how many seconds to provision are we talking about here? 1 sec vs 60 is a dealbreaker for me, some clarity on that would be nice.

500ms. Less than 1 second. We're aiming to get that down to 200ms in the next 3 months.

This looks sick!

Did you build this for yourself?

I built this for myself because I hated running a large ElasticSearch instance at work and wanted something that would autoscale and something that allowed for reindexing data. I also had a lot of experience running a large BigTable/Elasticsearch custom graph database I thought could be unified into a single database to cut costs. Started adding an embedding index for fun based on some Google papers and now here we are!

what google papers?

Not strictly google but microsoft/bing too, here's the top ones from my notes:

https://arxiv.org/abs/2410.14452 spfresh, https://arxiv.org/abs/2111.08566 spann, https://arxiv.org/abs/2405.12497 rabitq, https://arxiv.org/abs/2509.06046 diskann,

I have a variety of blogs that I used too and reference implementations!

It's a Rabit[Q]uantized Hierchical Balanced Clustering algorithm we use for the vector index and we use a chunked segment index for the sparse index if you're curious! Happy to discuss more!

Curious if you’re using any SIMD optimizations for numerical calculations.

Yes we do use SIMD heavily! https://github.com/ajroetker/go-highway I also added SME support for Darwin for most algorithms. We use it in the full-text index, all over the vector indexes and heavily for the ml inference we do in go especially.

Glad you got it just in time!

The guy who created fastmcp, he mentioned that you should use mcp to design how an llm should interact with the API, and give it tools that are geared towards solving problems, not just to interact with the API. Very interesting talk on the topic on YouTube. I still think it's a bloated solution.