Predax's answer

• All-in-one protection: VPN/proxy/Tor detection, risk scoring, geolocation, WAF, and community threat intelligence in a single API — competitors like IPQualityScore and MaxMind charge separately for each
• WordPress-native: Ready-made plugins for WordPress and WooCommerce with guided setup wizards. Competitors like Sift and IPinfo require custom development
• Price: Plans start at $9/month. Comparable coverage from IPQualityScore starts at $49/month, Sift at $500+/month
• No contracts or minimums: Pay monthly, cancel anytime. Scale up or down as your traffic changes
• Real-time data: Tor exit nodes refresh hourly, proxy lists every 15 minutes, VPN feeds daily. Many competitors update weekly or less

LayerCall's answer:

Because of what comes back in the response, not what it costs.

Every result carries a 0–100 risk score, an allow / review / block verdict, and the individual signals behind it — so a decision can be explained to a customer, a colleague or an auditor rather than only made. Strictness is tunable per request without re-scoring, which means the same integration can be strict at signup and forgiving at login.

Two smaller things tend to matter more in production than they sound. When a data source is unavailable, the response says so instead of quietly scoring lower, so an incomplete answer stays distinguishable from a clean one. And test keys return fixed, fictional data that never bills and never touches live reputation data, so a test suite can assert on exact values without polluting anything.

Beyond that, it is worth comparing directly rather than taking our word for it: the live demo runs the real scoring engine with no signup, and the free tier needs no card.

Predax's answer

• WordPress & WooCommerce site owners losing ad revenue or suffering fraud from VPN/proxy traffic
• E-commerce developers building checkout fraud prevention into custom platforms
• Ad-tech companies needing to filter non-human and anonymised traffic to protect revenue
• SaaS platforms preventing abuse, trial fraud, and account takeover from masked IPs
• Security teams adding IP-level threat intelligence to their existing stack via API

LayerCall's answer:

Developers and small product teams who need a trust decision at signup, login or checkout, and who would rather call one endpoint than integrate several vendors and reconcile their answers by hand.

In practice that means SaaS signups, marketplaces, fintech onboarding, and anyone whose free tier is being farmed by throwaway accounts.

A newer part of the audience is teams who suddenly have to decide what an AI agent may do on their site. That is a different question from classical fraud — an agent can be entirely legitimate and still need a policy — which is why agent verification sits in the same API rather than in a separate product.

Predax's answer

• Backend API: Python, FastAPI, PostgreSQL, Redis, Celery
• Frontend: Next.js (React), TypeScript, Tailwind CSS
• Infrastructure: Docker, Caddy (reverse proxy), automated CI/CD
• Machine Learning: scikit-learn (GradientBoosting risk model trained on real threat data)
• Plugins: PHP (WordPress & WooCommerce native), JavaScript
• Data sources: Real-time feeds from Tor Project, public proxy lists, VPN provider APIs (NordVPN, Mullvad), cloud provider IP ranges (AWS, GCP, Azure, DigitalOcean, Vultr), RIPE/BGP ASN data

LayerCall's answer:

TypeScript on Next.js, running on Vercel's Fluid Compute, with Postgres (Supabase) behind accounts, keys and usage.

The scoring path is deliberately boring. No third-party SDK sits in the request path; every external feed is fetched under its own timeout inside a request-wide deadline, so one slow source cannot hold up a response. A feed that fails degrades the result rather than failing the call, and the response names any signal that was unavailable so the caller can tell the difference between a clean answer and an incomplete one.

On the client side: official Node/TypeScript and Python SDKs, Express and Next.js middleware, a published OpenAPI spec, and an MCP server so AI tools can call the API directly.

Predax's answer

IPSentry is used by WordPress site owners, WooCommerce stores, and developers across multiple countries. As a privacy-focused company, we don't publicly disclose customer names without their permission.

Predax's answer

IPSentry started from a personal frustration. I was running content sites monetised with Google AdSense, and kept getting hammered by waves of VPN and proxy traffic. This non-genuine traffic was dragging down my overall RPM — advertisers don't pay premium rates when their ads are being served to masked, unverifiable visitors. My revenue was suffering and I had no visibility into what was hitting my sites.

I wanted control over my traffic. I wanted to see exactly who was visiting, filter out the junk, and make informed decisions about what to allow and what to block. I looked for a WordPress plugin that could do this — detect VPN and proxy visitors, flag them, let me decide what to do — and found nothing that actually worked. The few options that existed were either broken, absurdly expensive, or required wiring up an external API with custom code.

So I built my own. It started as a simple IP lookup tool, then grew into a full detection API with VPN, proxy, Tor, and datacenter identification. I added a WordPress plugin so any site owner could install it in one click and immediately see and control their traffic, then a WooCommerce plugin for fraud prevention at checkout.

The Community Threat Network came next — the idea that when one site blocks a bad actor, every other IPSentry user benefits from that intelligence. Today IPSentry protects sites across multiple countries with millions of IP lookups per month.

LayerCall's answer:

It started from a specific frustration: the signal that actually catches a fake signup is usually a relationship between fields, and the tools available answered one field at a time.

Blocking disposable email domains stops very little on its own. The signups that matter use real mailboxes, often on domains registered days earlier, arriving from addresses that look entirely ordinary. What gives them away is the domain's age set against the IP's provider set against whether the phone is a VoIP line — and assembling that meant several vendors, several response shapes, several bills, and writing the correlation by hand anyway.

LayerCall is that correlation as a product: one call, every signal, and the reasoning returned next to the score.

The AI-agent side came later, from the same observation in a new place. An agent has a real browser, a real fingerprint and a real mailbox, so nothing in a classical fraud stack has an opinion about it. What you need to know is which agent it is and whether it can prove it — a signature problem, not a fraud-signal problem.

Predax's answer

IPSentry combines real-time IP intelligence with community-powered threat detection — something no other provider offers at this price point.

• Community Threat Network: Every block reported by any IPSentry user strengthens protection for all users. When one site blocks a bad actor, every other site knows about it instantly
• Purpose-built WordPress & WooCommerce plugins with one-click install — no code required. Most competitors are API-only
• Transparent risk scoring: Every score comes with full provenance showing why an IP was flagged (VPN, Tor, proxy, datacenter, WAF attack, community reports), not just a black-box number
• Built-in WAF: SQL injection, XSS, path traversal, and scanner detection included — not a separate product or add-on
• Generous free tier: 1,000 lookups/month free, with paid plans starting at just £5/$7 per month

LayerCall's answer:

Most fraud APIs answer one question per call — is this IP a VPN, is this email disposable, is this phone real. LayerCall returns IP, email, phone, domain and device together, and scores the relationships between them. A brand-new domain paired with a datacenter IP and a throwaway mailbox is obvious in combination and unremarkable one field at a time.

Every response also carries the reasoning: a 0–100 risk score, an allow / review / block verdict, and the individual signals behind it, so a decision can be explained rather than only made.

It treats AI agents as a first-class case as well. Web Bot Auth signature verification establishes which agent is calling and whether it can prove it, and a policy engine decides what it is allowed to do — a question classical fraud signals cannot settle, because an agent arrives with a real browser, a real fingerprint and a real mailbox.