The Neuronify model
How it works: from brief to a vetted AI team
Real AI talent is hard to judge from the outside — anyone can claim it, demos take a weekend, and interviews reward performance. So we run a matching model instead of a marketplace: you describe the project once, and we bring you two or three people we have already verified.
The short version: you submit a two-minute brief, take one fifteen-minute scoping call, and interview two to three hand-picked matches with verified production work. Everything up to the engagement is free; when you do engage, the terms — including our fee — are written into the proposal where you can read them. Most engagements start within two to three weeks of the brief.
The model exists because the alternative fails predictably. Open marketplaces hand you two hundred profiles and make the screening your problem. Recruiters forward keyword matches. Big consulting firms staff junior teams behind a partner’s logo. Each of those routes works for someone — the comparison is laid out honestly in our guide to AI staffing models — but none of them solves the actual problem, which is verification.
The five steps, start to finish
1. Submit a project brief
A few sentences on what you want to build, your budget range, and your timeline. Two minutes, free, no obligation — and no account to create. We read every brief ourselves; nothing is auto-routed by keyword.
2. One scoping call
If the project looks like a fit for the bench, we book fifteen minutes to understand it properly: what exists today, what "working" would mean, who will own the system after launch. This is a scoping conversation, not a sales pitch — and if we are not the right route, we say so on this call.
3. Two to three curated introductions
You get hand-picked matches — independent engineers or specialized teams whose verified production work fits your problem, not a directory of two hundred profiles to sift. Each introduction comes with why we chose them: the systems they have shipped and the specialty we verified.
4. Interview, choose, start
You interview the matches directly and pick who to work with. Engagement terms are agreed in a written proposal — scope, rate, and our fee, all visible. Most engagements start within one to two weeks of the first introduction.
5. We stay in the loop
A match fee only pays for itself if the engagement works. We check in at the start, at the first milestone, and at the end — and if the fit is wrong, we rematch rather than defend the original introduction.
Ready when you are: start with the project brief. If you would rather understand costs first, the engagement models and typical ranges are on the pricing page.
What “vetted” means on this bench
The word is used loosely across the industry — on most platforms it means a form was filled in. Here it means three specific checks, done by people who have built and operated AI systems themselves:
Production evidence, not portfolios
Every engineer and team on the bench has shipped systems that ran in production for real users — named projects with an operating history we can interrogate, not demo links or certificate stacks.
References we call ourselves
We speak to people who operated systems alongside the candidate and ask what they owned, specifically. A polished profile survives a form; it does not survive that phone call.
A defined specialty
Nobody on the bench claims the full stack from research to frontend. We record what each person is verifiably good at — and, just as deliberately, what they are not — so matches are made on fit rather than availability.
This is the same bar we teach employers to run themselves in our hiring guide — the network simply runs it before you ever see a name. Engineers and specialized teams who clear it can apply to join the network.
Four ways to engage the network
Project-based build
A defined system, scoped and delivered — RAG pipelines, AI agents and copilots, custom integrations. Fixed scope or milestone-based. Most projects on the bench run $25k and up.
AI implementation services→Contract engineers
Senior AI engineers embedded with your team by the week or month — capacity and expertise without a six-month search or a full-time commitment.
Hiring routes compared→Fractional AI leadership
An experienced AI leader one to two days a week to set strategy, make build-vs-buy calls, and keep vendors honest — while the network supplies the build capacity.
Fractional AI leadership→Team training
Workforce AI training delivered through vetted training partners — from a leadership baseline to company-wide, role-based rollout — brokered and quality-checked the same way we match engineers.
Corporate AI training→The brief works the same way for all four — describe the problem, and the scoping call settles which shape fits. Many engagements combine two: a fractional leader plus contract engineers is the most common pairing for a first serious AI build.
Describe the project once
Two minutes for the brief, fifteen for the call, and you are interviewing people whose production work we have already verified — instead of screening two hundred applicants yourself.
Frequently asked questions
How fast can we go from brief to a working engagement?+
Typically two to three weeks end to end: briefs are reviewed within two business days, the scoping call happens that week, introductions follow within days of the call, and most engagements start within one to two weeks of the first introduction. Contract placements move fastest; scoped project builds take slightly longer because the proposal defines deliverables.
What does it cost to submit a brief or get matched?+
Nothing. The brief, the scoping call, and the introductions are free with no obligation. You pay only if you engage someone — under terms set out in a written proposal, with our fee stated transparently rather than hidden as a markup. Engagement cost ranges are published on our pricing page.
How is this different from a staffing agency or freelance marketplace?+
Marketplaces give you a huge pool and make the screening your problem; staffing agencies place from whoever is on their bench, with a 40–80% markup you rarely see. We run the opposite model: a deliberately small bench, verified production evidence and references for everyone on it, two to three matches instead of two hundred profiles, and a fee you can read in the proposal.
What kinds of projects are the right fit?+
Serious AI work with a real budget — typically $25k and up for projects, or ongoing contract and fractional engagements. RAG and retrieval systems, AI agents, LLM integrations, ML pipelines, and the strategy work around them. If your project is smaller or earlier than that, the free readiness tools and guides on the site are the honest place to start, and we will tell you so.
What does "vetted" actually mean here?+
Three checks, all done by humans: verified production systems with an operating history (not demos or certificates), references we call ourselves and interrogate about specific ownership, and a defined specialty so we match on fit. Most applicants to the network do not clear this bar — which is precisely what a match fee pays for.
Can we hire the engineer full-time later?+
Yes. Contract-to-hire is a common path: prove the fit on real work first, then convert. Conversion terms are agreed upfront in the engagement proposal, so there is no surprise fee negotiation at the moment you want to make the hire.