The only conversational AI copilot that runs your entire video management system — and never touches the cloud. Ask, search, investigate, automate, and administer through natural conversation.
Radha is not a chatbot bolted onto a dashboard. She commands 75+ operational tools covering every Visylix feature, answers questions from all 22 AI models, finds footage from a visual description, runs multi-step investigations with evidence timelines, sees through an on-premise vision model, listens through local speech-to-text, and learns your site's vocabulary the more you use her. Every conversation stays inside your infrastructure.
75+
Operational Tools
22
AI Models Queryable
55+
Languages Supported
0
Cloud Dependencies
Most AI assistants answer questions. Radha executes operations, investigates incidents, writes reports, and learns your site. Every Visylix feature is controllable through conversation.
Talk to your VMS like you talk to a colleague. Radha understands requests like "show me all face detections from the parking lot cameras between 2pm and 4pm yesterday" and executes them instantly — in 55+ languages, replying in yours.
Radha runs a purpose-built 8 billion parameter language model locally on your GPU, with optional on-premise vision and speech models beside it. Every conversation, image, and voice clip stays inside your infrastructure with zero cloud dependency — built for government, defense, banking, and any organization that requires complete data sovereignty.
Radha learns your site's vocabulary. Tell her once to "call this camera the gate cam" and every future conversation understands it. She remembers per-user preferences, learns from thumbs-up/down feedback and corrections, and gets measurably better the longer your team uses her — all learning stays on your hardware.
For open-ended questions Radha becomes an investigator: she plans, chains searches across sightings, detections, events and alerts, and returns findings with an evidence timeline you can replay moment by moment. The kind of capability others run in the cloud — Radha does it air-gapped.
Every important alert gets a plain-language explanation of what happened and why it fired, written by the local model seconds after the alert lands — so operators triage the alert rail without decoding raw detection data.
Destructive actions never execute from model output alone. Radha proposes, names exactly what will be affected, and waits for your explicit click — the confirmation is enforced server-side with single-use tokens, so the AI cannot approve itself.
From a person's movements to a full incident investigation — here is how operators use Radha every day.
When was James recognised today?
James was recognised 4 times today: first at 08:52 at the Main Entrance, then at 09:14 in the Lobby, 13:03 at the Cafeteria camera, and last seen at 17:41 leaving through the Employee Gate. Want me to play the recording of any of these moments?
Find a person in a red jacket near the entrance this morning
I found 3 matches this morning: 08:12 at Main Entrance (strong match), 08:47 at Side Entrance A, and 11:20 at Parking Entry. The 08:12 sighting is the closest match — shall I open that recording at the exact moment?
What happened at the loading dock this afternoon? Anything unusual?
I investigated the loading dock between 12:00 and 18:00: 14 person detections (normal for a weekday), one tripwire crossing at 14:22 during a scheduled delivery, and a 6-minute loitering event at 16:48 that did not match any delivery window. I have built a timeline — the 16:48 event is worth reviewing. Play it?
Summarise my shift and email me the report
Your shift summary: 24/24 cameras online, 7 AI alerts (2 unacknowledged — both low severity), zero PPE violations, storage at 61% with 34 days of runway. Nothing needs escalation. I have generated the printable report and it is on its way to your email.
Radha does not simulate actions — she executes them against your live system, within your permissions, with confirmation gates on anything destructive.
List and play cameras, start or stop streams and recordings, capture snapshots, control playback (pause, seek, speed, fullscreen), and nudge PTZ cameras — all by asking.
"Show me the gate camera live"
"Pan camera 4 left and zoom in"
Ask about results from every AI model: face recognition, ANPR, fire and smoke, weapons, intrusion, PPE, crowd, audio events and more — with dates, cameras, and confidence.
"When was James recognised today?"
"Any fire detected overnight?"
Describe what something looks like and Radha finds it across your footage: clothing, vehicles, carried objects. No tags, no manual review — just language.
"Find a man in a red jacket near the entrance"
"Was there a white van this morning?"
Ask an open question and Radha runs a real multi-step investigation — chaining sightings, detections, events, and alerts into findings plus a time-sorted evidence timeline.
"What happened at the dock this afternoon?"
"Trace what James did today"
Radha can look at a live camera or snapshot and describe the scene with an on-premise vision model, and take spoken questions through fully local speech-to-text. Nothing leaves your network.
"What do you see on the office camera right now?"
Push-to-talk in every chat surface
Arm live watches and author real automation rules from a sentence. Rules are created as safe drafts with a dry-run preview, and enabling them always requires your explicit confirmation.
"Watch for plate MH12* tonight"
"Alert me when someone loiters near the vault"
A narrated morning briefing of cameras, alerts, PPE and storage — on demand or scheduled to your channels. One-sentence incident reports become structured, printable evidence documents.
"Summarise my shift"
"Make a report of that fire alert"
Jump to the exact moment on any camera, bookmark recordings, and place tamper-evident legal holds with SHA-256 hashes — every destructive step confirmation-gated.
"Show me camera 2 at 14:32 yesterday"
"Lock recording 42 as evidence"
Add or remove cameras, scan the network for ONVIF devices, create users, restrict camera access, enroll faces and plates, create zones and tripwires, test integrations, activate licences, restart services.
"Enroll James from snapshot 12"
"Let Priya see only the lobby cameras"
Health, storage runway, audit trails, alert statistics with noisiest-source analysis, rule health, occupancy, events, licence state — every dashboard answer, conversationally.
"Who deleted recordings last week?"
"Which alerts are noisiest?"
Radha was built for organizations where data privacy is not optional — and where an AI with real power needs real guardrails.
Language, vision, and speech models all run on your hardware. No API calls to external services, no telemetry, no data leaving your network — Radha works in completely air-gapped environments, from government facilities to classified networks.
Deleting a camera, arming a rule, restarting services — Radha proposes the action, names the exact target, and waits for your explicit click. The gate is enforced server-side with single-use tokens; the model cannot confirm its own actions.
Radha enforces your role-based permissions, per-camera access restrictions, and licence entitlements on every single tool call — and writes every AI action to the audit trail. Operators can never do through Radha what they could not do in the UI.
Person searches based on race, ethnicity, or religion are refused before the model ever runs. Prompt-injection attempts are blocked and audited. Radha answers only about your VMS — never the internet, never off-topic, never your system internals.
No other video management system ships a conversational AI copilot that runs entirely on-premise. Cloud vendors keep their AI in their cloud; on-premise vendors ship search boxes. Radha is a full copilot — chat, search, investigation, vision, voice, and administration — with zero cloud dependency.
Every tool executes real system commands within your permissions. When you ask Radha to enroll a person, restrict a user to specific cameras, or lock a recording as evidence, she calls the Visylix platform and confirms the result. This is not a simulation.
Radha investigates. Ask "what happened at the dock this afternoon?" and she autonomously chains searches across sightings, detections, events, and alerts into findings with a replayable evidence timeline.
Radha learns your site. Camera nicknames, user preferences, and corrections accumulate in on-box memory — the longer your team uses her, the better she understands your deployment. All learning stays on your hardware.
Radha is governed. Confirmation gates on destructive actions, refusal of discriminatory person searches, prompt-injection blocking, licence and permission enforcement on every call, and a complete audit trail of every AI action.
Schedule a live demo and experience what it feels like to run your entire video infrastructure through conversation.