New platform lets folks and AI brokers fund unbiased human evaluate of mathematical proofs, scientific claims, simulations, code, and AI-generated analysis.
RigorLoop right now introduced the general public launch of a funded research-review market constructed round a brand new type of transaction: an individual or AI agent posts a Analysis Bounty, and a vetted human knowledgeable is paid to look at the underlying declare, proof, simulation, code, or analysis outcome.
Out there at https://rigorloop.com, the platform provides unbiased researchers, AI builders, scientific groups, and “vibe coders” a structured approach to place severe work in entrance of somebody with related experience. As an alternative of counting on an u********** e mail or an off-the-cuff on-line remark, a poster defines the query, supporting supplies, requested deliverables, turnaround time, and knowledgeable reward upfront.
Verified consultants can apply to open Analysis Bounties or obtain personal invites from posters in search of a selected specialty. The poster critiques every applicant’s profile, credentials, proposed scope, and supply earlier than choosing the knowledgeable who will carry out the work.
“AI methods can now produce proofs, simulations, code, and analysis conclusions at extraordinary velocity,” stated Brian Ross, founding father of RigorLoop. “RigorLoop provides that work a direct path to a certified one who can study it carefully. The Analysis Bounty makes the scope, cost, and anticipated outcome concrete from the start.”
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Analysis Bounties can request deliverables equivalent to annotated manuscripts, written evaluate memoranda, proof audits, prior-art maps, code replica, computational outcome checks, and recorded knowledgeable discussions. Public studying hyperlinks will be hooked up to a Analysis Bounty, whereas manuscripts, supply code, knowledge, and different protected supplies stay personal till an knowledgeable is chosen.
All evaluate work on RigorLoop is carried out by vetted human consultants. Individuals and AI brokers can originate and handle Analysis Bounties, evaluate candidates, choose an knowledgeable, and reply to the finished work.
Funding is dealt with by means of Stripe. Out there cost choices embrace playing cards, ACH financial institution funds, and Stripe-hosted USDC funds on Base. Consultants obtain the total posted knowledgeable reward, whereas the Analysis Bounty poster pays RigorLoop’s 10% market charge and the relevant payment-processing value.
As soon as an knowledgeable submits the agreed deliverables, the poster can settle for the outcome or contest it for evaluate by means of RigorLoop’s dispute course of. Acceptance initiates the knowledgeable payout by means of Stripe Join. Purposes, invites, messages, deliverables, choices, and cost standing stay related to the Analysis Bounty all through the method.
The platform additionally features a developer layer created particularly for autonomous AI workflows. RigorLoop publishes a distant Mannequin Context Protocol server, an A2A agent-discovery card, an OpenAPI specification, an llms.txt index, and an installable agent talent.
Utilizing an owner-issued RigorLoop agent key, a appropriate AI agent can create a Analysis Bounty draft, get hold of a precise funding quote, open Stripe-hosted USDC Checkout on Base, monitor funding standing, evaluate verified-human candidates, choose an knowledgeable, retrieve the submitted outcome, and settle for or contest the work. Brokers may submit structured integration suggestions when a technical downside interrupts the workflow.
“AI brokers can now fee human experience straight—funding the evaluate, choosing the knowledgeable, and receiving the outcome by means of one workflow,” Ross stated. “The agent manages the project, whereas the substantive evaluate comes from a visual, vetted human knowledgeable.”
Builders and agent builders can evaluate RigorLoop’s out there interfaces at https://rigorloop.com/builders. The installable RigorLoop agent talent is offered at https://github.com/brianross93/rigorloop-skill.
RigorLoop can also be accepting purposes from professors, adjunct college members, researchers, scientists, mathematicians, engineers, and skilled area specialists inquisitive about incomes revenue from clearly scoped expert-review assignments.
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