In 2025, the video surveillance analytics world is moving faster than ever. As AI technology grows smarter and more connected, the need for custom video surveillance software development keeps climbing. Companies everywhere are rethinking how they handle security, monitoring, and real-time data analysis, looking for trusted partners to build, refine, or modernize their systems with advanced AI features.

What drives this momentum is the shift from traditional surveillance to intelligent analytics – tools that turn raw footage into useful insights. By combining computer vision, deep learning, and edge computing, these systems can spot anomalies, track behavior, and respond to threats before they escalate. 

This article takes a closer look at where the video surveillance analytics market is headed and which developers are leading the way in 2025.

Market Outlook: How Fast AI Surveillance Is Growing

The AI-powered video surveillance analytics market is expected to reach $28.7 billion by 2030, growing at more than 30% a year. That’s massive, and the reasons are clear: organizations want faster, smarter ways to detect problems before they happen.

Cloud adoption is nearly universal, with over 80% of businesses now using cloud-based surveillance. It’s not just convenient; it’s faster, more reliable, and easier to scale. Many users say AI analytics have boosted their accuracy by 5% and cut response times by up to 40%.

Some of the biggest trends right now include edge computing for on-site processing, hybrid clouds that balance flexibility and control, and deep-learning algorithms that make anomaly detection sharper than ever. The analytics segment alone is growing at 32.5% a year and could hit $241.8 billion by 2033. It’s safe to say: the old model of “record and review later” is fading fast.

The Developers Powering Video Surveillance in 2025

Let’s look at some of the companies setting the bar high in custom video surveillance software development.

🏆Phombus Systems

Rhombus Systems delivers cloud-based analytics that help organizations make sense of what their cameras capture. Their software transforms footage into metrics you can actually use, like how people move through a space or when unusual patterns appear. It’s built for multi-site monitoring, supports real-time alerts, and connects easily with other platforms through APIs. If you want flexible, hardware-independent surveillance without being tied down, Rhombus is a strong choice.

🏆Fora Soft

With over 20 years in video surveillance software, Fora Soft has built systems that thrive under pressure, whether they’re running in the cloud or completely offline. Their solutions bring AI motion detection, object recognition, and anomaly spotting into one smooth experience. They’re perfect for setups that need to handle real-time monitoring at scale: parking enforcement, threat response, or large-site control.

A standout example is VALT – a video surveillance SaaS project generating $9.7 million+ in revenue, serving 650+ organizations and 25,000 daily users. It integrates Amazon Transcribe to search for spoken words in video, saving huge amounts of time for police departments, educators, and child-protection agencies. Features like PTZ control, motion recording, and phone-as-camera streaming keep it versatile and high-performing. It’s also been recognized as one of Wisconsin’s fastest-growing tech firms.

Fora Soft- top AI video surveillance development company
Fora Soft's Video Surveillance case

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🏆Verkada

Verkada stands out for how easily its platform works with existing hardware. Their cloud-based AI tools bring anomaly detection, smart search, and unified event timelines to mixed-device setups. Their open APIs make integration straightforward, letting you build custom analytics and alerts into your existing workflows. It’s ideal for offices, campuses, or enterprise systems that want more power without replacing every camera.

🏆i2V Systems

i2V Systems builds AI analytics designed for real-time object detection and behavior tracking. Their solutions can scale from a single site to an entire city and can be trained on your own data, which reduces false alarms and cuts back on manual monitoring. They’re a great fit for high-traffic environments like warehouses, airports, and public spaces where quick, accurate alerts matter most.

🏆Vegavid

Vegavid brings something special to the table – blockchain-backed AI analytics. Their systems create tamper-proof logs that can’t be altered, making them a perfect fit for financial institutions, compliance projects, and legal monitoring. Vegavid’s team builds custom smart contracts and dApps alongside their AI tools, so every event is recorded securely without slowing real-time processing. If you value transparency and trust, Vegavid’s hybrid of blockchain and AI is hard to beat.

🏆IntelliVision Inc.

IntelliVision Inc. focuses on edge-based analytics for facial recognition and vehicle tracking. Their technology runs directly on smart cameras, minimizing latency and keeping costs low. It’s an efficient option for smart homes, retail security, or any setup where real-time decisions at the edge are key. If you want to boost on-device intelligence without overhauling your network, IntelliVision delivers exactly that.

FAQ

How much does custom video surveillance platform development cost in 2025?

Budgets range from $10,000 to $24,000 for a solid MVP, depending on features. Basic features (live video streaming, recording, IP camera management) are cheaper, while live multi-platform apps climb higher. Hosting costs ~$100 monthly as users grow.

How big is the AI video surveillance market in 2025?

It’s estimated at around $6.5 billion and projected to grow to $28.7 billion by 2030, a CAGR of over 30%.

Why is it expanding so quickly?

The surge comes from better computer vision tech, smarter deep-learning models, smart-city initiatives, and the shift toward cloud and edge computing for faster, more reliable analytics.

Which deployment models are most common now?

Cloud and hybrid setups dominate the market since they make scaling and updates easy, though some industries still rely on on-premises for strict data control.

What types of analytics make the biggest difference?

The strongest impact comes from object detection, anomaly tracking, facial recognition, and behavioral analytics – anything that reduces false alarms and turns video into useful, real-time insight.

How do I pick the right development partner?

Look for a team that understands your use case, supports your current hardware, and builds flexible, scalable AI models. The best partner is one that helps you evolve, not just deploy.

Wrapping Up 

AI video surveillance analytics are reshaping how we think about safety, visibility, and real-time decision-making. The companies above show just how wide the possibilities are.

If your goal is to modernize a surveillance platform, improve SaaS performance, or build something from scratch, now is the time to invest in AI-driven analytics that actually deliver results.

🔎Ready to explore what advanced AI video recognition software can do for you?

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🚀 Reach out or book a quick call today to get a custom development plan and quote, and see how the right partner can take your surveillance system to the next level.

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