Zipline Reloaded
github.comMaintain event-driven Python backtests with the Zipline research model
Maintain event-driven Python backtests with the Zipline research model
Compare company research with options strategy simulations
AI content engine for startups to research, draft, publish, and track content
A Python property-based testing library that generates inputs to challenge the properties your code should preserve.
Generate trading rules and test how their results withstand changes
Develop Python strategies with graphical backtesting and market gateways
Host coded or visual strategies through shared broker connections
Link customer feedback and product strategy to prioritization, roadmaps, and delivery views.
Develop and compare trading strategies in a Windows backtesting workspace
Connect product strategy, feature priorities, and delivery plans in visual roadmaps.
Compare Google rankings and AI-answer visibility around the same keyword strategy.
Use enterprise Kanban boards and Lean metrics to follow work from planning through delivery.
Choose Indian stock screens, options tools and chart workspaces
Ask questions across a client project and get answers linked to the original passages.
Build trading algorithms with AI, backtest them, then execute on one platform.
Product management system that grounds decisions in customer signals
AI chatbots and channel strategy tools for customer service automation
AI marketing assistant that builds ICPs, strategies, ads and social content for agencies and consultants.
AI OKR and performance management software with three named AI models
Use a shared Microsoft canvas for brainstorming, planning, templates, and image export.
Online PTE preparation with mock tests, automated scoring, strategy videos and study planning.
Explore crypto derivatives and purchase selected historical datasets
Social competitor benchmarks, content themes and exportable reporting
AI trading copilot for market research, strategy and execution.