01
AI Platform Onboarding
Team onboarding for ChatGPT, OpenAI, Codex, Claude, Claude Code, and related AI platforms.
ChatGPTClaudeCodex
Deployment LabsAI Deployment Engineers
Deploy AI into the way your team actually works.
Deployment Labs helps companies onboard teams to OpenAI, Codex, Claude, and other frontier AI platforms — then turns that access into practical workflows, skills, plugins, and internal operating systems.
From AI access to AI capability
Deployment partners across
OpenAI
ChatGPT Enterprise
Claude
Claude Code
Codex
Cursor
Anthropic API
Vercel AI SDK
OpenAI
ChatGPT Enterprise
Claude
Claude Code
Codex
Cursor
Anthropic API
Vercel AI SDK
The gap
Your team has AI access. That does not mean your team has AI capability.
Most companies are stuck between experimentation and deployment. A few employees move faster. Others are unsure where to start. Leadership sees the potential, but the organization lacks shared workflows, standards, and practical deployment support.
01↗
Scattered usage
Everyone uses AI differently, with inconsistent quality and unclear standards.
02↗
Low adoption
The tools are available, but most team members do not know where AI fits into their work.
03↗
No internal system
Prompts, workflows, and lessons stay trapped in individual chats instead of becoming reusable company assets.
04↗
Technical bottlenecks
Teams want Codex, Claude Code, plugins, automations, or custom skills, but need help implementing them safely.
Services
We design, build, and deploy AI workflows for your team.
We audit existing workflows, identify high-leverage use cases, train your team, and build the internal systems that make AI useful across the organization.
02
Workflow Mapping
Identify where AI can create leverage across operations, marketing, sales, support, engineering, and leadership.
AuditMapPrioritize
03
Skills & Plugins
Reusable skills, custom instructions, plugin-like workflows, internal GPTs, Claude projects, and AI-assisted tools.
SkillsGPTsProjects
04
Team Training
Live and async enablement for employees, managers, and technical teams. Role-specific examples and hands-on labs.
LiveAsyncLabs
05
AI Operating System
Documentation, governance, prompt libraries, SOPs, evaluation standards, and usage guidelines for the whole company.
GovernanceSOPsEvals
06
Deployment Engineering
Hands-on implementation of AI workflows, automations, API integrations, and internal tooling.
APIsToolingAutomations
Process
A deployment process built for adoption.
Each step produces a concrete artifact your team can use, maintain, and extend. By the end, AI is not a tool a few people use — it is how the team works.
- Step 01↗
Audit
We map your team, workflows, tools, risks, and AI-readiness.
- Step 02↗
Design
We identify high-leverage use cases and design practical deployment paths.
- Step 03↗
Build
We create workflows, skills, plugins, docs, and internal systems.
- Step 04↗
Train
We onboard your team with role-specific examples and hands-on implementation.
- Step 05↗
Deploy
We embed AI into daily work, measure adoption, and refine the system.
- Step 06↗
Scale
We help your internal champions improve, extend, and maintain the AI operating system.
Use Cases
Deploy AI across the work that already exists.
Every team has work that AI can support. We help you find it, build for it, and roll it out without disrupting how things actually get done.
Codex onboarding
Claude Code adoption
Code review assistance
Documentation generation
Internal dev workflows
AI-assisted debugging
Repo-specific coding agents
Deliverables
You leave with systems, not just suggestions.
Every engagement produces durable artifacts your team can use, edit, and extend long after we're done.
01AI adoption roadmap
02Team workflow map
03Platform onboarding plan
04Role-specific training
05Prompt libraries
06Custom GPTs / Claude Projects
07Codex & Claude Code workflows
08AI usage policy
09Internal AI playbook
10Skills & plugin specs
11Automation diagrams
12Evaluation checklists
13Documentation templates
14Implementation backlog
15Adoption metrics dashboard
Engagement Models
Flexible support for every stage of AI adoption.
Whether you're piloting AI in a single team or deploying it across the entire company, there is a path here that fits.
2–4 weeks
AI Deployment Sprint
A focused engagement to identify, build, and deploy high-leverage AI workflows for a specific team.
Teams starting from scratch
One department
Pilot programs
Quick implementation
Most popular
Monthly
AI Enablement Retainer
Ongoing monthly support for teams deploying AI across multiple departments.
Growing companies
Agencies
Multi-team orgs
Continuous workflow dev
3–5 weeks
Codex / Claude Onboarding
Training and implementation engagement for technical teams adopting AI coding tools.
Engineering teams
Product teams
Internal dev teams
Technical agencies
Quarterly
Internal AI Operating System
A deeper engagement focused on company-wide AI standards, workflows, playbooks, governance, and internal capability.
Leadership teams
Mid-market companies
Teams scaling AI
Standardizing usage
Ready when you are
Ready to move from AI experiments to deployed workflows?
Talk with a Deployment Labs engineer about your team, tools, and highest-leverage opportunities. No slide decks. No theory. Just deployment.