TeamingSpace AI Platform
Advantage
Outcomes at a Glance
>50 %
TIME SAVED IN DELIVERY OF STAKEHOLDER UNDERSTOOD MODELS
100%
ELIMINATION OF EXPLANATION DATA BURDEN AND RELATED RISKS
> 80%
TIME SAVED IN DELIVERY OF ADVICE AUGMENTED MODELS
> 70%
TIME SAVED IN DELIVERY OF MULTI MODEL AND RESPONSIVE AGENTIC AI
TeamingSpace AI
Innovation from Ground Up
STAKEHOLDERS CONSUME DECISION STEPS WITH NO TRANSLATIONS
Decision Steps eliminate SHAP/LIME related tasks and subsequent complex translation of statistical measures for stakeholder understanding, resulting in significant time and cost savings.
Self explanatory Decision Steps using features and evaluations for decisions are stakeholder friendly.
Decision Steps set the standard for transparent algorithmic decisioning.
All TeamingSpace ML algorithms generate models using the Decision Steps standard irrespective of data domains.
ELIMINATED EXPLANATION DATA MINIMIZES DATA SECURITY RISKS
Persisted explanation data must be safeguarded like any other enterprise data.
Eliminating explanation data reduces enterprise data security burden and exposure risks.
Eliminating explanation data that are often much larger in size than model inputs saves ongoing data management costs.
INTERCHANGEABLE ADVICE AND ALGORITHMIC DECISION STEPS ENABLE ROBUST AGENTIC AI
TeamingSpace AI Platform design enables Decision Steps and Advice to be interchangeable, eliminating the need for external wrapper applications to integrate them, reducing delivery and upgrade costs significantly.
Advice, as an enterprise asset, can be proactively incorporated into future model builds eliminating expensive software upgrades.
TeamingSpace generated Decision Steps and Advice eliminate loss of enterprise memory stemming from replaced traditional ML models when they are upgraded.
SURGICAL DECISION STEPS ENABLE EFFECTIVE ML-OPS TO AI-OPS MIGRATION
Decision Steps are deployable as granular software units, eliminating risky unintended consequences that can be introduced by monolithic model deployments, resulting in effective AIOps.
Decision Steps and Advice incrementally strengthen Agentic AI and sustain enterprise knowledge across Data Science and AI projects for sustained reduction in costs and time to deliver value effectively realizing the goals of AIOps.
SEAMLESS AND ON DEMAND ADVISABILITY IMPROVES AI TRUST
Decision Steps, at the core of TeamingSpace AI, enable Human and Algorithmic Decisioning to be interchangeable creating well established and rehearsed hand-off opportunities to improve Trust in AI.
TeamingSpace Agentic AI enables on demand control transfers between humans and algorithms so that enterprises define and evolve guard rails to sustain Trust in AI.
TeamingSpace Decision Path Analytics, similar to clickstream analytics, surfaces issues to be addressed refining Trustworthiness of AI.
ROBUST AI FRAMEWORKS MAKE OUR TEAMINGSPACE AI PLATFORM YOURS
TeamingSpace AI Platform innovation supports Human Machine Teaming processes to be customized through formal frameworks.
Edico Research, Inc., through its collaboration with researchers such as Johns Hopkins University Applied Physics Lab and other industry leaders bring proven research outcomes through AI Frameworks, organizational roles and responsibilities and AI Competency Centers.
TeamingSpace AI Platform when augmented with AI Competency Centers make TeamingSpace AI as your space to deliver AI responsibly.
