Insights
Rapidly assess, plan, and build your AI strategy
Insights streamlines AI strategy development by identifying high-impact use cases, assessing AI maturity, and providing data-driven recommendations for deployment. With Insights, you can ensure your model is transparent, adaptable, diverse, interconnected, equitable, fair, and measurable across the entire AI lifecycle.
Why Insights?
With its comprehensive AI Data Readiness (AIDR) questionnaire, Insights provides a structured AI maturity assessment framework, enabling organizations to evaluate their current capabilities and identify growth opportunities
With built-in transparency, fairness evaluation, and equity assessments, Insights helps organizations minimize AI-related risks, ensuring AI models are auditable, compliant, and free from bias
Insights offers customization of assessments, programmatic execution, and executive-level, standardized reports. It also seamlessly integrates with existing AI development environments and governance tools
Key capabilities
AI maturity assessments
Automated engagement scoping
Business case development
AI maturity stages
Gain a deeper understanding of your organization’s AI maturity level using Insights’ advanced analysis. Insights provides a structured, clear view of your current AI capabilities and roadmap for growth across five distinct stages: Aware, Approaching, Defined, Managed, and Optimizing.
Aware
The enterprise is in the early, exploratory stage of ML projects. There is a basic understanding of AI capabilities and potential within the organization. Identifying ML’s potential for business needs (e.g., customer service, efficiency) will be critical for maturation, in addition to researching ML techniques for problem fit and applicable use cases.
Approaching
Organizations at this stage are beginning the implementation phase. Additional problem clarification is needed, in addition to gathering and preparing data for ingestion. Prototyping ML models to assess feasibility is of key importance to identify the best approach.
Defined
The enterprise has successfully defined the ML project and has created a detailed implementation plan. Organizations at this stage have secured necessary resources required for project success, in addition to finalizing collected data for model training. They are implementing pilot projects for testing, gaining hands-on experience, and starting to document AI practices.
Managed
In this stage, the organization has completed testing and is operational with a defined AI strategy. They are building new business models and tools that leverage AI capabilities to improve efficiency and create new opportunities. Progress is being monitored, and the strategy is being adjusted as needed.
Optimizing
Enterprises in this phase have scaled their implementation of more complex AI projects and tools. They continue to iteratively enhance their ML models by tuning parameters, incorporating new data, and employing ensemble techniques for better performance. In this advanced stage, they continue to integrate AI across their operations, actively refining models, and maximizing the potential of AI to drive significant business benefits and gain a competitive advantage. Our AIDR questionnaire can help measure an AIDR score to facilitate a go / no-go decision to move forward with the AI build.
Maximize your AI return on investment and minimize AI-related risks
With Insights, you can ensure your model is transparent, adaptable, diverse, interconnected, equitable, fair, and measurable across the entire AI lifecycle.
Transparency
Transparency is a key principle in developing ethical and trustworthy AI systems. When users understand how an AI model works, they’re more likely to trust its outputs and accept its decisions. Insights’ reporting ensures that AI decisions can not only be readily explained but that the systems’ algorithms, data, and design processes can be evaluated and audited.
Adaptability
An AI assessment tool needs to grow in tandem with the AI landscape, incorporating existing technologies within a consistent ecosystem and enabling integration of new approaches and libraries. With Insights, enterprises can ensure their AI systems learn, adapt, and improve as changes are encountered, both in data and the environment.
Perspective
Insights provides a continuously curated selection of methods to assess datasets and models, focusing on which assessments are currently the most useful or sought out. For users with limited background in how to implement responsible AI, Insights populates an intuitive taxonomy of assessments to ensure running a full suite of assessments is effortless.
Connectivity
It’s critical that an assessment tool seamlessly integrates both with the AI development environment, as well as other governance tools. That’s why we’ve built Insights to include customization of assessments, programmatic execution, and generation of executive-level, standardized reports.
Equity assessment
An effective AI governance strategy must include an equity assessment. With Insights, your team can evaluate the equality of outcomes across sensitive features, ensuring equal treatment across diverse demographic populations.
Fairness evaluation
Insights analyzes your AI system to identify and quantify potential biases or discriminatory outcomes to ensure equitable treatment and recommendations for diverse user groups. Using Insights, you can assess how sensitive features relate to other dataset features and examine model performance variations based on these features.
Performance metrics
As the need for responsible and transparent AI grows, a robust model evaluation has become a critical component of AI governance. With Insights, you’ll receive standardized, auditable assessments of model performance and risks—using user-specific metrics—all in a single, executive-level dashboard.
Uncover gaps in your AI strategy across five categories with our comprehensive AI readiness survey
Business
Insights will guide you in assessing business readiness to ensure you have the right technology, high-quality data, skilled workers, and an organizational mindset conducive to success
Data
Our data readiness questionnaire evaluates your data landscape for data availability, data volume and diversity, data quality and integrity, data governance, and data ethics and responsibility
Machine Learning
Unlock AI’s full potential with our readiness index to evaluate your team’s current capabilities in applying machine learning
Deployment
Using our readiness survey, your team can ensure you’re prepared for deployment and keeping factors like LLM monitoring, version control, and resource allocation top of mind
People
Different stages of AI maturity require different resources. Insights will help you identify your current stage to allocate resources more effectively, whether that’s training current resources or hiring talent
Get your AI strategy right from day one
Maximize your AI return on investment and minimize AI-related risks with Insights’ advanced analysis capabilities.
