Roadmap

Our mission to build an innovative platform for the democratisation and decentralisation of data processing, artificial intelligence and machine learning requires an ambitious roadmap that is able match the objectives we have previously set.

We are currently close to finalising the initial phase of demonstrating the feasibility and applicability of Timeworx.io, on our path from MVP to the Public Launch. Along the way we have checked off impressive achievements: we have successfully deployed our solution on, not one, but two Blockchain networks, we have forged long-lasting partnerships, and we have attracted more than 1,500 active users that are hungry for solving data processing tasks.

What’s still to come?

• Public Sale

• Mainnet launch on Injective and MultiversX

• Rewarding our loyal community with bountiful airdrops

• Public Release of our mobile applications on the Apple App Store and the Android Play Store

But this is only the beginning! We are now able to focus on the objectives for developing the future of AI & data processing, with clear targets on the commercial success of our platform.

Firstly, we will continue to further develop our data labelling capabilities in terms of both technological advancements, as well as in terms of curating our community of Human Agents. At this stage, we will also be able to validate our Customer Discovery process, and start building our sales funnel towards achieving at least 10 paying customers.

We have set forth the following steps:

• University Outreach Programme: discover & fund academic research projects that are in dire need of data processing. With a plethora of data and use-cases, these flagship projects will provide additional requirements for our platform.

• Console Application: our one-stop-shop web app that enables our customers to easily design, deploy and run their data processing pipelines.

• Web Client: a truly multi-platform implementation for our data processing crowdsourcing app by supporting both web and mobile natively.

• Gamification features: implementing awards & penalties, custom-tailored improvements paths and leaderboards & challenges for incentivising Human Agents to be more responsible, engaged and constantly seeking to improve their performance

• Community growth: we will be integrating educational modules in our mobile application that will incentivise the adoption of our platform to a growing community of Human Agents.

Subsequently, in the following years, we will be focusing on gaining more business, and scaling our Customer Discovery process to be able to reach up to 350 paying customers. At this stage, we will be actively engaged in the integration of automated data processing capabilities:

• Identifying & initiating key partnerships with mobile-edge computing facilities

• Creating flagship use-cases for Federated Learning

• Implementing and publishing the Agent Node packaging support

• Onboarding a large number of AI Agents into the platform