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Product & Technology

Q1. What is IndoAI?

IndoAI is a vision intelligence platform that turns existing CCTV cameras into real-time AI systems. It detects safety, security, and operational events as they happen and sends instant alerts to the right person — with a snapshot, video clip, and event context. You do not need to replace your cameras. IndoAI works with what you already have.

Traditional CCTV records footage. IndoAI acts on it. A traditional system shows you what happened after the fact — you review footage when something goes wrong. IndoAI detects events in real time and alerts the right person while the event is still happening. This shifts your cameras from passive recording devices to active operational tools.

An Edge AI camera processes video intelligence directly on the camera itself — not in a remote server or cloud. This means detection and alerts happen within seconds, the system works even without internet, and your footage never leaves your premises. The ‘edge’ refers to the fact that processing happens at the source — at the camera — rather than being sent elsewhere for analysis.

IndoAI combines computer vision AI models with edge computing hardware. Each AI model is trained to recognize specific events — fire, intrusion, PPE non-compliance, number plates, and so on. These models run directly on IndoAI’s edge cameras or on the IndoAI Edge Box connected to your existing cameras. The system then routes alerts through the IndoAI mobile app and dashboard.

The Edge AI Camera is a new camera with AI built in — you install it as you would any CCTV camera, but it comes with on-device intelligence from day one. The Edge Box is a device you connect to your existing CCTV network — it adds AI capability to cameras you already own, without replacing them. If you have existing cameras, start with the Edge Box. If you are doing a fresh installation, the Edge AI Camera is the recommended choice.

No. IndoAI is designed to work fully offline. All AI processing happens on the device. The camera or Edge Box detects events and sends alerts even without internet. When connectivity is available, data can sync to the cloud dashboard or mobile app. This design is intentional — many Indian industrial and campus environments have unreliable connectivity.

Nothing stops. The AI keeps detecting events on the device. Alerts are stored locally and delivered once connectivity is restored. The system does not depend on the cloud to function. This is one of IndoAI’s core design principles — built for Indian infrastructure conditions.

Appization is IndoAI’s model marketplace — a framework that lets you install, remove, or upgrade AI detection capabilities on your cameras the same way you install apps on a phone. You start with the models you need today and add more later without changing any hardware. For example, a factory might start with PPE detection and add fire detection and intrusion detection the following quarter — all through a software update.

Yes. IndoAI is designed to scale from a small pilot to thousands of cameras. Many clients start with 8 to 16 cameras on one site, evaluate the results, and then expand. There is no minimum camera requirement for a pilot. Contact the team to discuss a starter deployment.

IndoAI’s architecture supports thousands of cameras from a single dashboard. Large enterprise campuses, industrial zones, and multi-site deployments are all supported. The system uses distributed edge processing, so adding more cameras does not degrade performance on existing ones.

Deployment and Integration

Q11. Can IndoAI work with my existing CCTV cameras?

Yes. IndoAI connects to any IP camera or DVR/NVR system that supports RTSP or ONVIF protocols — which covers the vast majority of cameras sold in India including Hikvision, CP Plus, Dahua, Axis, and Sparsh. You do not need to replace your cameras. The IndoAI Edge Box connects to your existing network and adds AI on top.

IndoAI has been tested with Hikvision, CP Plus, Dahua, Axis, Bosch, Sparsh, and most IP cameras that support RTSP and ONVIF standards. If you have cameras not on this list, contact us for a compatibility check — we test on request at no charge.

RTSP (Real-Time Streaming Protocol) and ONVIF are the primary integration protocols. IndoAI also supports H.264 and H.265 video formats and can work with custom SDK integrations for specific camera brands. Most modern IP cameras in India are compatible without any modification.

In most cases, no. IndoAI runs on your existing IP network. If your cameras are already accessible on the network (via NVR or directly), IndoAI can connect to them without infrastructure changes. In some high-density or high-bandwidth deployments, a VLAN configuration may be recommended for security and performance.

A small deployment of 8 to 16 cameras at a single site typically takes one to two days including configuration and testing. A mid-size deployment of 32 to 100 cameras typically takes three to five days. Large enterprise or multi-site deployments are scoped individually. IndoAI’s setup process is designed to be low-disruption to your operations.

Yes. IndoAI supports fully on-premises deployment with no cloud dependency. This is the preferred option for banks, government facilities, defence installations, hospitals, and any environment where footage must not leave the premises. All processing, storage, and alerting happens within your network.

Yes. In addition to on-premises, IndoAI supports cloud-based deployment (where the AI engine runs in the cloud and receives camera streams) and hybrid deployment (edge processing for real-time detection with cloud sync for reporting and dashboards). The right model depends on your connectivity, compliance, and cost preferences.

Yes. IndoAI exposes REST APIs that allow integration with most modern VMS platforms. Events, alerts, and metadata from IndoAI can be pushed into your existing control room software. If you use a VMS that requires a custom integration, speak to the technical team about your specific platform.

Yes. IndoAI Edge AI Cameras are rated IP66 for weatherproofing and are suitable for outdoor installation. The system supports thermal imaging, night vision (IR), and can be configured with solar power and battery backup for locations without direct power access.

Yes. This is one of IndoAI’s design priorities. The system runs fully offline, stores events locally, and syncs when connectivity is available. It has been deployed in environments with 2G connectivity and intermittent power. 4G SIM-based connectivity is supported as a primary or backup network option.

AI Models and Capabilities

Q21. What AI models does IndoAI currently offer?

IndoAI’s model marketplace includes: Face Recognition (for attendance, access control, and visitor management), Fire and Smoke Detection, Vehicle Number Plate Recognition (ANPR), Intrusion Detection, PPE Compliance Detection (helmet, vest, gloves, footwear), Fall Detection, Crowd Density Monitoring, Theft and Gesture Detection, Object Left Behind Detection, and Perimeter Breach Detection. New models are added regularly.

IndoAI models achieve above 95 percent detection accuracy in standard deployment conditions — adequate lighting, appropriate camera placement, and minimum resolution of 2MP. Accuracy varies by use case and environment. The IndoAI team provides a site assessment before deployment to confirm that camera placement and specifications meet the accuracy requirements for your specific models.

Yes. Multiple AI models can run concurrently on a single camera, subject to the compute capacity of the device. For example, a camera at a factory entrance can simultaneously run Face Recognition for attendance and PPE Detection for compliance — from the same video feed.

Yes. IndoAI’s Fire and Smoke Detection model identifies visual signs of fire or smoke in the camera frame within seconds of detection. It is designed for large open spaces such as warehouses, factories, server rooms, and parking basements where conventional smoke detectors have delayed response. The model sends an alert with a snapshot and video clip to the designated contact.

IndoAI’s PPE Detection model scans each person in the camera frame and checks for required safety gear — helmet, safety vest, gloves, and footwear. If a person enters a zone without the required PPE, an alert is triggered immediately. The alert includes a snapshot of the non-compliant individual and the camera location. This is used in factories, construction sites, chemical plants, and warehouses.

Yes. IndoAI’s ANPR (Automatic Number Plate Recognition) model is trained specifically for Indian number plate formats. It recognises plates from moving and stationary vehicles, in daylight and low-light conditions. It is used for automatic gate access, blacklist alerts, parking management, and visitor vehicle logging.

Yes. IndoAI’s Fall Detection model identifies sudden changes in body posture that indicate a fall. It is deployed in hospital wards, elder care facilities, factory floors, and public areas. When a fall is detected, an alert with a video clip is sent to the designated contact — typically a nurse station, security desk, or facility manager.

You define one or more zones in the camera view — for example, a server room entrance, a restricted storage area, or a perimeter fence line. IndoAI’s Intrusion Detection model triggers an alert whenever a person enters or approaches the defined zone outside permitted hours or without authorisation. The alert includes the zone name, timestamp, snapshot, and a short video clip.

Yes. IndoAI’s Crowd Density model estimates the number of people in a defined area. It can trigger alerts when density exceeds a set threshold — useful for managing overcrowding in malls, stations, campuses, religious venues, and event spaces. Historical crowd data is available in the dashboard for planning.

Yes. IndoAI’s team develops custom AI models for use cases not covered by the standard marketplace. Examples include detecting specific machine states in a factory, identifying dress code violations, monitoring specific goods handling procedures, or tracking equipment movement. Custom models are developed on a project basis — contact the team to discuss requirements and timelines.

Standard models are updated via OTA (Over-the-Air) updates pushed to devices automatically. Enterprise clients on private deployments can schedule update windows. IndoAI also retrains models periodically using anonymised real-world data to improve accuracy in Indian conditions.

Privacy, Security and Compliance

Q32. Is IndoAI compliant with India's DPDP Act?

Yes. IndoAI is designed with DPDP (Digital Personal Data Protection Act) compliance as a core requirement. Key compliance features include: on-premise processing so video data does not leave your facility, configurable data retention periods with automatic deletion, role-based access controls, full audit logs of who accessed what data and when, and support for consent mechanisms required for face recognition deployments. Speak to the IndoAI team for a compliance assessment specific to your deployment.

Yes. Under India’s DPDP Act, collecting and processing biometric data — which includes facial recognition — requires clear notice to individuals and, in most cases, their consent. For employee deployments (attendance, access control), employers must post clear notices and maintain records. IndoAI provides documentation templates and deployment guidance to help clients implement DPDP-compliant face recognition systems. The IndoAI team recommends consulting a legal advisor for your specific context.

Only if you choose that option. In the default on-premise deployment, all video processing happens on-device and footage stays within your network. Event snapshots and video clips (triggered by AI detections) can optionally be synced to a secure cloud dashboard for remote access and reporting. You have full control over what is stored and where.

Video footage and event data are stored using AES-256 encryption. Access to the dashboard requires multi-factor authentication. All API communications use TLS 1.3. Role-based access ensures that each team member sees only what they are authorised to see. Audit logs record all access events and configuration changes.

Yes. The IndoAI dashboard allows administrators to set retention periods per device or per event type. Footage can be configured to auto-delete after 7, 15, 30, 60, or 90 days. Event clips and snapshots can be retained separately from raw footage. All deletion events are logged in the audit trail.

Yes. IndoAI’s on-premise deployment is specifically designed for environments where cloud use is restricted — government facilities, banking, defence, healthcare, and regulated industries. The entire stack (AI processing, alerting, storage, and dashboard) runs within your network with zero external data transfer.

Yes. IndoAI has a GDPR-compatible mode that includes data anonymisation, opt-in consent management, data minimisation controls, right-to-erasure workflows, and region-specific data retention policies. This is relevant for multinational companies deploying IndoAI across India and Europe.

Access is entirely controlled by the system administrator. You create user accounts with specific roles — operator, supervisor, manager, or admin — each with defined permissions on which cameras, events, and data they can view or modify. No IndoAI employee can access your footage without explicit permission from your administrator.

Yes. All AI models in IndoAI — including face recognition — are opt-in. They must be explicitly activated by your system administrator. You can enable face recognition on specific cameras only, restrict it to specific hours, or disable it entirely at any time without affecting other models running on the same device.

All your data — including footage, event clips, and configuration — remains your property at all times. On termination of service, IndoAI provides a data export window and then purges all copies of your data from any shared infrastructure within 30 days. For on-premise deployments, the data is on your hardware and you retain it entirely.

Pricing and Licensing

Q42. How is IndoAI priced?

IndoAI pricing is modular and based on the number of camera streams you activate and the AI models you deploy. There is a one-time hardware cost for the Edge AI Camera or Edge Box, and a recurring subscription for the AI software and platform access. Subscription is available monthly or annually, with discounts for annual plans and bulk camera deployments. Contact the team for a custom quote based on your site.

There is no hard minimum for a pilot. IndoAI works with clients starting from as few as 4 cameras. For production deployments, the typical entry point is 8 to 16 cameras. As volume increases, per-camera subscription pricing reduces.

Yes. The base platform subscription gives you access to the dashboard, mobile app, and alerting infrastructure. Each AI model (face recognition, fire detection, PPE, etc.) is activated per camera stream and billed as an add-on. This means you only pay for the models you actually use, on the cameras where you need them.

Yes. IndoAI offers a free live demo (remote or on-site) and a paid pilot program for enterprise clients who want to evaluate the system on their own infrastructure before committing to a full deployment. Pilot terms — including duration, cameras, and models included — are agreed with the team on a case-by-case basis.

Yes. IndoAI supports government tender pricing, GeM portal procurement, and PSU evaluation programs. The team is experienced with government procurement processes including EMD, performance guarantees, and staged payment structures. Contact the team for GEM listing details and tender support.

Both options are available. For enterprise and government clients who prefer a one-time licence structure (common in capital expenditure budgets), IndoAI offers perpetual licence pricing with an annual maintenance and support fee. The subscription model is preferred by clients who want flexibility to scale cameras and models over time.

Primarily per camera stream. If you have 10 cameras on one site and 10 on another, you have 20 active streams. Multi-site clients on a single agreement receive volume pricing that reduces the per-stream cost. The dashboard and user accounts are not charged separately.

The subscription includes: platform access (dashboard and mobile app), AI model runtime for activated models, OTA software updates, alert delivery (mobile app, WhatsApp, email), standard support (email and WhatsApp), and access to new models added to the marketplace. Hardware warranty and on-site support may be included depending on the plan tier.

Yes. You can add cameras to your plan at any time. Removing cameras from an active plan is subject to the minimum commitment terms in your agreement. Annual plans typically require a minimum of 12 months on the subscribed camera count before reduction.

Standard deployments using IndoAI’s Edge AI Camera or Edge Box on RTSP/ONVIF cameras do not carry an integration fee. Custom integrations — connecting IndoAI to third-party VMS platforms, ERP systems, or bespoke alerting workflows — are scoped and priced separately on a project basis.

Industries and Use Cases

Q52. How is IndoAI used in manufacturing and factories?

In factories, IndoAI is primarily used for PPE compliance monitoring (helmet, vest, gloves), intrusion detection in restricted production zones, fire and smoke detection, and forklift and vehicle safety monitoring. It reduces safety incidents, supports DGFASLI and factory act compliance, and reduces the cost of manual safety supervision.

Warehouses use IndoAI for after-hours intrusion detection, perimeter monitoring, vehicle and truck tracking via ANPR, theft detection, and fire safety. A common deployment is 4 to 8 cameras covering loading docks, perimeter gates, and storage areas with intrusion and fire models active after operational hours.

Retail deployments use IndoAI for theft and shoplifting detection, customer flow analysis, restricted area access monitoring, and after-hours intrusion alerts. The system is particularly useful for multi-store retail chains where a central security team monitors all locations from a single dashboard.

Hospitals use IndoAI for fall detection in patient wards, PPE compliance monitoring in ICUs and OTs, unauthorised access detection in restricted areas, visitor management using face recognition, and fire detection. It reduces liability from patient falls, supports infection control compliance, and reduces the manpower cost of manual security rounds.

Educational institutions use IndoAI for attendance automation using face recognition, restricted zone monitoring (server rooms, hostels, labs), vehicle entry management using ANPR, and fire detection. It reduces administrative time spent on manual attendance and improves campus security without increasing security staff.

Housing societies use IndoAI for gate automation (face recognition for residents, ANPR for known vehicles), visitor management, after-hours intrusion detection in common areas, parking management, and fire detection in basements and common areas. The system integrates with existing intercom and barrier gate systems in most societies.

Yes. IndoAI has been deployed in smart city infrastructure projects covering traffic monitoring, public space surveillance, crowd management, and perimeter security for government facilities. IndoAI’s on-premise deployment model meets the data sovereignty requirements of government projects. The platform supports role-based access for multi-department command centres.

Corporate campuses use IndoAI for access control using face recognition, visitor management, vehicle tracking, compliance monitoring for safety drills, and after-hours security. It reduces the cost of security manpower, automates attendance, and provides centralised control across multiple buildings or floors from one dashboard.

Yes. IndoAI’s crowd density model is specifically designed for events. It monitors crowd build-up in entry points, corridors, and open areas, and triggers alerts when density exceeds safe levels. This is relevant for religious events, concerts, stadiums, and political gatherings where crowd crush risk is a concern.

IndoAI has been deployed for perimeter security at large farms, water infrastructure facilities, and mining sites. Outdoor use cases include perimeter intrusion detection, vehicle tracking, and fire detection in open areas. Solar-powered configurations are available for remote agricultural and infrastructure sites.

Hardware — Edge AI Camera and Edge Box

Q62. What is the IndoAI Edge AI Camera?

The IndoAI Edge AI Camera is a purpose-built surveillance camera with AI processing built directly into the device. It does not need a separate processing unit — detection, alerting, and event storage all happen on the camera itself. It ships with four pre-installed AI models and supports the full Appization marketplace for additional models.

The Edge Box is a compact AI processing device that connects to your existing CCTV cameras via your local network. It receives video streams from your cameras, runs AI detection on them, and generates alerts — without requiring you to replace any camera hardware. One Edge Box can process multiple camera streams simultaneously.

One Edge Box can handle between 8 and 16 camera streams simultaneously depending on the AI models activated and the resolution of each stream. For larger deployments, multiple Edge Boxes are deployed and managed from the same dashboard.

Minimum recommended resolution is 2MP (1080p). For face recognition and ANPR, 4MP or higher is recommended with appropriate lens selection and camera placement. IndoAI’s team provides a pixel density guide to help you select the right camera specifications for each use case.

The Edge Box supports wired Ethernet (recommended for stability), Wi-Fi, and 4G SIM connectivity as a primary or backup connection. For on-premise deployments, Ethernet is strongly preferred. 4G connectivity is used for remote sites where wired infrastructure is not available.

Yes. Edge AI Cameras can be configured with solar panel and battery backup systems for deployment in locations without grid power — remote farms, highways, mining sites, and outdoor perimeters. The solar configuration is specified at the time of order and includes charge management hardware.

IndoAI hardware carries a standard 12-month warranty from the date of deployment. Extended warranty and AMC (Annual Maintenance Contract) plans are available for enterprise deployments. The AMC includes hardware replacement, on-site servicing, and software updates.

 IndoAI Edge AI Cameras use standard mounting dimensions compatible with most CCTV pole and wall brackets. If you are replacing cameras at an existing installation, the existing mounts can typically be reused. The IndoAI team confirms mount compatibility during the site assessment.

Alerts, Dashboard and Mobile App
Q70. How does IndoAI deliver alerts?

IndoAI alerts are delivered via the IndoAI mobile app (iOS and Android), WhatsApp messages, email, and SMS. Each alert includes the event type, camera name, timestamp, a snapshot of the event, and a short video clip. The alert is sent to the designated person or group for that camera and event type, as configured by the administrator.

Alert delivery typically happens within 5 to 15 seconds of event detection for on-premise deployments with good network conditions. Detection itself happens in real time on the device. The small delay between detection and alert delivery is due to clip generation (1 to 3 seconds of video is captured before and after the event) and network transmission time.

Yes. The dashboard allows you to define alert routing per camera, per event type, and per time of day. For example, intrusion alerts from a warehouse camera can go to the security head during business hours and to the site manager after hours. Multiple people can receive the same alert simultaneously.

The IndoAI mobile app lets you view live camera feeds, receive and review alerts, mark incidents as resolved, add notes, and access event history — all from your phone. It is available for iOS and Android and supports biometric login. Team members can be given different levels of access depending on their role.

Yes. The web dashboard and mobile app both support live view of all cameras on your deployment. You can view a single camera full-screen or a grid of multiple cameras simultaneously. Live view supports standard and high-definition playback depending on your network bandwidth.

Yes. IndoAI supports event-based search — you can filter incidents by camera, event type, date, and time. For deployments with the Vision LLM module, you can also search using natural language — for example, ‘show me all intrusion events at the north entrance this week.’

Yes. Each alert in the mobile app and dashboard can be reviewed, annotated, assigned to a team member, and marked as resolved. The resolution history is stored in the event log for audit purposes. This workflow supports incident management and compliance reporting.

Yes. IndoAI supports WhatsApp alerts to individual numbers and WhatsApp groups. This is particularly useful for security teams and facility managers in India who coordinate on WhatsApp. The alert message includes the event summary and a link to view the full clip on the dashboard.

Yes. The web dashboard is cloud-accessible (for hybrid and cloud deployments) and can be accessed from any browser. For fully on-premise deployments, the dashboard is accessible within your internal network. VPN access from remote locations can be configured by your IT team.

Yes. The dashboard generates daily, weekly, and monthly reports by camera, event type, site, and time period. Reports can be exported as PDF or CSV. Typical use cases include weekly safety compliance reports for factory management, monthly incident summaries for HR, and daily access logs for security.

Installation, Maintenance and Support
Q80. Who installs IndoAI at my site?

IndoAI is installed by IndoAI’s certified deployment team or by authorised CCTV integration partners. For clients who have an existing CCTV integrator, IndoAI provides technical training and support to enable the integrator to deploy the system. The IndoAI team conducts a site assessment before deployment to confirm camera placement, network readiness, and hardware requirements.

The process follows four steps: site assessment (reviewing existing cameras, network, and use case requirements), hardware provisioning (Edge Boxes or Edge AI Cameras), on-site installation and configuration (connecting cameras, configuring AI models, setting up alert routing), and handover and training (showing the client team how to use the dashboard and app). Most small to mid-size deployments are completed in one to three days.

IndoAI provides email and WhatsApp support for all clients. Enterprise and AMC clients additionally receive: 24/7 phone support, SLA-based response times, regular model performance reviews, on-site visits for troubleshooting, and a dedicated account manager. Standard support response time is within 4 business hours.

Yes. The dashboard and mobile app are designed to be self-service. Adding cameras, adjusting alert settings, adding or removing users, activating or deactivating AI models, and reviewing event history can all be done without contacting support. For complex configuration changes (new AI models, network changes, multi-site setup), the support team is available to assist.

Yes. IndoAI provides standard training for administrators (dashboard configuration and user management), security operators (alert handling and incident management), and site supervisors (reviewing reports and escalations). Training is available online and in person. Multilingual training materials are available in Hindi and English.

IndoAI’s dashboard has built-in device health monitoring that alerts the administrator if a camera goes offline or an Edge Box stops communicating. Under the warranty and AMC terms, defective hardware is replaced within the agreed SLA period. Critical deployments can request spare units to be kept on-site for immediate replacement. 

Yes. All software updates, AI model updates, and configuration changes are pushed remotely via the OTA (Over-the-Air) update mechanism. You do not need to visit the site or touch the hardware to update the system. Updates are scheduled to minimise disruption and can be rolled back if needed.

Appization and Developer Platform
Q88. What is the IndoAI developer platform?

IndoAI’s developer platform allows third-party AI developers and system integrators to build, test, and publish computer vision models to the IndoAI marketplace. Published models can be deployed on IndoAI cameras by any customer — enabling a growing ecosystem of industry-specific AI models beyond what IndoAI builds internally.

The IndoAI SDK supports Python, TensorFlow, ONNX, and PyTorch. Models are packaged in a containerised format (compatible with Docker) and deployed through IndoAI’s runtime environment. Detailed developer documentation and sample models are available in the developer portal.

Submitted models go through IndoAI’s review process which checks for accuracy performance, compute efficiency, security compliance, and absence of harmful bias. Approved models are published to the marketplace and made available to customers. The review process typically takes 10 to 15 business days for standard models.

Yes. IndoAI operates a revenue-sharing programme for marketplace developers. Models can be listed on a per-stream subscription basis or as a one-time deployment fee. Revenue share terms are disclosed in the developer agreement. IndoAI handles billing and distributes developer revenue monthly.

Yes. Organisations can develop AI models using the IndoAI SDK and deploy them privately — only to their own cameras — without publishing to the marketplace. This is used by clients who need proprietary detection models for specific manufacturing processes, compliance requirements, or security protocols.

Yes. IndoAI provides a web-based test bench with preloaded video datasets and simulated camera streams. Developers can test model accuracy, latency, and resource consumption before submitting for review. Performance profiling and event log tools are included in the SDK.

Visit indo.ai/developer or contact the partnerships team. Developer onboarding includes SDK access, documentation, sandbox credentials, and a technical walkthrough call with the IndoAI engineering team. Partner integrators receive additional support including co-selling opportunities and joint deployment support.

Competitive Comparison
Q95. How does IndoAI compare to Hikvision?

Hikvision is primarily a camera hardware manufacturer. Their AI capabilities are limited to features built into specific camera models and are not easily expandable. IndoAI adds flexible, model-based AI on top of any camera — including Hikvision cameras. IndoAI also processes data on-premise in India, whereas Hikvision’s cloud services route data through servers outside India, which raises DPDP and data sovereignty concerns for enterprise and government buyers.

CP Plus is India’s largest CCTV brand by volume, focused on hardware distribution. Their AI features are pre-embedded in specific models with limited customisation. IndoAI is a software-first platform that works on CP Plus hardware, adds expandable AI models, and provides enterprise-grade alerting and reporting that CP Plus systems do not offer natively.

Cloud-based platforms require continuous video upload to remote servers — which creates privacy risks, adds bandwidth costs, and creates single points of failure. IndoAI processes video at the edge (on the device) and only sends event metadata and short clips when triggered. This is faster, cheaper, and more compliant with Indian data protection requirements.

Axis is a premium camera hardware brand with strong imaging quality. Their on-camera AI (ACAP applications) is limited and requires Axis hardware. IndoAI is hardware-agnostic, supports any brand’s cameras, and offers a broader, more flexible model marketplace with India-specific support. For enterprises already invested in Axis cameras, IndoAI’s Edge Box adds AI without replacing the hardware.

Yes. This is one of IndoAI’s most common deployment scenarios. Clients with existing Hikvision, CP Plus, Dahua, or any other RTSP/ONVIF-compatible cameras add IndoAI’s Edge Box to their network and activate the AI models they need — without replacing a single camera.

Open-source video analytics tools require significant technical expertise to set up, maintain, and scale. They do not provide the alerting infrastructure, mobile app, dashboard, OTA updates, support, or compliance documentation that enterprise buyers need. IndoAI delivers a production-ready, supported platform designed specifically for Indian enterprise deployment conditions.

Getting Started
Q101. How do I get started with IndoAI?

The best starting point is a free 30-minute live demo. You will see the system working on a real deployment — alerts being triggered, the mobile app in action, and the dashboard. After the demo, if you want to evaluate on your own site, the team will conduct a free site assessment and propose a pilot configuration. Book at indo.ai/book-a-demo or send a WhatsApp message to +91 82084 36017.

It helps to know approximately: how many cameras you have or plan to install, the industry and site type (factory, office, warehouse, etc.), the primary use cases you want to address (safety, security, access control, compliance), and whether you prefer cloud, on-premise, or hybrid deployment. This lets the IndoAI team tailor the demo to your actual context.

A pilot typically covers one site with 8 to 16 cameras, two or three AI models, and runs for 30 to 60 days. The IndoAI team handles installation, configuration, and training. You use the system normally and evaluate alert quality, response times, and operational value. At the end of the pilot, you decide whether to expand.

Yes. IndoAI can facilitate reference calls or site visits with existing clients (subject to their consent) for enterprise buyers who want to evaluate the system based on real-world deployment experience. Ask the sales team to arrange a reference conversation.

Yes. IndoAI works with CCTV integrators, AMC companies, and security system installers across India as authorised partners. Partners receive product training, demo units, joint deployment support, and a revenue share on installations. Contact the partnerships team at [email protected] or visit indo.ai to enquire about the partner program.

WhatsApp is the fastest channel — send a message to +91 82084 36017. For technical questions or partnership enquiries, email [email protected]. The team aims to respond within 2 hours on business days.

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