| Vision agents | Build your own, one specialized agent per camera or use case, as many as you need | Two, VITA (quality and downtime) and ALIS (safety and productivity), configured by Maneva |
| Use cases covered | Defect detection, assembly verification, counting, OCR, PPE and safety compliance, logistics, and any custom vision task | Defect detection, label and seal verification, counting, product tracking, OEE and downtime analysis (VITA); PPE, hand hygiene, danger zones, slip and fall (ALIS) |
| Who builds the agent | You do, on your own images, with AI-assisted labeling | Maneva does; proprietary agents tuned by Maneva staff after an on-site assessment |
| Label your own data | Yes, Auto Label from a text prompt plus Smart Polygon powered by Segment Anything | Not documented; no customer-facing labeling tool |
| Train your own model | Yes, RF-DETR, YOLO (v8 / v11 / v26), Detectron2, and more; retrain as parts and lighting change | Not documented; positioned as removing custom training |
| Export and own model weights | Yes | No, proprietary patent-pending agents |
| Sub-agents for frontier models (MCP) | Yes, every trained model is exposed over MCP so frontier models can call it as a specialized vision tool, and agents can query Vision Events history over MCP | No; agents are closed and are not exposed to outside models |
| Model architectures | Open, user-selectable registry | Proprietary; no architecture or foundation model publicly named |
| Camera support | Any RTSP, USB, GigE, or industrial camera, plus the Roboflow AI1 device with integrated camera and lighting | Hardware-agnostic; existing industrial or security cameras, RGB, depth, SWIR, X-ray, thermal |
| Edge deployment | Yes, NVIDIA Jetson, x86 servers, Roboflow AI1, fully offline | Yes, NVIDIA edge devices; cloud data layer on AWS by default |
| PLC and line integration | Yes, PLC Reader, PLC Writer, and OPC UA blocks in Workflows (OPC UA, Modbus TCP, EtherNet/IP) | Yes, accept/reject/reroute up to 30 decisions per second; ERP, MES, and SCADA via API; protocols not documented |
| No-code application logic | Yes, visual Workflows chain detection, OCR, counting, and PLC output without code, with a line-side HMI | Configured by Maneva; customers use the Orchestration Platform for dashboards, alerts, and agent tuning |
| Dashboards and analytics | Yes, Vision Events aggregates predictions, images, and metadata from every camera and site into one dashboard, filterable by shift, line, lot, or serial range, with saved filters | Yes, Orchestration Platform with multi-site, facility, and agent dashboards, OEE, root-cause analysis |
| Operator feedback loop | Yes, operators flag wrong predictions from the line-side HMI; flagged events are stored with the image and go straight into the next training set | Not documented; agent tuning is done by Maneva staff |
| Self-serve sign-up and free tier | Yes | No; demo request only |
| Time to first agent | Days, on your own images, starting the same day | Not disclosed; deployment begins with an on-site assessment by Maneva staff |
| API and SDK | Yes, Python SDK, REST API, MCP server, public docs | Integration API mentioned; no public API reference, SDK, or docs |
| Open source | Yes, supervision and inference libraries | No |
| Compliance | SOC 2 Type II, HIPAA with BAAs, PCI DSS | States SOC 2 and ISO 27001 certified; type and scope not published |
| Air-gapped deployment | Yes, Docker-based offline install | Edge inference runs locally; fully air-gapped offering not documented, data stored on AWS by default |
| Pricing | Published plans; free tier; usage you can see before you sign | Not published; quote-based, expanding one agent and one line at a time |