We don’t sell generic MX packages. We partner with you to implement what works for your specific context.
Every organization has different needs, constraints, and opportunities. Our approach adapts to your situation.
The Four Phases
Phase 1: Understand
We start by deeply understanding your current state:
- How do agents currently interact with your site?
- Where are they succeeding? Failing?
- What’s your competitive landscape?
- What are your business priorities?
- What constraints exist (technical, organizational, timeline)?
Deliverable: MX Readiness Assessment with prioritized recommendations.
Phase 2: Plan
We collaboratively design your path forward:
- Define measurable success criteria
- Sequence implementation by impact and dependencies
- Identify resource requirements
- Plan for knowledge transfer
- Establish testing and validation approach
Deliverable: Strategic MX Roadmap with clear milestones.
Phase 3: Implement
We work hands-on with your team:
- Add Schema.org markup to priority pages
- Fix accessibility issues blocking agents
- Make implicit states explicit
- Validate with agents and tools
- Document patterns for replication
Deliverable: MX-compliant code ready for production.
Phase 4: Enable
We ensure you can maintain and expand:
- Train your team on MX principles
- Create checklists and decision frameworks
- Document patterns specific to your stack
- Establish ongoing testing procedures
- Provide post-launch support
Deliverable: Self-sufficient team that understands MX.
What Makes Us Different
1. We Practice What We Preach
This website exemplifies Machine Experience. Browse it with an AI agent—everything is structured, accessible, and explicit.
2. We Prioritize Impact
You don’t need to fix everything. We help you identify the 20% of changes that deliver 80% of value.
3. We Transfer Knowledge
We don’t create dependency. We make your team self-sufficient through training, documentation, and frameworks.
4. We Measure Results
We define success metrics upfront and track them throughout. Agent traffic, SEO impact, accessibility scores—we show the ROI.
5. We Stay Current
AI agent capabilities evolve rapidly. We track developments and ensure our recommendations reflect latest best practices.
Engagement Principles
No Generic Solutions - Every recommendation is specific to your context
Impact Over Perfection - Quick wins first, comprehensive implementation second
Knowledge Transfer - Your team should understand MX as well as we do
Measurable Outcomes - We track and report on defined success metrics
Honest Assessment - Sometimes the answer is “not yet” or “focus elsewhere first”