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Blueprints for Value Engineering in Agentic Automation: Turning AI Potential into Enterprise Value

Discover how Value Engineering in Agentic Automation helps enterprises overcome the Agent AI Paradox by shifting from building AI agents to engineering measurable business outcomes.

Oct 29, 2025

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Nov 11, 2024
FIT-RAG
FIT-RAG: Are RAG Architectures Settling On A Standardised Approach? As RAG is being used, vulnerabilities are emerging & solutions to these problems are starting to look very much alike.
Cobus Greyling
Cobus Greyling
Nov 3, 2024
Challenges In Adopting Retrieval-Augmented Generation Solutions
Challenges In Adopting Retrieval-Augmented Generation Solutions I have thoroughly examined academic papers on RAG (Retrieval-Augmented Generation) and have identified several common challenges raised in studies associated with implementing retrieval-augmented solutions.
Cobus Greyling
Cobus Greyling
Nov 1, 2024
Adaptive-RAG
It is evident that there needs to be a balance between query time, quality in terms of performance, but also efficiency.
Cobus Greyling
Cobus Greyling
Oct 30, 2024
Retrieval Augmented Fine-Tuning (RAFT)
Retrieval Augmented Fine-Tuning (RAFT) Adapting Language Model to Domain Specific RAG
Cobus Greyling
Cobus Greyling
Oct 30, 2024
Large Language Models Excel At In-Context Learning (ICL)
Large Language Models Excel At In-Context Learning (ICL) Recent studies have shown that, when supplied with a contextual reference at Inference, LLMs opt to make use of the contextual data as opposed to model training data.
Cobus Greyling
Cobus Greyling
Oct 27, 2024
DRAGIN: Dynamic RAG Based On Real-Time Information Needs Of LLMs
DRAGIN: Dynamic RAG Based On Real-Time Information Needs Of LLMs A Recent study introduced a new approach to RAG but more importantly the study highlighted a number of shortcomings of RAG as we know it.
Cobus Greyling
Cobus Greyling

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