Graph.one unlocks your network's hidden potential for strategic connections. Map the shortest, strongest paths to investors, talent, and customers within your existing contacts. Leverage Graph.one to reach out confidently, backed by data-driven insights
Hi Product Hunt,
I'd like to share the vision behind Graph.one.
Search for people and organizations is fundamentally broken. Try using Google to find an investor, doctor, or lawyer – it sucks. This isn't surprising; search engines like Google or Bing were not originally designed for these kinds of searches – their indexes are organized as graphs of documents, not social graphs. LinkedIn is often used as a substitute, but its search is limited and confined to its own platform.
We're building a search engine specifically designed for people and organizations. Imagine an index that combines data from various platforms, podcasts, research papers, conferences, public filings, licenses and more. Now, add to that your personal network from email, calendar, and social networks. The result? A powerful tool to help you find the ideal professional for any need, or the right investors for your venture, no matter how niche or complex.
Graph.one is our first step towards this vision. Here's how you can use it today:
1. Discover your connections in any city with our best-in-class location filter. I use it every time I travel for work.
2. Find who you know at a specific organization or who can introduce you, based on real interaction strength. This feature was born out of frustration with fake connections on LinkedIn.
3. Collaborate on lists of people or organizations – for example, I use this to build investor lists for our next funding round which I then share with existing investors and friends to ask for introductions.
4. Find ProductHunt users in your network to ask for support for your launch.
We're launching this early version because we value your feedback. Our current focus is on startup founders and venture investors. If you're in either group, I'd love to offer you personal onboarding and support.
We're excited to build the future of network-driven search and discovery. Try Graph.one and let us know what you think – your input will shape its evolution.
Hey Maciek,
How do you ensure user data protection, especially when integrating with email and calendar?
Have you considered adding any AI-powered features for network recommendations?
Congrats on the launch!
@kyrylosilin
Regarding Data Protection:
We have taken extensive measures, audited and verified by Google's Trust and Security Team on a regular basis, even to get access to email and calendar data.
Great data protection starts with not storing the data you do not need. e.g. We do not ask for access to email bodies, attachments etc.
After we have gotten the rather limited set of the data, we employ the following techniques (non-exhaustive list) to ensure that our user's data is protected as much as possible:
- Penetration Testing: We simulate cyberattacks on the our systems to identify vulnerabilities in the infrastructure and applications. This helps to prevent unauthorized access or data breaches.
- Vulnerability Scanning: We us automated tools to scan for known vulnerabilities in the our software, network, and databases. This helps in identifying weak points that hackers could exploit.
- Multi-Factor Authentication (MFA) Testing: We regularly test the effectiveness of additional security layers beyond just passwords.
- Data Encryption and Decryption Tests: We ensure that sensitive customer data, like account details, is properly encrypted both in transit and at rest, preventing unauthorized access during transmission or storage.
- Access Control Audits: These tests assess the our internal access controls, ensuring that only authorized personnel can access sensitive account information. These audits also look for unnecessary ACL escalations that might be possible in when using our APIs.
- Disaster Recovery and Backup Testing: We simulate situations like system failures or cyberattacks to verify that the we can quickly restore services and protect customer data without major disruptions.
Regarding AI-powered features for network recommendations:
This is a fantastic idea. And something we have been considering doing for some time. The idea being, how can we make recommendations to connect two different people in different parts of the social graph such that they both get a much stronger overall network out of such introductions. Is this how you are also thinking about this feature or do you have something else in mind?
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