Level Up Your Cyber Defense with External Threat Management
See every risk before it hits. From exposed data to dark web chatter. All in one unified view.
Move beyond alerts. Gain full visibility, context, and control over your external attack surface to stay ahead of every threat.
Try for Free
Say goodbye to broken revenue funnels and poor customer experiences
Connect and coordinate your data, signals, tools, and people at every step of the customer journey.
LeanData is a Demand Management solution that supports all go-to-market strategies such as account-based sales development, geo-based territories, and more. LeanData features a visual, intuitive workflow native to Salesforce that enables users to view their entire lead flow in one interface. LeanData allows users to access the drag-and-drop feature to route their leads. LeanData also features an algorithms match that uses multiple fields in Salesforce.
Fully written in python which is one of the most used programming languages due to its simplified syntax and shallow learning curve. It is the first time in history that users, regardless of their background, can so easily add features to an investment research platform. The MIT Open Source license allows any user to fork the project to either add features to the broader community or create their own customized terminal version.
A portfolio-optimizer using Markowitz(1952) mean-variance model
PortOpt [Portfolio Optimizer] is a C++ program (with Python binding) implementing the Markowitz(1952) mean-variance model with agent's linear indifference curves toward risk in order to find the optimal assets portfolio under risk.
You have to provide PortOpt (in text files or - if you use the api - using your own code) the variance/covariance matrix of the assets, their average returns and the agent risk preference.