Maneva offers two vision agents, Roboflow lets you build your own

Maneva offers wo proprietary vision agents, VITA for quality and downtime and ALIS for safety and productivity, running on NVIDIA edge devices off the cameras a plant already has, plus an Orchestration Platform for dashboards, OEE, and ERP, MES, and SCADA hooks. It is delivered as a service. Maneva's team walks the line, configures the cameras, and tunes the agents, and the company positions the product as removing custom training altogether. That works well if you want a vendor to own the agent.

Teams that want to build their own agents often choose Roboflow. GPT-6 Astra is the first foundation model that sees well enough to label production data, and Roboflow turns those labels into agents you own. Your engineers label their own images (GPT-6 Astra and Gemini do the first pass through Auto Label), train a specialized model (such as RF-DETR or YOLO26), and deploy it to a Jetson, an air-gapped server, or the Roboflow AI1 device with PLC triggers built into Workflows. Vision Events then logs every prediction, image, and operator correction from every camera into one searchable dashboard, so you get defect trends, downtime, and shift-level views without a separate orchestration layer.

Each trained model is exposed over MCP as a vision sub-agent, so you can call it whenever you need to see the line precisely. Manufacturers pick Roboflow because the first agent proves out on their own images in days, on a free plan, and the same platform then produces an agent for every camera in the plant, from defect detection to PPE compliance to pallet counting.

Maneva vs Roboflow: feature by feature

Both run vision agents on the cameras already in your plant, send results to the line, and roll them up into dashboards. The difference is who builds the agent, how many you can have, and whether your frontier models can call them.

The key differences

Maneva is a managed service wrapped around two fixed agents. That is a reasonable choice for a plant with no engineering bandwidth that wants a vendor to own the outcome. Roboflow is the platform your own team uses to build agents, Vision Events supplies the dashboards and the feedback loop, and your frontier models can call both the agents and the event history.

• Agents: Maneva gives you VITA and ALIS. Roboflow gives you the tooling to build a specialized vision agent for every camera and use case in the plant, each trained on your own parts, defects, and lighting.
• Frontier model integration: Roboflow exposes each trained model over MCP, so GPT-6 Astra or Gemini can hand off precise visual tasks to a sub-agent that knows your line, and can query Vision Events for questions like which shift had the most flagged predictions this month. The same frontier models that labeled the data end up calling the agent it produced. Maneva's agents are closed to outside models.
• Dashboards and feedback: Both give you multi-site dashboards. Vision Events also stores every prediction with its image and metadata, lets operators flag mistakes from the HMI, and sends those flagged events into retraining, so the agent gets better on your data instead of waiting for a vendor to tune it.
• Ownership: With Roboflow the dataset, the model weights, the event history, and the deployment are yours to export and move. With Maneva the agents are proprietary and tuned by the vendor.
• Speed to a new agent: Roboflow proves a new station on your own images in days, with a free tier to start today. Maneva's rollout starts with an on-site assessment and a demo request, and time to deploy is not published.
• Line integration: Both write to the line. Roboflow does it through documented OPC UA, Modbus TCP, and EtherNet/IP blocks you configure yourself; Maneva integrates through its team and an API that is not publicly documented.

Maneva fits manufacturers who want a turnkey quality and safety service. Roboflow fits manufacturers who want to build, own, and scale their own vision agents, from the first defect detection station to every camera in the plant, with Vision Events tracking the results and frontier models calling the agents over MCP.