G2

Girish V.

Chief Data and AI Officer

Mid-Market (51-1000 emp.)

6/23/2026

"White-box access and dedicated compute to run multimodal AI at scale"

5/5

What do you like best about Neysa Velocis?

The thing that mattered most to us was getting real control over the serving stack. On the big cloud APIs we were locked out, we couldn't see hardware logs, couldn't tune the model the way we needed, couldn't diagnose latency. Neysa gave us root-level access to dedicated compute, so our engineering team can actually monitor and troubleshoot the system underneath. The hands-on engineering support has been just as valuable, they got into the detail with us to get our setup production-ready Review collected by and hosted on G2.com.

What do you dislike about Neysa Velocis?

Getting the stack tuned for our specific multimodal workload took real work upfront, recognising our store signboards, product stickers, and stamped job sheets reliably. The Neysa team was hands-on throughout, but it's a setup that needs engineering investment rather than something you switch on out of the box. Review collected by and hosted on G2.com.

What problems is Neysa Velocis solving and how is that benefiting you?

We verify 7,000+ field service reports a day across 50,000+ merchant stores. These image and documents need a quick review as an agent is standing in the store waiting on the result before they can move on, so we need the verification back in seconds. On a general-purpose cloud, latency fluctuated with network traffic and token costs climbed with volume, which would have broken our unit economics at scale.

Running a custom Qwen 3.0 VL model on dedicated Neysa compute, we now process those reports in under 30 seconds at 96% accuracy, and a flat dedicated-compute model cut our total cost of ownership by 60%. That predictability is what let us scale the audits. Review collected by and hosted on G2.com.