---
title: "Read AI Case Study"
description: "How Read AI runs OpenFGA at 5,200 requests per second with 20ms p99 latency over more than 5 billion relationship tuples."
canonical: "https://openfga.dev/docs/adopters/read-ai"
content_type: "documentation"
last_updated: "2026-09-03T05:50:49.000Z"
---

# Read AI: 5 billion tuples, 20ms p99 latency

[Read AI](https://www.read.ai) is the AI meeting notetaker and assistant trusted by more than 100,000 organizations and 75% of the Fortune 500, adding more than one million new customers every month. OpenFGA backs the authorization layer that lets Read AI safely share intelligence across meetings, messages, email, and documents.

## At a glance

|                         |                                        |
| ----------------------- | -------------------------------------- |
| **Industry**            | AI productivity / meeting intelligence |
| **In production since** | April 28, 2023                         |
| **Peak load**           | 5,200 RPS                              |
| **Latency**             | 20ms p99 / 1.8ms average               |
| **Tuple count**         | 5,323,283,829 (and growing)            |
| **Version**             | v1.8.16                                |
| **Storage**             | PostgreSQL                             |

## Why OpenFGA

Read AI ran a proprietary, organically built authorization system that hit performance and scalability ceilings as the platform grew. The team evaluated alternatives such as Authzed before choosing OpenFGA, citing:

- **Zanzibar foundations** that aligned with the sharing semantics the product needed.
- **Documentation clarity**, especially the practical examples and modeling guides.
- The ability to **self-host** with predictable cost.
- Approachable, responsive maintainers.

## Production at scale

The self-hosted OpenFGA service handles peak load of **5,200 requests per second** with a **20ms p99 latency** and **1.8ms average latency**. The data store holds more than **5.3 billion tuples** and grows daily.

OpenFGA upgrades are folded into a monthly cadence. The OpenFGA release pace is faster than Read AI's, but upgrades have been smooth with no significant backward-compatibility issues.

## Outcomes

- Confidence in secure data authorization across the entire product surface.
- Adoption of ReBAC best practices improved internal design decisions.
- Compute and hosting costs dropped versus the prior solution.
- OpenFGA has not been the bottleneck even at peak.

## Source

This case study is based on the public CNCF TOC adopter interview with Andrew Powers, Software Engineering Manager at Read AI, available in the [`cncf/toc` repository](https://github.com/cncf/toc/tree/main/projects/openfga).