VIDIZMO for NVIDIA Teams: Pull-Through Field Guide

A field guide for NVIDIA account executives, solution architects, partner and Inception managers, and OEM and channel teams. It follows Priya, an NVIDIA solution architect, as she turns one GPU conversation into a running VIDIZMO deployment: AI Live Insight for vision agents on the cameras customers already own, AI Intelligence Hub for agents across video, audio and documents, and Redactor with Nexus for releasing only what is allowed.

It shows where VIDIZMO sits on DeepStream, TensorRT, NIM and CUDA, the deployment options from the customer's own cloud to fully air-gapped, the industries to target, a play for every NVIDIA role, and how VIDIZMO is bought through Carahsoft, TD SYNNEX, CDW-G and SHI. Learn more at https://vidizmo.ai/partners

Transcript

If you sell, architect or partner at NVIDIA, this is a short field guide to VIDIZMO: an NVIDIA Inception member whose applications run on DeepStream, TensorRT, NIM and CUDA, and turn the GPUs your customers buy into work they run every day. NVIDIA's priorities this year point one way. Agentic AI that reasons and acts. Physical AI and vision agents that watch the real world. Sovereign and on-premises AI for regulated buyers. And RTX PRO servers moving into the enterprise data center. Each one needs an application on top before the GPU earns its keep. Here is the gap you meet in accounts. The customer likes the blueprint but has no developers to build on it. Their data is video, audio and documents that cannot leave the building. Security wants one permission model and one audit trail. And procurement wants a contract vehicle they already use. Meet Priya, an NVIDIA solution architect covering state government, health systems and manufacturers. Let's follow how she uses VIDIZMO to turn one GPU conversation into a running deployment. Start with where VIDIZMO sits. The video pipeline runs on DeepStream, with RTSP and ONVIF cameras. TensorRT optimizes the detection models. Language and vision-language serving is standardizing on NIM microservices. Everything scales on NVIDIA GPUs and CUDA, and VIDIZMO Nexus and its products sit on top. Customers ask how this relates to the video search and summarization blueprint. The blueprint gives developers a reference for building vision agents. VIDIZMO gives the customer applications they can deploy on the same NVIDIA foundation, with access, sharing, permissions, single sign-on, retention and audit as part of the platform. First play: physical AI on the cameras customers already own. This is AI Live Insight on live video. On the machine floor, people and equipment are detected as they move. Outdoors, a fire is flagged the moment it starts. In the warehouse, missing protective gear is flagged on each worker. Rules are built without code. On this street camera, object detection feeds a wrong-direction check, and the zone it watches is drawn on the image. Each rule is a graph the customer can change without a developer. In the control room, cameras with active alerts move to the top, and every flag is listed beside them. Every alert is saved with its clip and is searchable by camera, type and time. For Priya, each of these streams is GPU work: decoding, detection and tracking, around the clock. Second play: agentic AI across video, audio and documents. In AI Intelligence Hub, anyone can ask a recording a question. Here a user asks what is happening on a street camera, and the answer describes the fire, the people and the time. Agents are assembled as no-code graphs. This one reads incoming documents, routes each one to its department, and applies that department's redaction rules. The model behind any step can be changed in configuration, including a NIM running on the customer's own GPUs. Answers can be shared with colleagues. Here an investigator opens a shared thread and asks for a case summary. Every question is an inference call, and agents working in the background add more. Third play: regulated content, released only as allowed. Redactor removes personal, health and payment data. Here is a report with names, an ID number and an address, and then the same report, redacted and ready to release. Release goes out as a limited share, with a secure link and an expiry date set by the person sharing it. This is where the GPU lands. VIDIZMO runs in the customer's own cloud tenancy, on premises, in FedRAMP High environments through Project Hosts, in sovereign and hybrid setups, and fully air-gapped, with no outbound dependency for inference, licensing or updates. Now, where to point it. Priya targets the industries where NVIDIA's priorities and VIDIZMO's customers overlap. Public safety and justice, for evidence, investigations and live camera analysis. Government and smart cities, for transit, records and public requests. Healthcare, for clinical media and protected health information. Financial services and legal, for fraud, compliance and discovery. And manufacturing and energy, for safety monitoring on the plant floor. Every role at NVIDIA has a play. Account executives bring VIDIZMO into accounts that own GPUs but have no application on them. Solution architects size the build from camera streams, redaction volume and language model concurrency. Partner and Inception managers bring VIDIZMO into co-sell. And OEM and channel managers pair it with Dell, HPE, Supermicro and Lenovo GPU systems in joint offers through distribution. Here is how NVIDIA earns from each deployment. On premises and air-gapped, the customer owns the GPUs, with production builds recommended on RTX 5090 or RTX 6000 Blackwell cards. In the customer's cloud and VIDIZMO's hosted service, the work runs on NVIDIA GPU instances. And NIM serving carries NVIDIA AI Enterprise into regulated accounts. VIDIZMO connects to what the account already runs: any IP camera or video management system over RTSP and ONVIF, NIM endpoints hosted or on the customer's own GPUs, MCP servers, and REST API and webhooks. For a system that is not listed, VIDIZMO's engineers build the connector against its documented interface, at no development cost to the customer. And it is ready to buy. VIDIZMO is an ISV that builds and supports the software, and the channel sells it, through Carahsoft, TD SYNNEX, CDW-G and SHI, on vehicles such as GSA MAS and NASA SEWP V. Partners who qualify can also install, deliver and support it. So, five things to remember. Watch live cameras with physical AI. Understand video, audio and documents with agents. Release only what is allowed. Deploy wherever the data lives. And every deployment runs on NVIDIA. Bring VIDIZMO into your next GPU conversation. Request a joint demo at vidizmo.ai/partners.