AI ENGINEERING · COMPUTE · GLOBAL DEPLOYMENT
Build, deploy, and distribute AI globally.
Cosmic V3 brings together AI applications, engineering, inference and compute, and software–hardware integration to help teams turn open-model capabilities into practical solutions for international markets.
From a model to a working system.
Start with the outcome you need, then connect the application, compute and delivery work around it. V3’s three solution areas provide a way to define the project without treating every technical decision as a separate engagement.
AI Applications & Engineering
Turn an idea or early prototype into a defined application. Explore AI product research, forward-deployed engineering, workflow development and system integration, with evaluation and handover built into the scope. The starting point can be a product question, an existing system or a specific operational task.
Inference & Compute
Match the serving approach to the workload. Discuss model inference, token-based access and distribution, or overseas compute capacity and orchestration. Define the model, usage pattern, target region and operating responsibilities before choosing a delivery option. Capacity procurement and inference usage are scoped separately.
Infrastructure & Hardware
Connect AI software with the systems that run it. Scope AI data-centre deployment, hardware research and prototyping, and software–hardware integration around clear interfaces, validation requirements and handover responsibilities. Where specialist partners are needed, their role belongs in the plan from the start.
Built around your next product, workload or market.
For international teams
You may be building an AI application, assessing a compute environment or developing an intelligent device. Start with your use case, existing systems and operating requirements. V3’s engagement model brings the relevant engineering and delivery work into a scope your team can review, test and take forward.
For AI companies going global
Bring product delivery, distribution and overseas compute into the same market-entry plan. For AI companies from China, the starting point is a defined target market and operating model, with commercial, technical and regulatory workstreams assigned to the appropriate teams and advisers.
Know what you are building—and what happens next.
A useful first engagement should leave you with a clearer decision and a defined next step. That might be a tested prototype, an integration plan, a compute assessment or a deployment specification. The deliverable should match the question you need answered.
Before implementation, agree the inputs, dependencies, acceptance criteria and ownership of each workstream. Distinguish what V3 will deliver from what your team or a specialist partner provides. Include documentation and operational handover in the scope, rather than leaving them until the end.
A clear path from assessment to handover.
01 — Understand
Define the use case, target market, constraints and intended outcome. Identify the decision the project needs to support.
02 — Design
Agree the architecture, deliverables, responsibilities and acceptance criteria. Make assumptions and third-party dependencies visible.
03 — Build & Validate
Develop and integrate the agreed scope. Test the result against representative tasks and document limitations alongside findings.
04 — Deploy & Support
Plan rollout, documentation and handover. Define any ongoing monitoring, maintenance or support as part of an explicit agreement.
What are you ready to build next?
Tell us about your product, workload or target market. Start a conversation about AI engineering, compute, infrastructure, hardware or global expansion—and define a practical next step for your project.