{"id":19156182,"url":"https://github.com/kyegomez/whiterock","last_synced_at":"2025-07-22T12:33:37.018Z","repository":{"id":242908528,"uuid":"810957924","full_name":"kyegomez/WhiteRock","owner":"kyegomez","description":"The world's first fully automated VC fund.","archived":false,"fork":false,"pushed_at":"2025-05-26T14:37:45.000Z","size":2290,"stargazers_count":23,"open_issues_count":2,"forks_count":6,"subscribers_count":1,"default_branch":"main","last_synced_at":"2025-06-12T16:04:41.055Z","etag":null,"topics":["ai","capital","fund","llc","llp","ml","vc","venture"],"latest_commit_sha":null,"homepage":"","language":"Python","has_issues":true,"has_wiki":null,"has_pages":null,"mirror_url":null,"source_name":null,"license":"mit","status":null,"scm":"git","pull_requests_enabled":true,"icon_url":"https://github.com/kyegomez.png","metadata":{"files":{"readme":"README.md","changelog":null,"contributing":null,"funding":".github/FUNDING.yml","license":"LICENSE","code_of_conduct":null,"threat_model":null,"audit":null,"citation":null,"codeowners":null,"security":null,"support":null,"governance":null,"roadmap":null,"authors":null,"dei":null,"publiccode":null,"codemeta":null,"zenodo":null},"funding":{"github":["kyegomez"],"patreon":null,"open_collective":null,"ko_fi":null,"tidelift":null,"community_bridge":null,"liberapay":null,"issuehunt":null,"otechie":null,"lfx_crowdfunding":null,"custom":null}},"created_at":"2024-06-05T17:08:10.000Z","updated_at":"2025-04-28T16:34:15.000Z","dependencies_parsed_at":"2024-06-05T17:40:09.690Z","dependency_job_id":"22d04d0f-58b4-40fe-8f02-5078d21beab5","html_url":"https://github.com/kyegomez/WhiteRock","commit_stats":null,"previous_names":["kyegomez/whiterock"],"tags_count":0,"template":false,"template_full_name":"kyegomez/Python-Package-Template","purl":"pkg:github/kyegomez/WhiteRock","repository_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/kyegomez%2FWhiteRock","tags_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/kyegomez%2FWhiteRock/tags","releases_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/kyegomez%2FWhiteRock/releases","manifests_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/kyegomez%2FWhiteRock/manifests","owner_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners/kyegomez","download_url":"https://codeload.github.com/kyegomez/WhiteRock/tar.gz/refs/heads/main","sbom_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/kyegomez%2FWhiteRock/sbom","host":{"name":"GitHub","url":"https://github.com","kind":"github","repositories_count":266496009,"owners_count":23938645,"icon_url":"https://github.com/github.png","version":null,"created_at":"2022-05-30T11:31:42.601Z","updated_at":"2022-07-04T15:15:14.044Z","status":"online","status_checked_at":"2025-07-22T02:00:09.085Z","response_time":66,"last_error":null,"robots_txt_status":null,"robots_txt_updated_at":null,"robots_txt_url":"https://github.com/robots.txt","online":true,"can_crawl_api":true,"host_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub","repositories_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories","repository_names_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repository_names","owners_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners"}},"keywords":["ai","capital","fund","llc","llp","ml","vc","venture"],"created_at":"2024-11-09T08:33:31.567Z","updated_at":"2025-07-22T12:33:36.960Z","avatar_url":"https://github.com/kyegomez.png","language":"Python","funding_links":["https://github.com/sponsors/kyegomez"],"categories":[],"sub_categories":[],"readme":"# WhiteRock: The First Fully Autonomous VC Fund\n\n\n\nThe idea for WhiteRock emerged during a pivotal event that underscored the inefficiencies and limitations of traditional venture capital (VC) operations. Our team observed that while VCs aim to identify and invest in high-potential startups, their decision-making processes are often constrained by human factors, time zones, and the necessity of physical presence. These limitations can hinder their ability to make timely, data-driven investment decisions. This inspired us to create WhiteRock, an autonomous VC fund that leverages advanced AI and operates 24/7 to provide superior returns and revolutionize the VC landscape.\n\n\n## Install\n\n```bash\n$ pip3 install whiterock\n```\n\n## ENVs\n```\nBLAND_API_KEY=\"\"\nOPENAI_API_KEY=\"\"\n```\n\n## Usage\n```python\nfrom whiterock.main import WhiteRock\nfrom whiterock.agents import due_diligence_agent, principal_investor\n\n# Instantiate the WhiteRock class\nwhiterock = WhiteRock(\n    agents=[due_diligence_agent, principal_investor],\n    max_loops=5,\n    phone_number=\"+16505188709\",  ##+19729719060\",\n    phone_call_duration=160,\n)\n\n# Run the WhiteRock class\ntask = \"Enter in your task\"\nwhiterock.run(task)\n```\n\n## What It Does\n\nWhiteRock is designed to transform the way venture capital operates by automating the entire investment process. Here’s how it works:\n\n1. **Initial Outreach**: The system autonomously reaches out to founders and fundraisers through various channels. It can schedule and conduct interviews using natural language processing (NLP) and conversational AI.\n2. **Data Collection**: During these interactions, WhiteRock collects comprehensive data on the startup's product, business model, market traction, financials, and other critical aspects.\n3. **Analysis and Evaluation**: The collected data is then passed to the Analyst Agent, which performs a detailed evaluation using machine learning models trained on historical investment data.\n4. **Decision Making**: Based on the analysis, the Investor Agent assesses the potential and risks associated with each startup, ultimately making investment recommendations.\n5. **Continuous Monitoring**: Post-investment, WhiteRock continuously monitors the performance of portfolio companies, providing insights and recommendations to optimize returns.\n\n## How We Built It\n\nWhiteRock was built using a combination of **Bland.ai API** and our proprietary **Swarms Framework**. Here’s a breakdown of the development process:\n\n### Bland.ai API\n\n- **Conversational AI**: We utilized Bland.ai's state-of-the-art NLP capabilities to enable WhiteRock to autonomously conduct conversations with startup founders. This includes initial outreach, data collection, and follow-up interactions.\n- **Data Processing**: Bland.ai's robust data processing tools allowed us to seamlessly integrate and manage large volumes of data collected from various sources.\n\n### Swarms Framework\n\n- **Modular Architecture**: Our Swarms Framework is designed to be highly modular, allowing us to create specialized agents for different tasks within the VC process.\n- **Scalability**: The framework is built to scale efficiently, handling an increasing number of startups and investors without compromising performance.\n- **Integration**: We integrated various tools and APIs to ensure seamless communication and data flow between agents, enhancing the overall efficiency of the system.\n\n## Challenges We Ran Into\n\nDeveloping WhiteRock was not without its challenges. One of the biggest hurdles was addressing the human factors inherent in VC decision-making. Traditional VCs rely heavily on intuition, personal connections, and subjective judgment, which are difficult to replicate in an autonomous system. Additionally:\n\n- **Data Sensitivity**: Ensuring the privacy and security of sensitive startup data required implementing robust encryption and access control measures.\n- **AI Bias**: Mitigating biases in AI models was crucial to ensure fair and accurate evaluations of startups.\n- **Complex Interactions**: Simulating complex, nuanced human interactions with founders required advanced NLP techniques and extensive training data.\n\n## Accomplishments That We're Proud Of\n\nDespite these challenges, we achieved significant milestones, including:\n\n- **First Demo in 5 Minutes**: We successfully demonstrated the core functionality of WhiteRock within just five minutes of launching the prototype. This rapid deployment showcased the system's efficiency and potential impact.\n- **24/7 Operation**: WhiteRock’s ability to operate continuously without human intervention is a groundbreaking achievement, ensuring that no investment opportunity is missed due to time constraints.\n- **Scalable Architecture**: Our modular and scalable architecture allows WhiteRock to handle an expanding portfolio of startups and investors seamlessly.\n\n## What We Learned\n\nThe journey of building WhiteRock provided us with valuable insights, including:\n\n- **Importance of Data Quality**: High-quality data is essential for accurate analysis and decision-making. Ensuring data integrity and reliability was a top priority.\n- **Human-AI Collaboration**: While automation can significantly enhance efficiency, human oversight remains important in refining AI models and handling exceptional cases.\n- **Continuous Improvement**: The AI models and algorithms powering WhiteRock require continuous updates and improvements to adapt to changing market conditions and emerging technologies.\n\n## What's Next for WhiteRock\n\nAs we look to the future, several exciting developments are on the horizon for WhiteRock:\n\n- **Expanding Capabilities**: We plan to enhance WhiteRock’s capabilities by incorporating more advanced AI technologies, such as deep learning and reinforcement learning, to further improve its decision-making processes.\n- **Global Reach**: Expanding our reach to global markets will enable us to tap into a broader pool of innovative startups and provide more diverse investment opportunities.\n- **Human-AI Synergy**: We aim to foster greater synergy between human investors and AI, leveraging the strengths of both to achieve optimal investment outcomes.\n- **Enhanced Monitoring and Support**: Post-investment, we will develop more sophisticated monitoring tools to provide real-time insights and support to portfolio companies, ensuring they achieve their full potential.\n- **Community Engagement**: Building a community of founders, investors, and industry experts around WhiteRock to share insights, best practices, and foster collaboration.\n\n## Conclusion\n\nWhiteRock represents a pioneering step in the evolution of venture capital. By leveraging AI and automation, we aim to create a more efficient, scalable, and impactful investment process. Our journey is just beginning, and we are excited to continue pushing the boundaries of what’s possible in the world of venture capital.\n\n# Next steps\n- [Tool Integrations: Mercury for bank transcations, api for sending money, api for trackinv investments like carta]\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fkyegomez%2Fwhiterock","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fkyegomez%2Fwhiterock","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fkyegomez%2Fwhiterock/lists"}