Service
Computer vision & multimodal AI
Real-time video and image AI that's accurate — and cheap enough to run continuously.
Production vision pipelines: real-time video/RTSP analysis, deliberate vision-model selection, and motion-gating that cuts inference cost without missing events — plus multimodal builds (virtual try-on, image and video generation) on Vertex AI.
What's included
- Real-time video / RTSP analysis pipelines
- Vision-model selection (Gemini, Groq vision) for accuracy vs cost
- Motion-gating that cuts inference cost 70–90% without missing events
- Multimodal builds on Vertex AI (virtual try-on, image/video generation)
- Evidence extraction, alerting, edge / on-prem deployment
Proof
dvr_ai cuts vision-model API cost 70–90% via motion-gating; a distributed virtual try-on platform built on Vertex Virtual Try-On.
Trust, process & timelines
How do you handle our trade secrets and sensitive data?
Default to keeping data inside your boundary: VPC/on-prem deployments, no-training terms, private endpoints, and protected-branch workflows. The whole point of the Bedrock/VPC and self-hosted-embedding patterns is that sensitive code and documents never leave your control.
What are typical timelines?
An audit is ~2 weeks, a PoC sprint 2–4 weeks, and a RAG or computer-vision build 4–8 weeks depending on scope. Every fixed quote is anchored to a locked scope and a short discovery step — scope creep is what blows fixed prices.
What happens after launch?
You get the system, the eval harness and the documentation to run it. I can stay on as a fractional architect for ongoing direction and reviews, or hand over cleanly — your choice, not a lock-in.
Need computer vision in production?
Book a 15-minute call and we'll scope it properly.