Built by people who
needed this themselves

The origin

Superscan started inside OpenIR, where we're building an AI platform for Investor Relations. In IR, tracking market movements, executive changes, and regulatory shifts isn't a nice-to-have — it's the job. Our IR clients needed to stay on top of everything happening around their portfolio companies, and doing it manually meant checking dozens of sources, filing away fragments of information, and hoping nothing slipped through the cracks.

We started building internal AI agents to help us stay on top of all of this. The first version was a simple pipeline: take a plain-English description of what to track, generate search queries, scan the web, and score results for relevance. We then helped some of our clients set up similar agents to monitor news about their portfolio companies. The feedback loop was the breakthrough — when users could tell the agent "this is relevant" or "not useful", the system learned what actually mattered and the noise dropped dramatically.

Along the way, we realized the core idea — describe what to track in plain English, let an AI agent scan and learn — was useful far beyond Investor Relations. So we packaged it as Superscan: a standalone product open to every use case. Competitive intelligence, fundraising signals, tech trends, regulatory watch, geopolitical risk — anywhere you need to stay informed without the manual work.

How does Superscan work?

Superscan is an AI-powered web monitoring platform. You describe what you want to track in plain English — "Alert me when any competitor launches a new feature or changes pricing" — and the system handles everything else. It generates targeted search queries, scans thousands of sources on a schedule (hourly, daily, or weekly), scores every result for relevance on a 0-100 scale, and surfaces only the alerts that matter.

Under the hood, Superscan uses Claude by Anthropic as its reasoning engine. Claude understands the intent behind your monitoring instructions, evaluates search results for relevance, and incorporates your thumbs-up/thumbs-down feedback to improve its scoring over time. The result is an autonomous monitoring agent that gets sharper with every scan cycle — reducing noise and surfacing higher-quality alerts as it learns your preferences.

Superscan searches across news sites, company blogs, social media, regulatory databases, financial filings, academic papers, forums, and more. Each use case comes with specialized source lists and scoring frameworks, so your watcher is expert-grade from day one.

The team

Superscan is built by the founding team at OpenIR. We spent years building AI-powered monitoring and analysis tools for the financial services industry, and Superscan is where we bring that expertise to a broader audience. We're a small, focused team that cares deeply about building tools that actually work — no enterprise sales cycles, no week-long onboarding, no noise.

Our approach

We believe monitoring tools should be simple to set up, transparent in how they work, and get better over time without manual tuning. Most monitoring tools in the market are either too simple (keyword matching with no intelligence) or too complex (enterprise platforms that take weeks to configure). Superscan sits in the middle: AI-powered intelligence with a 30-second setup.

We also believe in honest pricing and transparent AI. Our plans start at $9/month, there's no black box — you can see the scanning prompt your agent uses, review every scored result, and your feedback directly shapes how the system learns. If an alert is wrong, tell it. The agent adjusts.

Get in touch

We'd love to hear from you — whether it's feedback, feature requests, partnership ideas, or just saying hello. We read every message.

support@superscan.run