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.
 

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