@@ -21,25 +21,30 @@ image: ./preview.png
2121
2222![ FluxNinja joins CodeRabbit] ( ./preview.png )
2323
24- We are excited to announce that CodeRabbit has acquired FluxNinja, a startup
25- that provides a platform for building scalable generative AI applications. This
26- acquisition will allow us to ship new use cases at an industrial scale while
27- sustaining our rapidly growing user base. FluxNinja's Aperture product provides
28- advanced rate-limiting, caching, and request prioritization capabilities for
29- building reliable and cost-effective AI workflows.
24+ We are excited to announce that CodeRabbit has acquired
25+ [ FluxNinja] ( https://fluxninja.com ) , a startup that provides a platform for
26+ building scalable generative AI applications. This acquisition will allow us to
27+ ship new use cases at an industrial scale while sustaining our rapidly growing
28+ user base. FluxNinja's Aperture product provides advanced rate-limiting,
29+ caching, and request prioritization capabilities for building reliable and
30+ cost-effective AI workflows.
3031
3132<!-- truncate-->
3233
33- Since our launch, Aperture's open-source core engine has been critical to our
34- infrastructure. Our initial use case centered around mitigating aggressive rate
35- limits imposed by OpenAI, allowing us to prioritize paid and real-time chat
36- users during peak load hours while queuing requests from the free users.
37- Further, we used Aperture's caching and rate-limiting capabilities to offer
38- open-source developers a fully featured free tier while minimizing abuse. These
39- capabilities allowed us to scale our user base without ever putting up a
40- waitlist and at a price point that is sustainable for us. With Aperture's help,
41- CodeRabbit has scaled to over 100K repositories and several thousand
42- organizations under its review in a short period.
34+ Since our launch,
35+ [ Aperture's open-source] ( https://github.com/fluxninja/aperture ) core engine has
36+ been critical to our infrastructure. Our initial use case centered around
37+ [ mitigating aggressive rate limits] ( ../openai-rate-limits-2023-10-23/blog.md )
38+ imposed by OpenAI, allowing us to prioritize paid and real-time chat users
39+ during peak load hours while queuing requests from the free users. Further, we
40+ used Aperture's
41+ [ caching and rate-limiting capabilities] ( ../how-we-built-cost-effective-generative-ai-application-2023-12-23/blog.md )
42+ to manage costs that in turn allowed us to offer open-source developers a fully
43+ featured free tier by minimizing abuse. These capabilities allowed us to scale
44+ our user base without ever putting up a waitlist and at a price point that is
45+ sustainable for us. With Aperture's help, CodeRabbit has scaled to over 100K
46+ repositories and several thousand organizations under its review in a short
47+ period.
4348
4449We started CodeRabbit with a vision to build an AI-first developer tooling
4550company from the ground up. Building enterprise-ready applied AI tech is unlike