Comparison
Devlyn vs Turing: precise AI role staffing or broad remote talent network?
Turing is built for scale: a large remote engineering network spanning many categories, often pitched with automated vetting. Devlyn runs the opposite operating model: eight AI roles, a role-diagnosis call, and proof by real work in your repo rather than by a vetting score.
Choose by operating model.
Choose Devlyn when the problem is one precise production AI role and you want public monthly pricing with trial proof in your own workflow. Choose Turing when your priority is scaling remote engineering hiring across many categories from a large network, and centralized vetting at volume matters more than a single role-specific trial.
How the two models actually differ
Same goal, different operating models.
A fair, model-based comparison. Descriptions of Turing reflect how that hiring model generally works; confirm current terms with the provider.
| Dimension | Devlyn | Turing (remote network model) |
|---|---|---|
| Pricing model | Public monthly ladder: $2,500 / $3,500 / $4,500 per role level. | Rates typically depend on role, seniority, and region and are usually scoped per engagement rather than published as a fixed ladder. |
| How talent is matched | Role-diagnosis call narrows the work to one of eight AI roles before 2-3 profiles are shown. | Candidates are sourced from a large remote network, often using platform vetting and matching to fill many engineering categories. |
| Specialization | Narrow: production AI engineering and data science only. | Broad remote software engineering across many stacks and seniority levels. |
| Trial / proof of fit | Two-week paid trial in your repo with inspectable artifacts as the proof. | Often relies on platform vetting and assessment signals up front; confirm what real-environment trial is offered. |
| Contract / lock-in | Month-to-month after trial, free replacement, no conversion fee. | Engagement terms vary by contract; confirm replacement and ramp policies before signing. |
| Who it is best for | Teams whose bottleneck is one ownable AI production role. | Teams scaling remote engineering headcount across many categories. |
When Turing is the better choice
- You are scaling remote engineering headcount across many roles and stacks at once.
- Your hiring need spans general software engineering rather than a single AI specialization.
- You want a large network and centralized vetting to fill volume quickly.
- You are building an enterprise remote-hiring pipeline rather than placing one focused role.
When Devlyn is the better choice
- The bottleneck is a named AI role and you want that role diagnosed before candidates appear.
- You trust proof from real work in your repo more than an up-front vetting claim.
- You want a public monthly price rather than a per-engagement quote.
- You want one dedicated engineer with deepening context, not interchangeable network capacity.
Buyer checklist
Questions to ask before buying from a remote network
- How exactly is this engineer vetted for production AI work, beyond a general assessment score?
- Can we run a paid trial in our own codebase before committing, and on what terms?
- Is the engineer dedicated to us, or shared across the network during ramp?
- What is the monthly cost for this seniority, and does it change with timezone or region?
- What is the replacement process and timeline if the match underperforms?
Cost, risk, and process
Where the two models diverge in practice.
On cost transparency, Devlyn lists a fixed monthly ladder, while a large network usually scopes rate per engagement. On risk ownership, Devlyn shifts proof to a paid trial in your real repo rather than relying on an up-front vetting signal, so quality is judged on shipped work. On process speed, a big network can fill many seats fast across categories, whereas Devlyn optimizes for one well-scoped AI role: a diagnosis call, then a 48-hour shortlist of 2-3 profiles already matched to that role.
FAQ
Comparison questions.
How is Devlyn different from Turing?
Turing is a large remote engineering network built for scale across many categories. Devlyn is a narrow AI staffing product: eight roles, public monthly pricing, and proof through a trial in your repo.
Does Devlyn use AI vetting like Turing?
Devlyn does not lead with a vetting score. It diagnoses the role, shortlists 2-3 profiles, and then proves fit through real work in your codebase during a two-week paid trial.
Can Devlyn scale a whole remote team?
Devlyn adds adjacent AI roles one at a time as needs grow. If you need broad, high-volume remote engineering hiring, a large network is the better tool.
Is Devlyn pricing higher or lower than a network rate?
Devlyn publishes its rate: $2,500, $3,500, or $4,500 per month by seniority. Network rates vary by region and engagement, so compare on the specific role and seniority you need.
Next step
Scope the AI role in 30 minutes.
Bring the bottleneck. We will map it to one of eight AI roles, send a vetted shortlist in 48 hours, and prove fit with a two-week paid trial in your codebase.