Ubio Obu

Project Owner

OmniForge: Agentic Ready IDE for the ASI:Chain

Expert Rating

n/a

Type SingularityNET RFP
Funding Request n/a
RFP Guidelines An AI-native Development Environment for the ASI:Chain

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Overview

We are the team behind Omnideamon, a framework-agnostic event-driven runtime that turns AI agents into production-grade, autonomous infrastructure services, and OmniCoreAgent, a powerful Python framework for building autonomous AI agents that think, reason, and execute complex tasks. We propose to adapt our production-tested AI agent framework, which currently has 228 GitHub stars and over 10,000 downloads, into the first AI-native IDE for ASI: Chain.

RFP Guidelines

Internal Proposal Review

An AI-native Development Environment for...

Ended on:

13 Feb. 2026

Days

Hours

Minutes

Type SingularityNET RFP
Total RFP Funding $50,000 USD
Proposals 27
Awarded Projects n/a

SingularityNET

Feb. 4, 2026

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This RFP seeks proposals for the development of an AI-native Development Environment (IDE) that improves the efficiency and accessibility of blockchain application development for the ASI:Chain.

Proposal Description

Proposal Details Locked…

In order to protect this proposal from being copied, all details are hidden until the end of the submission period. Please come back later to see all details.

Total Milestones
4
Total Budget
$50,000_USD
Last Updated
13 Feb 2026

Milestone 1 - The Foundation Layer

Description

-Browser-based IDE with file management. -"One-Click DevNet" (spins up `rnode` container)

Deliverables

OmniForge IDE v0.1 + OmniDaemon Local Node (Docker Adapter)

Budget

$15,000 USD

Success Criterion

-Browser-based IDE v0.1 working (file create/edit/save) -One-click local ASI node starts in <60 seconds -Demo video shows IDE + node start + logs

Milestone 2 - The Intelligence Layer

Description

-Natural Language to Rholang transpiler (using RAG context). -Integrated Chat Window for "Agent Help".

Deliverables

OmniCoreAgent Integration + "Vibecoding" Interface

Budget

$15,000 USD

Success Criterion

-Chat accepts natural language prompt -Generates valid Rholang code from 3 different examples -Demo video shows prompt → code generation → editor

Milestone 3 - The Ecosystem

Description

Experimental MeTTa syntax highlighting and snippets. `omni-cli` for terminal-based node management.

Deliverables

MeTTa Support (Research Preview) + CLI Tools

Budget

$10,000 USD

Success Criterion

-MeTTa syntax highlighting + basic snippets working -omni-cli starts/stops node and shows logs -Demo video shows MeTTa code editing in IDE

Milestone 4 - The Launch

Description

-Production deployment of OmniForge. -"OmniCoreAgent Academy" (interactive tutorials).

Deliverables

Public Release + Documentation + tutorials

Budget

$10,000 USD

Success Criterion

-Production IDE released -ASI Wallet connects and signs transactions -Block explorer view shows chain state/transactions -3 tutorial videos published

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The weighted average of the 4 perspectives Overall

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The weighted average of the 4 perspectives Overall

0.0
Each RFP defines a maximum allowed budget, but teams can differentiate their proposal by offering a solution with a lower budget or a wider scope.Value for money

0.0
This rating indicates compliance to 'Must haves' but also adaptation of 'Nice to haves' and Non-functional requirements defined in the RFP.Compliance with RFP requirements

0.0
RFPs will offer varying degrees of freedom. This rating indicates the quality of the team's specific solution ideas, the provided details, and the reviewer's confidence in the team's ability to execute.Solution details and team expertise

0.0

Review Headline

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Reviews and Ratings in Deep Funding are structured in 4 categories. This will ensure that the reviewer takes all these perspectives into account in their assessment and it will make it easier to compare different projects on their strengths and weaknesses. Overall (Primary) This is an average of the 4 perspectives. At the start of this new process, we are assigning an equal weight to all categories, but over time we might change this and make some categories more important than others in the overall score. (This may even be done retroactively). Feasibility (secondary) This represents the user\'s assessment of whether the proposed project is theoretically possible and if it is deemed feasible. E.g. A proposal for nuclear fission might be theoretically possible, but it doesn’t look very feasible in the context of Deep Funding. Viability (secondary) This category is somewhat similar to Feasibility, but it interprets the feasibility against factors such as the size and experience of the team, the budget requested, and the estimated timelines. We could frame this as: “What is your level of confidence that this team will be able to complete this project and its milestones in a reasonable time, and successfully deploy it?” Examples:

A proposal that promises the development of a personal assistant that outperforms existing solutions might be feasible, but if there is no AI expertise in the team the viability rating might be low.
A proposal that promises a new Carbon Emission Compensation scheme might be technically feasible, but the viability could be estimated low due to challenges around market penetration and widespread adoption.

Desirability (secondary) Even if the project team succeeds in creating a product, there is the question of market fit. Is this a project that fulfills an actual need? Is there a lot of competition already? Are the USPs of the project sufficient to make a difference? Example:

Creating a translation service from, say Spanish to English might be possible, but it\'s questionable if such a service would be able to get a significant share of the market

Usefulness (secondary) This is a crucial category that aligns with the main goal of the Deep Funding program. The question to be asked here is: “To what extent will this proposal help to grow the Decentralized AI Platform?” For proposals that develop or utilize an AI service on the platform, the question could be “How many API calls do we expect it to generate” (and how important / high-valued are these calls?). For a marketing proposal, the question could be “How large and well-aligned is the target audience?” Another question is related to how the budget is spent. Are the funds mainly used for value creation for the platform or on other things? Examples:

A metaverse project that spends 95% of its budget on the development of the game and only 5 % on the development of an AI service for the platform might expect a low ‘usefulness’ rating here.

A marketing proposal that creates t-shirts for a local high school, would get a lower ‘usefulness’ rating than a marketing proposal that has a viable plan for targeting highly esteemed universities in a scaleable way.
An AI service that is fully dedicated to a single product, does not take advantage of the purpose of the platform. When the same service would be offered and useful for other parties, this should increase the ‘usefulness’ rating.

Ubio Obu

Project Owner

Project and AI team Lead

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abiola adeshina

AI/Web3 Architect

Infrastructure layer build of the project

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Account Pending

Full Stack dev

Integrations of builds into the interface and performance optimization

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