Strategy
Our mission is to bridge the gap between data science and business. We want to help companies develop machine learning as a new core competency that positively impacts overall performance and employee well-being. Our strategy consulting services are designed to meet a company exactly where it is in the enterprise AI adoption process, from the earliest stages of opportunity assessment all the way through creation and implementation of a strategic plan.
Discover
Design
Develop
Deploy
Machine Learning
Identify potential ML applications with high ROI
Assess ML project feasibility & prioritize into roadmap
Develop ML models
Deploy ML models
Platform & Pipelines
Map, catalog and assess data quality
Create end state architecture staged implementation plan
Build our platform and pipelines in sync w/roadmap
Implement feedback loops and model refresh cycles
Upskilling & Retraining
Execs: expectations and their role in change management
Managers: resource req's, risk management, data privacy
Project Managers: team structure, model dev process
End users: dispel fear, how to work with AI tools
Talent Aquisition
Assess current state of data science resources
Create data science staffing roadmap
Recruit key DS positions in sync w/roadmap
Develop internal DS talent via data wrangling tasks
EAI Adoption Plan
Successful Enterprise AI adoption requires careful, coordinated planning across four distinct workstreams. As with any business transformation, C-suite commitment, clear articulation of goals and metrics, and cross-functional project and team development are critical to the process.
Machine Learning
Platform & Pipelines
Upskilling & Retraining
Talent Aquisition
Machine Learning
Identifying potential high-ROI ML applications and assessing and prioritizing projects is a critical first step in creating a machine learning roadmap. Once the roadmap is established, the models that support it need to be built, tested and deployed.
Platform & Pipeline
Every ML roadmap needs end-state architecture and a staged implementation plan. This is where platform and pipeline development come into play, along with implementation of production data flows that support the plan.
Upskilling & Retraining
Executives, managers, project managers and end users alike need training and assurance of their importance in an evolved organization. Developing a coordinated plan to explain, introduce and support corporate and cultural change is critical to successful EAI adoption.
Talent Acquisition
No EAI adoption plan is feasible without the right data science talent in place. Organizations undertaking an EAI transformation must create a data science staffing roadmap, hire data science talent, and help these individuals learn how to bring their technical expertise to the business of advancing strategic and tactical goals.