Investor Relations · Raising our first institutional round

A $95B market is recording everything and understanding nothing.

The world has deployed roughly a billion surveillance cameras and watches almost none of the footage. BlinkFree is the vision-language intelligence layer that turns that dead storage into a searchable, real-time security analyst, delivered as local-first, hardware-agnostic, 80%+ gross-margin software.

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MARKET TRAJECTORY · USD Global video surveillance TAM $200B $100B $262B · 2034 2026 2028 2030 2032 2034 THE THESIS AI CAGR ~33% GROSS MARGIN 80%+ INSTALLED CAMS ~1B 13.5% CAGR $95B → $262B Industry estimates · forecast 2026 to 2034

$95B

2026 video surveillance market

~33%

AI video-analytics CAGR

80%+

Target SaaS gross margin

~1B

Installed cameras = our SAM

The Opportunity

The largest untapped data goldmine on earth.

Humanity generates an estimated trillions of hours of surveillance video every year, and the overwhelming majority is never watched by a human. It is the single largest pool of unstructured, unmonetized, machine-readable data in existence, and incumbents have spent a decade selling storage for it instead of intelligence from it.

$95B → $262B

A market growing into a quarter-trillion

Global video surveillance is ~$95B in 2026 and forecast to reach ~$262B by 2034 (13.5% CAGR). We are not betting on the market existing; we are repricing it from hardware to software.

~33%

AI analytics is the fast lane

The AI video-analytics sub-segment alone is projected to triple from ~$28B (2026) to ~$86B (2030) at a ~33% CAGR, the highest-growth slice of the stack, and exactly where BlinkFree lives.

~1B

An installed base we plug into

Roughly a billion IP cameras are already mounted, powered, and pointed at something valuable. Because BlinkFree is hardware-agnostic, every one of them is a zero-capex deployment surface, not a sale we have to manufacture.

The incumbents monetize the camera and the cloud bill. We monetize the understanding: a higher-margin, faster-growing, software-defined layer that sits on top of all of it.

Why We Win

Three structural moats, three flywheels.

Each one of our architectural choices is also a financial advantage. The product decisions are the business model.

Margin Moat

Zero-cloud inference = 80%+ gross margins

Our AI runs on the edge or on the customer's own servers. We do not pay a per-minute AWS/GPU bill to process video, so our COGS is decoupled from usage. While cloud-video competitors watch margins erode as footage scales, ours expand: the classic software profile VCs underwrite at premium multiples.

  • No cloud egress or GPU-rental tax
  • Near-zero marginal cost per camera
  • Margins improve as customers scale
Distribution Moat

Hardware-agnostic = frictionless, viral scale

Verkada and peers require customers to rip out cameras and buy proprietary hardware, a capex sale measured in quarters. BlinkFree installs as software on any existing IP camera, with no NVR. That collapses the sales cycle from months to days and turns the entire installed base into our addressable pipeline.

  • No rip-and-replace, no capex barrier
  • Days-not-quarters time-to-value
  • Land-and-expand across every camera
Technical Moat

PhD-led vision-language = hard to copy

Our core combines state-of-the-art vision and language models into a pipeline that makes video searchable in plain English, a category leap over the motion-sensor and bounding-box analytics that define the incumbents. This is deep-tech IP and talent density, not a feature a fast-follower ships in a sprint.

  • Proprietary VLM search pipeline
  • Founder with a CV PhD & published research
  • Indexed footage = rising switching costs

Feature → Financial Moat

Every feature is a line item on the P&L.

How the product our customers love translates into the scalability metrics investors underwrite.

Product Feature Investor Impact / Scalability Metric
Local / on-prem inference (no cloud) 80%+ gross margins. COGS decoupled from usage, with no AWS or GPU-egress tax that crushes cloud-video competitors' unit economics. Margins expand with scale.
Hardware-agnostic, any IP camera, no NVR Near-zero CAC friction & viral scale. Land into the installed base of ~1B cameras with no capex barrier; sales cycle compresses from quarters to days.
Natural-language video search (VLM) Category creation & pricing power. "Search your world" vs commodity motion alerts; once footage is indexed, switching costs and retention climb.
PhD-led proprietary VLM pipeline Deep-tech defensibility. Talent density and hard-to-replicate IP create a durable lead over fast-follower incumbents and a recruiting magnet.
Real-time alerts (weapons, fire, falls) Mission-critical → low churn, high NRR. ROI is measurable in incidents prevented, justifying enterprise ACVs and multi-year contracts.
Edge deployment & data sovereignty TAM expansion. Unlocks regulated verticals (government, healthcare, finance, critical infrastructure) that cloud-only competitors are structurally locked out of.
Software-only delivery Infinite replicability. Zero marginal cost per camera; gross-margin leverage compounds as deployments scale, with no hardware supply chain to fund.
Cross-camera re-ID & space analytics Multiple expansion vectors. Per-camera + per-seat + analytics tiers create natural upsell surface and rising net revenue retention.

The Landscape

A $5.8B incumbent validated the market. We attack its weak flank.

Verkada hit a $5.8B valuation on $1B+ in annualized bookings, proof the demand is real. But its model is bolted to proprietary hardware and the cloud. That is the exact wedge BlinkFree is built to exploit.

BlinkFree Verkada Spot AI Coram AI
Works on existing cameras ✓ Any IP camera ✗ Proprietary hardware ~ Often paired w/ hardware ~ Camera-dependent
100% on-prem / no-cloud option ✓ Local-first ✗ Cloud-managed ✗ Cloud-centric ✗ Cloud-native
Natural-language video search ✓ Core VLM product ~ Emerging AI add-ons ~ Limited ~ Limited
Gross-margin profile ✓ Software (80%+) ~ Hardware-weighted ~ Cloud compute cost ~ Cloud compute cost
Time-to-deploy ✓ Days ~ Weeks to quarters (install) ~ Days to weeks ~ Days to weeks

Comparison reflects publicly described positioning of each competitor. Verkada ≈ $5.8B valuation / $700M+ raised; Spot AI ≈ $90 to $100M raised; Coram AI ≈ $66M raised. The category is funded and proven, and structurally exposed on hardware lock-in, cloud cost, and search.

The Deck

The thesis in five slides.

A preview of the narrative. The full deck and financial model live in the data room.

01

The Problem

Surveillance is stuck in a hardware-and-storage paradigm. Customers are locked into proprietary cameras, footage piles up as searchable-by-nobody "dead" storage, and cloud-AI vendors charge per-minute compute fees that make true 24/7 analysis economically impossible.

  • Hardware lock-in & rip-and-replace capex
  • Unsearchable, unwatched "dead" footage
  • Punitive cloud-compute & egress fees
02

The Solution

A software AI analyst that connects to any existing camera and runs on the edge or the customer's servers. It understands every frame in real time, lets operators search footage in plain English, and fires instant alerts on weapons, fire, falls, and custom events, with no new hardware and no cloud dependency.

  • Plain-English search across all cameras
  • Real-time threat & safety alerts
  • Runs 100% on-prem or in the cloud
03

Market & Competitor Gaps

A ~$95B (2026) market scaling to ~$262B by 2034, with AI analytics (our slice) compounding at ~33%. Verkada's $5.8B valuation proves enterprise appetite, but it, Spot AI, and Coram AI all carry the same exposure: hardware dependence, cloud cost, and shallow search. We attack all three.

  • TAM $95B → $262B; SAM ~1B cameras
  • Verkada validates the $-per-seat demand
  • Gap: no local-first NL-search player
04

The Tech Stack Moat

A proprietary vision-language pipeline, architected by a founder with a computer-vision PhD and published research, that runs efficiently on local hardware. The result is a product competitors can't easily copy and a cost structure they can't match: defensibility on both the tech and the P&L.

  • Proprietary on-device VLM pipeline
  • 80%+ gross margin, no cloud bill
  • Founder IP & research credibility
05

Traction & The Ask

Live with security-first operators, including XLR Security, whose team found in 8 seconds what used to take 3 hours of manual review, plus an expanding roster of design partners co-building the roadmap. We're raising to convert that pull into a repeatable go-to-market motion.

  • Design partners & paid pilots in motion
  • XLR Security reference deployment
  • Use of funds: GTM + core AI hires

Request the pitch deck & data room.

We share our full deck, financial model, and live-deployment metrics with qualified investors. Tell us a little about your fund and we'll send access within one business day.

  • Full investor deck (PDF)
  • Financial model & unit economics
  • Live customer & pipeline metrics
  • Direct line to the founder

Prefer to talk first?

Or email us directly at enquire@BlinkFree.com