ubiquity / series-a

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Pitch Materials #13

Open 0x4007 opened 2 months ago

0x4007 commented 2 months ago

We need to create a deck for series A.

Use our old deck as reference.

The old fundraising folder might be useful context.

Looks like we had 16 iterations on the first version throughout our six month fundraising cycle. So that means that every 2-3 weeks we should be iterating based on feedback from investors if we're taking last time as a case study.

Highlights

We need to amplify this messaging. I'll refine this over time:

We have an AI powered, distributed worker management system, and a stablecoin. When contributions are made to completed work, payouts are earned. We currently handle payouts in crypto and want to expand our offering to virtual/physical cards. Any idle capital in our system we earn interest on, leveraging our stablecoin solution. In this sense we are building a neobank with a built-in end-to-end solution for coordinating global teams.

We have $2.25M USD currently in our corporate treasury from our seed round two years ago, which translates to a 4.5 year runway.

Research Tasks

TBD

Drafts

Now available in the Series A folder.

0x4007 commented 1 month ago

@sergfeldman I can use some help on this I sort of hit a wall and can't make progress. Please duplicate my latest deck, retain the "minor" version number in the title (v0.3) and you can increment the "patch" (v0.3.1) so that we know which version is your base.

It would be appreciated if you can help me push forward based on the competitor research. I've been quite fatigued this week.

0x4007 commented 1 month ago

I keep losing this competitor analysis so putting here for reference https://github.com/ubiquity/research/issues/141#issuecomment-1990971293

0x4007 commented 1 month ago

Generative marketing copy exercise (I think only fetch is really useful.)

ChatGPT inspired by perplexity's fetch.ai summary:

The DevPool is a cutting-edge platform specializing in developer tooling on GitHub, harnessing the power of artificial intelligence (AI) and machine learning (ML) to streamline the development process and enhance productivity. We provide an innovative infrastructure where developers can create, manage, and optimize their GitHub workflows, leveraging AI-driven technologies to automate tasks, improve code quality, and facilitate collaboration at scale.

The DevPool platform utilizes a proprietary stablecoin for transactions within the ecosystem, rewarding contributions and facilitating access to premium tools and services. This approach not only incentivizes participation but also fosters a vibrant community of developers and contributors.

With applications that span across the software development lifecycle, the DevPool ecosystem is versatile, supporting everything from code analysis and bug detection to automated pull request reviews and integration testing. We enable secure, efficient access to code repositories and support the development of decentralized applications (dApps) that can streamline project management and collaboration efforts.

Built on modern, scalable technology, the DevPool platform emphasizes interoperability, allowing for seamless integration with various tools and services within the developer ecosystem. The DevPool AI components, tailored for developer needs, address complex challenges by combining the precision of machine learning with the flexibility of AI to offer solutions that surpass traditional automation tools.

The DevPool is recognized for its potential to revolutionize how developers work on GitHub, offering tools that optimize workflows, enhance code quality, and automate mundane tasks, thereby freeing developers to focus on innovation and creativity. We are committed to democratizing access to AI technology for developers, changing the way software is built, and making development more efficient and accessible to all.

Delysium (not useful):

Our company leverages a cutting-edge architecture to foster an expansive ecosystem focused on security, scalability, and rapid communication. Central to our approach are two layers: the Communication (or Fundamental) Layer for core interactions, and the Blockchain Layer for enhanced security and governance. This structure supports a dynamic environment where a network of AI agents and users can grow, interact, and innovate. Integrating blockchain, we ensure transparency and security, aligning with human values while promoting continuous development within our community.

Autonolas:

DevPool leverages advanced architecture and tokenomics, focusing on developer tooling on GitHub. It aims to revolutionize the development process by introducing a multi-agent systems architecture, consensus for service operations, and a unique approach to crypto-native off-chain services. Through innovative tokenomics, DevPool incentivizes developers, fosters a community of contributors, and facilitates a market for code value, aiming to create a virtuous cycle of innovation and growth within the GitHub ecosystem.

DevPool is a platform focused on enhancing developer tooling on GitHub, inspired by Olas's decentralized framework for autonomous services. It bridges the gap between traditional and blockchain development, offering a robust framework for creating, deploying, and managing software services with minimal human intervention. DevPool emphasizes decentralized governance through a DAO structure, incentivizes contributions via tokenomics, and relies on a multi-agent systems architecture for scalable, off-chain functionality with on-chain governance, fostering a community-driven ecosystem for continuous innovation in developer tools.

Morpheus:

Morpheus is a peer-to-peer network focusing on generative AI, emphasizing decentralization. As an open-source platform, it supports the development and deployment of generative AI services via a peer-to-peer infrastructure. This approach seeks to revolutionize generative AI technologies by offering an alternative to traditional centralized systems, promoting collaborative advancement in the AI field. For more details, visit their website.

sergfeldman commented 1 month ago

@pavlovcik We can review the structure of fetch.ai pitchdeck and use a similar one for ours https://drive.google.com/file/d/1CyMpVAXbv4YkRXLROv91zDbHOVPaCC-f/view?pli=1

0x4007 commented 1 month ago

@pavlovcik We can review the structure of fetch.ai pitchdeck and use a similar one for ours

https://drive.google.com/file/d/1CyMpVAXbv4YkRXLROv91zDbHOVPaCC-f/view?pli=1

I actually don't think that their deck is good. Are you sure that's the real one?

sergfeldman commented 1 month ago

I took this pitch deck from open sources, not from fetch.ai itself, so I can’t guarantee that this is the final version.