions shift by the minute. Contact center sentiment moves in real time. PhoenixAI gives your AI agents the live data access to act on all of it — before the moment has passed.

Book a demo See the product

<1s

Session event to personalization

Live clickstream ingestion

10K+

Concurrent user sessions

Sub-second query latency

2s

Dashboard load time

Down from 5 min (game studio)

The problem

Real-time data gaps have real consequences.

Without real-time data

Recommendations based on yesterday’s behavior

Personalization models trained on batch data — hours behind current session behavior
Inventory counts update overnight, leading to oversell and stockout surprises
Contact center analytics available only in next-day reports
Promotions triggered after the purchase window has already closed

With PhoenixAI

AI agents reacting to what customers are doing now

Personalization agents query live clickstream data within one second of each event
Inventory agents detect low-stock signals in real time and trigger replenishment
Contact center agents monitor sentiment live and surface issues before churn
Promotional agents activate based on current cart state and browsing behavior

Use cases

Where PhoenixAI makes the difference.

Real-time personalization

AI agents query live session data — page views, searches, cart events — to serve relevant recommendations and offers in the moment, not based on yesterday’s model run.

Agentic AI

Inventory intelligence

Point-of-sale and warehouse streams update inventory positions continuously. Agents detect stockout risk the moment velocity signals diverge from available stock.

Agentic AI

Contact center analytics

Live monitoring of contact center conversations and tickets. Agents surface recurring issue patterns and escalation signals before they impact CSAT scores.

Real-time

Works with your retail data stack

Standard SQL. No proprietary query language.

Apache KafkaApache FlinkApache IcebergDelta LakeTableauLooker

Serve customers based on what they’re doing right now.

Meet with our solutions team for a live product walkthrough.

Book a demo See the product