GeoSure is the world’s most trusted safety intelligence engine. Now more than ever, in a volatile world, our breadth and depth are essential to informed decisions about your people, your facilities, and your company’s future.
We provide actionable insights into more than 200 countries, covering and scoring 850,00 cities and neighborhoods within them. Our real-time data includes six dimensions of safety: Physical Safety, Theft, Women’s Safety, LGBTQ+ Safety, Health, Nighttime Safety and Political Freedoms.
Our AI ingests and analyzes more than 100,00 content sources and data feeds every day - across 60 languages - including essential sources like verified conflict databases and government crime statistics, as well as more nuanced sources of risk and safety critical events. Our built-in cross-referencing redundancy, refined over 12 years - assures accurate and trustworthy information.
We built our proprietary MCP – Model Context Protocol – because as smart as your internal AI may be, its intelligence is limited to the data it’s getting.
Without your AI plugging into GeoSure, you’re stuck with general knowledge and those limits are real: cutoff dates, web search results in English, no real-time awareness of what’s happening at street level.
With GeoSure’s MCP connected, every query your AI makes about a location is answered with verified, current, neighborhood-level intelligence.
Request MCP API documentation
Can't we just use ChatGPT or Claude for location intelligence?
Three problems with that approach. First, every travel itinerary, GPS position, or personnel location you paste into a public LLM leaves your governance boundary the moment it hits the API — with no verifiable audit trail. Second, general LLMs hallucinate geography. They can't monitor dozens of locations persistently, can't access social channels or local-language platforms where ground-level intelligence actually lives, and can't push a structured alert when something material changes. Third, you're locking into token pricing with no hedge. GeoSure's MCP architecture keeps your data inside your own infrastructure, delivers purpose-built geographic intelligence that no public LLM can replicate, and stays model-agnostic — swap the underlying AI without rebuilding a thing
Who built GeoSure's safety scoring methodology and why?
Who: Developed by Dr. Donald Pardew, a national security systems engineer and a Columbia University research scientist.
Why: Before GeoSure, there was no quantitative way to score geospatial safety, and no granularity beyond the country level. Travelers and citizens had no way to discern safety at the city or neighborhood level — even in places where risk varies dramatically block by block.
Why buy GeoSure instead of building our own travel safety capability?
This isn't a data feed you can license or a model you can prompt-engineer. It's 12 years of methodology across 200+ countries, continuously updated, and ISO 31030-ready out of the box. Building it yourself takes a decade.
How many POI’s (Points of Interest) does GeoSure cover?
71M Points of Interest
How do I integrate it?
1. Point your AI tool to GeoSure. One endpoint: serve.geosure.ai/mcp — nothing else required.
2. No code. No IT ticket. No new software. Works with Claude, ChatGPT, and any AI tool that supports MCP.
3. Live in under five minutes. Ask your first question about any location on Earth.
What does it cost?
Today's risk intelligence platforms charge $100k+/year for country-level PDFs. We charge a fraction of that for neighborhood-level intelligence, delivered instantly to the AI tools you already use.
Book a 10-minute call — we’ll give you a number based on your enterprise’s use case in the first conversation.
