Own your category.
Create new value with AI.
Get the product team aligned.
We align your AI and product strategy to the new category and capture new market value.
Set your company vision.
Identify a unique problem that only your company can solve.
Category Strategy
Identify the problem.
Explain ramifications of not solving the problem.
Declare your unique solution to the problem.
Describe the solution, vision for the future.
Explain ramifications of not solving the problem.
Declare your unique solution to the problem.
Describe the solution, vision for the future.
Define the "container" for the problem
Represent the market type, nature of the problem, and audience who has the problem.
Pick a unique name that other companies may want to use as they enter your market — having others come into your category helps you establish the category and your leadership position.
Represent the market type, nature of the problem, and audience who has the problem.
Pick a unique name that other companies may want to use as they enter your market — having others come into your category helps you establish the category and your leadership position.
Create a blueprint visual which illustrates the key components of the category — this will help when telling the category story and inform the category visual identity.
Visualize the key category components that can easily map to your product roadmap — this is how you align the category problem to your solution.
Launch your new category.
Visualize the key category components that can easily map to your product roadmap — this is how you align the category problem to your solution.
Launch your new category.
Capture new value with AI.
We engage executive decision makers and product team leaders to arrive at your AI strategy — without the hype.
AI Strategy
Understand the business problem to be solved with AI.
Define the business value for AI.
Review where generative AI and traditional AI could apply.
Review team, compute, licensing and model training resources.
Define the business value for AI.
Review where generative AI and traditional AI could apply.
Review team, compute, licensing and model training resources.
Lead workshops to explore highest value generative AI and traditional AI use cases.
Evaluate the availability and quality of data relevant to your use cases, and whether data is available internally or externally.
Pick the top projects to AI-enhance your current solution, or brainstorm new AI-first product concepts.
Scope AI Market Requirements Doc (AI MRD) with KPIs.
Evaluate the availability and quality of data relevant to your use cases, and whether data is available internally or externally.
Pick the top projects to AI-enhance your current solution, or brainstorm new AI-first product concepts.
Scope AI Market Requirements Doc (AI MRD) with KPIs.
Review the latest best practices and platforms available for our chosen use cases.
Determine generative AI and traditional AI/ML tools and technology approaches to help select prototype.
Review computational resource requirements, expertise in AI/ML, and access to software frameworks.
Define KPIs to measure success of prototype, including content quality, efficiency gains and cost savings.
Scope AI Product Requirements Doc (AI PRD) for prototype which defines implementation roadmap.
Determine generative AI and traditional AI/ML tools and technology approaches to help select prototype.
Review computational resource requirements, expertise in AI/ML, and access to software frameworks.
Define KPIs to measure success of prototype, including content quality, efficiency gains and cost savings.
Scope AI Product Requirements Doc (AI PRD) for prototype which defines implementation roadmap.
Build user-ready prototypes.
Hand-off prototype for development into customer-ready solution, or iterate the approach based on results.
Validate potential and KPIs.
Continuously monitor the performance and gather feedback for improvement.
Hand-off prototype for development into customer-ready solution, or iterate the approach based on results.
Validate potential and KPIs.
Continuously monitor the performance and gather feedback for improvement.
Scope AI responsibility and risk management requirements, including contingency planning to mitigate risks.
Determine your data governance strategy.
Build plan to ensure AI safety, accuracy, explainability and privacy.
Determine your data governance strategy.
Build plan to ensure AI safety, accuracy, explainability and privacy.
Align your product roadmap.
Update your product plans and positioning — to complement your new category and AI strategy.
Product Strategy
Understand the customer requirements.
Review the specifications.
Understand the key product metrics and KPIs.
Review the specifications.
Understand the key product metrics and KPIs.
Refine the competitive landscape with new category.
Review competitive features and positioning.
Update SWOT and competitive analysis.
Review competitive features and positioning.
Update SWOT and competitive analysis.
Update product positioning framework, mapped to new category.
Determine new value proposition highlighting differentiation.
Create new marketing messaging framework via key personas.
Determine new value proposition highlighting differentiation.
Create new marketing messaging framework via key personas.
Align product goals to category vision.
Scope multi-year category-product roadmap plan.
Determine key milestones and outcomes.
Scope multi-year category-product roadmap plan.
Determine key milestones and outcomes.
