Devlyn is a bench of 150+ pre-vetted AI engineers deployed into your team on demand, specializing in eight production AI disciplines from LLM engineering to MLOps, backed by a decade of delivery through ViitorCloud.
What is Devlyn?
Devlyn is a team-as-a-service platform that matches vetted engineers — forward‑deployed, LLM, context, agentic workflow, AI application, MLOps, AI infrastructure, and AI security — to specific gaps in your production AI system. It takes your repository, backlog, and evaluation criteria as input and returns a dedicated engineer (or a senior‑led pod) working within your standup and shipping measurable outcomes. The platform is built and operated by ViitorCloud, which has served 1,563+ organizations including KPMG, ADNOC, DP World, and Adani.
Key Features
- Eight role‑specific disciplines — Engineers are pre‑binned into the exact roles a production AI system needs: Forward‑Deployed Engineer, LLM Engineer, Context Engineer, Agentic Workflow Engineer, AI Application Engineer, MLOps Engineer, AI Infrastructure Engineer, and AI Security Engineer. Each role page lists published rates by seniority level.
- Free one‑week trial — Before any commitment, the engineer works your real backlog in your real repo. If you’re not convinced, you pay nothing and keep all work produced.
- 48‑hour replacement guarantee — If the fit is wrong, a replacement inherits full context through a documented handover within two business days, with no re‑sourcing fee.
- Senior review on every line — Every piece of code that ships is reviewed by a Devlyn senior engineer, regardless of the engineer’s level.
- Cost per task as a first‑class metric — Engineers track outcomes, not hours. Billing is either monthly dedicated or hourly Time & Material, and both rates are transparent per role page.
- NDA and IP assignment before onboarding — All produced work belongs to the client, including trial output. Access is scoped per engagement.
- Global timezone alignment — Engagements are planned with overlap for US, UK, European, and Australian working hours, with standups, reviews, and incident response inside those windows.
Who is it for?
- CTOs whose AI roadmap is stalled — They bring a system that “keeps you up at night” and get a shortlist of engineers within 24 hours who can own the path from notebook to production.
- Engineering leads needing a specific discipline — For example, a team that already has strong ML researchers but lacks an MLOps engineer to turn models into reliable infrastructure, or an AI Security engineer to handle prompt injection boundaries.
- Startups building from scratch — A senior pod of 2–4 engineers with a lead can own an entire AI workstream from zero, with documented handover when the team is ready to take over in‑house.
What can you do with Devlyn?
- Rescue a stalled AI initiative — The Forward‑Deployed Engineer “ships from inside your business and owns the last mile where AI projects usually die,” bridging the demo‑production gap.
- Add guardrailed agents — The Agentic Workflow Engineer builds agents that finish jobs with audit trails and approvals, not just prototypes that work on three happy paths.
- Ship an AI‑native product — The AI Application Engineer does full‑stack product engineering that makes the AI feel instant and trustworthy, paired with the Context Engineer who owns knowledge pipelines and memory.
