Nurby reads your camera feeds with local vision models, writes plain-language rules, and tells you only what matters. No cloud uploads. No API keys required. Your footage stays on your network.
Watch over babies, pets, and elders without streaming their lives to a stranger's cloud. Nurby whispers when something matters and stays quiet the rest of the time.
Nurby secures a home or a business out of the box. Guardian adds a privacy-first view for places that watch over people.
Families follow one person in a facility, and nobody else. Safe arrival, verified pickup, everyone else blurred.
Each parent sees their own child. A push on arrival, pickup checked against an approved list.
A calm status that answers the daily call, without watching the cameras all day.
Nurby watches for gentle chest movement and writes a soft note when it sees it. No alarms unless something is actually wrong.
Face recognition identifies trusted visitors and logs their arrival. You stop wondering. You just check.
Draw a loiter zone on the feed. Nurby timestamps anyone standing inside it longer than you want.
YOLO detection finds parcels the moment they land. Nurby files a clip with label, confidence, and timestamp.
Unknown faces outside your allow list fire rules. Clips get tagged, emails get sent, clusters group repeat visitors.
If a camera can see it, Nurby can react to it. Compose anything from a siren when a bear shows up to a silent webhook that logs sheep counts to your farm dashboard. No cap on how many.
When a bear is detected in the backyard, sound the yard siren for 20 seconds.
Pick a trigger. Toggle conditions. Chain actions. Nurby writes the rule back to you as a sentence so there is no guessing.
When a person is detected on Front Door after 10 pm, send an email and record a 30 second clip.
17 models from yolov8n through yolo-world and the 600-class OIV7 family. Labels are sourced directly from the active weights.
Swap providers per camera or per rule. Stay local with Ollama if you have a capable GPU, or route to a cloud provider when you need accuracy without the hardware.
Nurby's API Call action speaks plain authenticated HTTP with templated URLs, headers, and bodies, so a rule can write into whatever your site actually runs. No certified-partner list to wait for, and no vendor lock-in on our side.
Keyless entry, door controllers, and credential readers. Nurby posts the body count that the badge event alone cannot give you.
Every site is odd in its own way. The lighting, the angle, the one forklift that always parks in shot. A camera product that cannot absorb your corrections makes you tune it forever. Here is where Nurby is on closing that loop, honestly labelled.
A rule can run a vision model as a second opinion before it fires, so the borderline calls get looked at twice instead of paging the shift lead.
Every fired event carries a right/wrong control. Correcting one is the whole interaction. No labelling tool, no dataset, no ML team.
Nurby reads back your corrections and proposes the change: raise this rule's confidence to 0.86 and 28 of the 31 you dismissed would have stayed quiet. You approve it, it does not apply itself.
Your corrections become examples attached to that rule's prompt, so the model learns what a mis-slotted pallet looks like in your aisle, not in a benchmark.
Type what you remember. Nurby finds the clip. No more scrubbing through 23 hours of footage across five cameras to spot the package, the visitor, or the dog in the kitchen. Daily digest hands you the morning's highlights in one glance.
The dog was in the kitchen three times last night. Longest visit was 22 seconds at 11:42 pm near the fridge.
Ollama plus YOLO runs on your hardware. Nothing leaves unless you wire it to.
Toggle blur on specific family members in shared timelines. Keep kids private in exports.
NudeNet blurs sensitive frames. Audio triggers fire only on the sounds you pick.
Every rule, event, and action is addressable. Query your cameras from Claude Desktop via MCP, fire webhooks when rules trigger, or wire Nurby into your home stack with structured JSON.
{
"mcpServers": {
"nurby": {
"command": "python",
"args": ["-m", "services.mcp.server"],
"env": {
"NURBY_MCP_TOKEN": "<your-jwt>",
"DATABASE_URL": "postgresql+asyncpg://..."
}
}
}
}
// "who was at the door today?"
// → answered from your own cameras{
"name": "Late-night front door",
"trigger_pattern": {
"type": "object_detected",
"label": "person"
},
"conditions": {
"camera_id": "front_door",
"time_after": "22:00",
"min_confidence": 0.7
},
"actions": [
{"type": "verify"},
{"type": "telegram"},
{"type": "email", "to": "[email protected]"}
],
"cooldown_seconds": 300
}{
"type": "api_call",
"url": "https://ha.local/api/services/light/turn_on",
"method": "POST",
"headers": {
"Authorization": "Bearer {{ha_token}}"
},
"payload_template": {
"entity_id": "light.porch",
"brightness": 255
},
"secret": "hmac-key-for-signature"
}
// triggers fire → porch light turns onRun Nurby on your own hardware with a single compose file. The full backend is open source on GitHub.
Apache-2.0, self-host, no credit card