There is a wealth of knowledge and information about your issue and community, but it is scattered and fragmented. Lessons are learned repeatedly, wasting scarce resources. Certain forms of knowledge (institutional) are in greater use than others (lived experience).

A customized AI solution (Retrieval Augmented Generation) offers highly accurate and contextually relevant information. This hybrid approach leverages diverse data sources, enabling you and those you provide access with a wide range of knowledge and expertise that would otherwise be inaccessible. Additionally, RAGs are adaptable and scalable, allowing for continuous optimization and alignment with ethical standards and cultural sensibilities.

Retrieval Augmented Generation (RAG) is an advanced AI technique that combines retrieval-based methods with generative models. By retrieving relevant information from a large corpus of data and integrating it with AI-generated content, RAG provides comprehensive and contextually accurate responses. This approach enhances the quality and relevance of information, making it an invaluable tool for organizations seeking to leverage AI for decision-making and knowledge management.

Access to Expertise: For-purpose organizations often lack the resources to access advanced AI capabilities and expert knowledge. RAG services bridge this gap, providing organizations with the intelligence they need to make informed decisions.

Diverse Knowledge Integration: Jerrold McGrath’s unique approach integrates multiple ways of knowing and various forms of knowledge, ensuring a comprehensive and nuanced understanding of complex issues.

Citation: Models can reference the sources of their evidence and/or arguments allowing for confirmation and verification.

Automated Information Retrieval: RAG frameworks automate the process of retrieving relevant information from vast data sources, saving you time and effort.

Accurate and Contextual Responses: By combining retrieval methods with generative models, RAG provides highly accurate and contextually relevant information, enhancing the quality of your outputs.

Tailored Solutions: Our services are customized to meet your specific needs, ensuring that the RAG framework is adaptable to various contexts and scalable as activity grows.

Continuous Improvement: Through iterative testing and refinement, the RAG framework is continuously optimized for performance and accuracy.

Ethical Alignment: We ensure that the RAG framework aligns with your values and ethical standards, addressing potential biases and ensuring responsible use of AI.

Cultural Sensitivity: Our approach centres cultural sensibilities, making the solutions relevant and effective across different contexts.

Innovative Edge: Implementing advanced AI solutions like RAG provides you with a competitive edge, positioning you as an innovative leader in your field.

Data-Driven Insights: You can leverage data-driven insights to drive strategic initiatives, improve service delivery, and achieve better outcomes.

Cost-Effective: RAG services can be a cost-effective solution for organizations looking to harness advanced AI capabilities without investing heavily in infrastructure and specialized talent.

Maximized Impact: By effectively utilizing RAG frameworks, you can maximize impact, achieving your mission and goals more efficiently.

Expertise and Experience: With a strong track record in AI and for-purpose work, I have applied RAGs in strategy, program evaluation, education, and public-facing projects.

Holistic Approach: My commitment to integrating diverse knowledge forms ensures a well-rounded and effective solution.

Client-Centric: I prioritize your values, needs, and goals, delivering tailored solutions that drive real results.

I focus on the design, development, delivery, and testing of localized and customized cutting-edge Retrieval Augmented Generation (RAG) services. My focus is to empower for-purpose organizations with intelligence and expertise that are typically beyond their reach. By consolidating diverse lessons and knowledge within a RAG framework, I enable you to make informed decisions and achieve your mission more effectively.

I combine a tested and proprietary approach to developing RAGs with a commitment to integrating multiple ways of knowing and different forms of knowledge within your RAG framework(s). I understand that valuable insights can come from a variety of sources, and I ensure coherence within the overall model while incorporating this diverse data. This holistic approach allows for solutions that are both comprehensive and contextually rich and that can support values and goals outside the market economy.