
Exclusive focus on your roadmap
The team is assigned to your organization rather than divided across multiple unrelated client projects.
Your business may need a dedicated AI team when you have an ongoing product roadmap, multiple AI initiatives, or long-term engineering requirements that cannot be supported effectively through short projects or individual hires.
Dedicated teams are useful when you need stable delivery capacity, specialist AI skills, stronger product knowledge, and an engineering group focused exclusively on your organization.
Businesses choose dedicated AI teams to access specialized engineering talent, increase delivery capacity, and maintain continuity across long-term AI and software initiatives. A dedicated team provides the stability of an internal product team while reducing the time and operational effort involved in recruiting, onboarding, and managing every role independently.

The team is assigned to your organization rather than divided across multiple unrelated client projects.

Build a team across AI, LLM, machine learning, backend, data, cloud, QA, and product disciplines without hiring each role separately.

Engineers develop an understanding of your users, systems, architecture, data, standards, and business priorities.

Maintain stable engineering availability for product development, platform improvement, integrations, and ongoing AI operations.

Adjust roles and team size as your product moves from discovery to MVP, production, scaling, and optimization.

Reduce the internal effort required for sourcing, assessment, onboarding, retention, payroll, and talent administration.
Grayphite builds dedicated teams around the technical and product capabilities required for your roadmap.
Develop machine learning systems, intelligent features, prediction workflows, model pipelines, and production AI applications.
ViewBuild LLM integrations, RAG systems, AI agents, copilots, prompt architectures, evaluation pipelines, and model-powered workflows.
ViewCreate ingestion pipelines, data transformations, retrieval systems, vector indexes, analytics foundations, and model-ready datasets.
ViewDevelop APIs, business logic, databases, integrations, authentication, queues, and scalable application services.
ViewBuild dashboards, portals, SaaS interfaces, AI experiences, administration tools, and customer-facing applications.
ViewManage cloud infrastructure, CI/CD, containers, Kubernetes, observability, deployment automation, and production reliability.
ViewTest product functionality, AI workflows, APIs, integrations, user interfaces, performance, and release quality.
ViewSupport roadmap planning, requirements, sprint coordination, stakeholder communication, risk management, and delivery visibility.
ViewDefine model, data, application, integration, cloud, security, and scalability architecture for complex AI systems.
ViewDesign intuitive user journeys, AI interactions, dashboards, review workflows, feedback mechanisms, and product interfaces.
ViewDedicated AI teams can be structured around the products, workflows, data, and technical requirements of different industries.
Dedicated AI teams help HealthTech businesses build and improve patient platforms, clinical tools, administrative systems, and intelligent healthcare products.

Dedicated AI teams help financial organizations develop secure customer platforms, compliance tools, document systems, and intelligent workflows.

Dedicated AI teams help ecommerce businesses build product discovery, customer support, catalog, order, and merchant solutions.

Dedicated AI teams help AdTech companies develop campaign platforms, audience systems, reporting products, and generative AI capabilities.

Dedicated AI teams help education businesses build learning platforms, AI assistants, student tools, and assessment products.

Dedicated AI teams help consulting firms create research tools, knowledge platforms, client products, and AI-enabled delivery systems.

We evaluate engineers across AI, software development, cloud infrastructure, data engineering, DevOps, and product delivery disciplines. Our vetting process is designed to identify the top 3% of assessed engineering talent based on technical depth, project experience, communication, product thinking, and delivery readiness.
We look for engineers with hands-on experience building AI systems, LLM applications, RAG workflows, model integrations, or AI-powered product features.
Engineers are assessed on their ability to design scalable systems, understand trade-offs, and make practical technical decisions.
We review problem-solving ability, code structure, maintainability, testing awareness, and production engineering practices.
Engineers must be able to work with product managers, technical leads, designers, stakeholders, and distributed engineering teams.
We prioritize engineers who understand business goals, user needs, and measurable outcomes — not just isolated technical tasks.
We review ownership, accountability, documentation habits, async communication skills, reliability, and ability to integrate into client processes and delivery workflows.
Plan your AI team in minutes. Tell us about your roadmap, stack, and timeline, and we will recommend the right skill mix, engagement model, and onboarding plan.
A dedicated AI team is assembled around your roadmap, technical environment, product stage, working model, and required capabilities. The team works exclusively on your initiatives and can operate with Grayphite delivery leadership, your internal management, or a shared governance structure.









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71-75 Shelton St, Covent Garden
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