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Services

Practical AI strategy, workflow automation, data, and product-planning support.

Engagements begin with the business problem, current workflow, available data, organizational constraints, and desired outcome—not with a preferred tool.

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Services can begin with assessment and planning or progress into structured implementation support.

Some organizations need help deciding where AI or automation may create value. Others already understand the problem but need requirements, workflows, architecture, prototyping, testing, documentation, or adoption support.

The scope is adjusted to the organization’s readiness, budget, risk, internal capacity, and the complexity of the problem being addressed.

Service catalog

Structured support for assessment, design, planning, and adoption.

Each service is adapted to the organization’s current situation rather than delivered as a fixed technology package.

01

AI Strategy and Readiness Assessment

Identify where AI may create practical value, what must be improved first, and which opportunities deserve priority.

Discuss an AI readiness assessment

Best suited for

  • Organizations under pressure to adopt AI
  • Leadership teams with too many competing ideas
  • Teams uncertain about data readiness
  • Organizations concerned about governance and adoption

Common problems

  • No clear business case
  • Tool selection before problem definition
  • Unclear ownership
  • Weak data quality
  • Uncertain risk and governance

Possible deliverables

  • Readiness summary
  • Opportunity inventory
  • Prioritization matrix
  • Risk observations
  • Recommended implementation roadmap

Client contribution

  • Access to relevant stakeholders
  • Current process information
  • Known constraints
  • Existing systems and data context
02

Workflow Automation Planning

Document the current process, identify repetitive work and delays, and design a realistic future-state workflow.

Review an automation opportunity

Best suited for

  • Teams relying heavily on manual processes
  • Organizations with fragmented handoffs
  • Service businesses managing repetitive administrative work
  • Teams planning automation but lacking documentation

Common problems

  • Manual data entry
  • Repeated emails
  • Slow approvals
  • Inconsistent handoffs
  • Weak process ownership

Possible deliverables

  • Current-state workflow
  • Pain-point analysis
  • Automation opportunity map
  • Future-state workflow
  • Implementation priorities

Client contribution

  • Process participants
  • Examples of current work
  • Existing forms and tools
  • Known exceptions and bottlenecks
03

AI-Powered Customer Intake

Plan connected workflows for inquiries, leads, bookings, messages, notifications, and customer follow-up.

Discuss customer intake

Best suited for

  • Service businesses
  • Organizations receiving frequent inquiries
  • Teams managing leads manually
  • Businesses with inconsistent booking and follow-up

Common problems

  • Missed inquiries
  • Slow responses
  • Manual lead routing
  • Disconnected booking systems
  • Limited visibility into follow-up

Possible deliverables

  • Intake assessment
  • Lead-routing workflow
  • Booking requirements
  • Messaging and notification plan
  • Prototype or implementation roadmap

Client contribution

  • Current intake process
  • Service and booking rules
  • Examples of customer inquiries
  • Existing communication channels
04

Data Analytics and Business Intelligence

Improve the structure, quality, reporting, and usefulness of operational data for better decision-making.

Discuss reporting needs

Best suited for

  • Organizations using multiple spreadsheets
  • Teams with inconsistent reports
  • Leaders lacking reliable operational visibility
  • Organizations planning dashboards or data modernization

Common problems

  • Conflicting metrics
  • Poor data quality
  • Disconnected reporting
  • Unclear KPI definitions
  • Manual report preparation

Possible deliverables

  • Data assessment
  • KPI definitions
  • Reporting requirements
  • Data-model recommendations
  • Dashboard plan

Client contribution

  • Existing reports
  • Sample data
  • Business definitions
  • Stakeholder reporting needs
05

Generative AI Workflow Design

Replace inconsistent prompting with reusable templates, documented inputs, review criteria, and human oversight.

Improve your AI workflow

Best suited for

  • Teams already experimenting with generative AI
  • Organizations producing repeated content
  • Teams needing consistent AI outputs
  • Organizations concerned about review and responsible use

Common problems

  • Unreliable outputs
  • Ad hoc prompting
  • No reusable standards
  • Missing human review
  • Unclear ownership

Possible deliverables

  • Prompt templates
  • Input standards
  • Workflow design
  • Human-review checkpoints
  • Usage documentation

Client contribution

  • Representative tasks
  • Desired output examples
  • Review responsibilities
  • Known privacy or policy constraints
06

AI and SaaS Product Planning

Turn an early idea into a structured product plan that developers and AI assistants can implement responsibly.

Plan your product

Best suited for

  • Founders with an early software idea
  • Organizations planning internal platforms
  • Teams struggling with feature overload
  • Projects lacking requirements and acceptance criteria

Common problems

  • Unclear target users
  • Undefined MVP
  • Missing requirements
  • Uncertain architecture
  • No implementation roadmap

Possible deliverables

  • Product charter
  • Personas and user needs
  • MVP scope
  • Functional requirements
  • Roadmap and acceptance criteria

Client contribution

  • Product vision
  • Known users
  • Business constraints
  • Existing research or documentation
07

Training and Adoption Support

Help teams understand practical AI use, responsible workflows, review expectations, and implementation ownership.

Discuss team training

Best suited for

  • Nontechnical teams
  • Organizations introducing AI tools
  • Leadership teams developing usage standards
  • Teams needing practical workflow demonstrations

Common problems

  • Low confidence
  • Inconsistent usage
  • Unclear responsibilities
  • Resistance to adoption
  • Weak governance awareness

Possible deliverables

  • Training sessions
  • Practical demonstrations
  • Prompting guidance
  • Responsible-use guidelines
  • Adoption recommendations

Client contribution

  • Audience roles
  • Priority use cases
  • Current tools
  • Internal policies and concerns

Engagement fit

The strongest engagements begin with a real operational need.

Strong engagement signals

  • A business problem or workflow needs clarification
  • Leadership wants a realistic AI or automation plan
  • A product idea needs structure before development
  • Data or reporting problems are affecting decisions
  • A team needs reusable AI workflows and review standards
  • Stakeholders are prepared to participate in discovery

Situations requiring another approach

  • The only objective is to adopt a fashionable tool
  • The project requires guaranteed financial results
  • No stakeholder can explain the current process
  • The engagement requires specialist legal advice
  • The engagement requires specialist cybersecurity certification
  • The organization expects fully autonomous operation without oversight

How engagements work

A phased process keeps scope, decisions, and outputs visible.

Not every engagement requires every phase. The sequence is adjusted to the problem, risk, budget, readiness, and desired level of implementation support.

  1. 01

    Discovery

  2. 02

    Current-state assessment

  3. 03

    Opportunity prioritization

  4. 04

    Solution design

  5. 05

    Prototype or implementation

  6. 06

    Testing and refinement

  7. 07

    Deployment, documentation, and adoption

Next step

Begin with a focused conversation about the problem.

You do not need to arrive with a complete solution or a preferred AI tool.

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