Publications - AIdeSolutions

White Paper

Confidence by Design: Practical Patterns for Trustworthy AI Research Systems

The first three papers in this series built the argument for rethinking how trustworthiness is constructed in AI-enabled research. This paper closes the arc by demonstrating it, showing the confidence layer built into a working multi-agent modeling system where each property is a load-bearing architectural decision...

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Publication

A Decomposition Framework for Translating Published HE Model Descriptions into Executable R Code (R for HTA 2026)

Presented at R for HTA 2026. A published health economic model description is incomplete by design: it assumes the reader brings the tacit modeling knowledge that was never written down. Hand that sam...

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Publication

Use of Agentic AI to Create Health Economic Models (ISPOR 2026 Workshop)

This presentation, delivered at the ISPOR 2026 Workshop, explores a paradigm shift in health economic modeling: using AI not as a standalone tool, but as a reasoning engine within a structured multi-a...

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White Paper

Beyond Replication: What It Actually Means to Evaluate an AI-Generated Health Economic Model

When organizations evaluate AI-enabled health economic modeling tools, the question most frequently posed is whether the AI can replicate a published model. The appeal is understandable...

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White Paper

The Confidence Layer: A Design Philosophy for Trustworthy AI in Evidence Generation

The field agrees that accuracy metrics cannot tell you whether an AI research tool is trustworthy. This paper proposes the design response: a confidence layer built on four properties that make reliability visible and verifiable, embedded during construction rather than bolted on...

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White Paper

The Validation Gap: What Accuracy, Sensitivity, and Specificity Cannot Tell You About AI Research Tools

The widespread adoption of AI tools in HEOR has created a critical problem: common evaluation metrics were designed for simpler tasks. This paper explores where traditional metrics fall short in complex...

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White Paper

Invisible Errors: How to Know When an LLM Gets It Wrong

LLM errors in HEOR are invisible in output format. This white paper argues that responsible LLM use requires structural workflow architecture: automated validation, parameter-level traceability, and task decom...

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Publication

Understanding Multi-Agent Systems

From "One" to "Many": This presentation explores the shift from single-agent LLMs to multi-agent systems. It details common design patterns—such as sequential systems, parallel systems, and independen...

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White Paper

The Art of Delegation in the Era of AI: How to Brief an AI Like You'd Brief a Colleague

This guide explores the shift from treating AI as a mere tool to a collaborative teammate. Learn how to effectively brief an AI by leveraging the delegation skills you already possess, setting the rig...

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White Paper

5 Foundational Skills Every HEOR Team Needs for GenAI

True power in Generative AI comes from asking the right questions, not just using the tools. This guide outlines the five foundational skills every Health Economics and Outcomes Research (HEOR) team m...

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White Paper

From Task Replacement to Workflow Revolution

This paper explores the hidden crisis of 'digital graveyards' where valuable research insights are lost. It argues that the true power of GenAI lies not just in automating tasks, but in revolutionizin...

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Publication

Transforming LLMs into Reliable HEOR Research Tools

Foundation LLMs present significant challenges for scientific research, from hallucinations to a lack of reproducibility. This presentation outlines a methodical framework for transforming general-pur...

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White Paper

Decoding LLM Hallucinations: Beyond Just "Lack of Context"

LLM hallucinations are a multifaceted challenge, not a single problem. This brief decodes the primary causes of AI-generated misinformation—from imperfections in training data to suboptimal context ma...

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White Paper

AI Agents in Health Research: What Does “Agent” Actually Mean?

The term 'AI agent' is often misused, leading to confusion and poor tool selection. This guide clarifies the difference between structured AI workflows (like a systematic review) and adaptive AI agent...

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Publication

Upskilling for GenAI: A New Era in Research

GenAI is more than just a tool; it requires a new set of skills for researchers. This presentation outlines a practical upskilling journey, covering foundational principles, the balance between prompt...

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Publication

Augmenting Health Economic Model Report Creation with LLMs

This practical presentation demonstrates a specific use case for augmenting the creation of health economic model reports. It showcases a concrete workflow where LLMs assist in drafting and reviewing ...

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White Paper

Why Enterprise-Grade AI Requires a Purpose-Built Strategy

The choice between off-the-shelf AI and a custom solution is not just a technical preference; it's a strategic decision between a consumer-grade product and an enterprise-grade system. This white pape...

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White Paper

A Deep Dive into Advanced Retrieval-Augmented Generation (RAG)

Retrieval-Augmented Generation (RAG) is more than a simple pipeline; it's a sophisticated workflow that requires a deliberate architectural approach to succeed at scale. This white paper provides a bl...

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White Paper

Beyond Hype and Fear

The debate over Large Language Models isn't about hype versus fear; it's about a fundamental misunderstanding that leads organizations to treat them as standalone 'magic boxes,' resulting in staggerin...

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White Paper

LLM-as-a-Judge

Many organizations face what I call the 'AI Trust Paradox'—the potential efficiency of AI is often lost to the time-consuming manual verification needed to meet scientific standards. This whitepaper e...

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White Paper

Context Engineering: Why GenAI projects fail (or work)?

This whitepaper argues that the 95% failure rate of enterprise GenAI projects is not due to model limitations, but rather a lack of 'Context Engineering', a systematic architectural approach that prio...

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