# Alarum Technologies Ltd.

> Clarifo company profile — qualitative business description generated from
> the company's filings. Financial statements, charts and ratios are
> available on Clarifo (https://www.clarifo.com/en/companies/Alarum Technologies Ltd.).

## Overview

Alarum Technologies Ltd. develops web data collection and AI data infrastructure solutions through its NetNut subsidiary. Its platform combines proxy-network infrastructure, website unblocking, search-engine result collection, data collection tools, and AI-ready datasets for customers that need structured public web data at scale.

## Products & services

• Website Unblocker for accessing restricted web content
• SERP data collection solutions
• Proxy-network infrastructure and exit points
• Data Collector and web scraping tools
• AI-ready datasets for model training and fine-tuning

- **Proxy and network infrastructure** (35%) — Residential and server-based IP infrastructure used to route and manage web traffic.
- **Web data collection tools** (30%) — Tools that help customers access, extract, and analyze public online data.
- **Website Unblocker and anti-bot access** (15%) — Software and services that bypass blocking, rate limits, and anti-bot defenses.
- **SERP and search data solutions** (10%) — Search-engine result collection and related structured data feeds.
- **AI data sets and training data** (10%) — Prepared datasets sold for LLM training, tuning, and downstream AI use cases.

- Website Unblocker for accessing restricted web content
- SERP data collection solutions
- Proxy-network infrastructure and exit points
- Data Collector and web scraping tools
- AI-ready datasets for model training and fine-tuning

## Customers

Customers include foundation model labs, hyperscalers, enterprises, and other organizations that need large-scale public web data. The offering is used when internal scraping is blocked, too costly to operate, or needs to scale across many sites and geographies.

- **Foundation model labs** (primary) — Buy datasets and collection infrastructure to support LLM training and fine-tuning.
- **Hyperscalers** (primary) — Use web data infrastructure for AI pipelines, search, and structured data acquisition.
- **Enterprises** (primary) — Buy web collection tools and datasets for pricing, research, and competitive intelligence.
- **Innovators and developers** (secondary) — Use proxy and collection tools to build automated data workflows and applications.

- Foundation model labs needing training and fine-tuning data
- Hyperscalers building internal AI and search workflows
- Enterprises extracting market, pricing, and product data
- Innovators and software teams automating web intelligence
- Customers needing access to blocked or dynamic websites

## Geography

Alarum is a global business with infrastructure and ISP-partner servers distributed around the world. Its solutions are delivered online, so geography matters mainly through IP coverage, latency, and the ability to reach websites across multiple jurisdictions.

- Global proxy and server network supports worldwide data collection
- ISP-partner infrastructure broadens IP diversity and reach
- Tel Aviv is the principal executive office location
- Nasdaq and TASE listings broaden investor access
- Cross-border web access creates exposure to local regulations

## Strategy

Alarum is building a broader AI data infrastructure platform beyond its original proxy-network roots. The strategy is to combine access infrastructure, data collection software, and packaged datasets so customers can source structured web data more reliably at scale.

- **Broaden the product platform** (short-term) — A wider stack increases wallet share and makes the company harder to replace.
- **Serve AI infrastructure demand** (medium-term) — Model builders need scalable public-web data for training and fine-tuning.
- **Scale global network coverage** (medium-term) — Broader IP and server coverage improves access rates and data collection reliability.

- Expand from proxy access into a full AI data infrastructure stack
- Increase product breadth with datasets and collection tools
- Serve AI model builders that need large-scale training data
- Use proprietary reflection technology and ISP partners to improve reach
- Diversify customers to reduce reliance on any single use case

## Risks

The business depends on access to public websites and on maintaining network infrastructure that can bypass anti-bot and blocking systems. It also faces legal, compliance, and operational risk because proxy and residential-network services can attract law-enforcement scrutiny and customer concentration can swing demand.

- **Network disruption from law-enforcement or domain actions** [high] — The company disclosed recent action affecting domains associated with NetNut's residential proxy network.
- **Anti-bot and website blocking escalation** [high] — Customer value depends on collecting data from sites that actively block automated access.
- **Regulatory and legal scrutiny of proxy services** [high] — Residential proxy networks can face compliance, privacy, and enforcement risk across jurisdictions.
- **Customer concentration and demand variability** [medium] — AI and enterprise workloads can be lumpy and concentrated among a few large buyers.

- Anti-bot changes can reduce collection success and raise operating complexity
- Law-enforcement or domain actions can disrupt network services
- Customer concentration can create volatility in demand and renewals
- Regulatory scrutiny of proxy networks can affect product availability
- Global IP supply and ISP partner dependence can constrain scale

## Accounting

Revenue recognition depends on how recurring access, usage-based collection, and dataset delivery are contracted and fulfilled. Investors should also watch capitalization and amortization of technology assets, as well as impairment risk if platform components or customer relationships do not deliver expected cash flows.

- **Revenue recognition** — Affects reported growth and quarterly comparability
- **Intangible asset amortization** — Affects operating profit and asset carrying values
- **Impairment testing** — Could trigger non-cash charges
- **Share-based compensation** — Affects operating margin and non-GAAP adjustments

- Revenue timing may vary by subscription, usage, or dataset delivery terms
- Quarterly results may fluctuate with customer onboarding and project timing
- Capitalized software and technology assets affect amortization expense
- Impairment risk exists for acquired or developed intangible assets
- Share-based compensation can affect reported operating results

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*Last updated: 2026-09-28T11:57:38.093592+00:00*