KVAi Research
We produce applied research on AI. Not for other researchers — for those who need to understand, invest, and act.
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Publications
MAR 2026
Research Note
Epistemic Knowledge Access
OIDA: Organizational Knowledge in the Age of Associative Intelligence
Federico Bottino, Carlo Ferrero, Nicholas Dosio, Pierfrancesco Beneventano
A framework that gives every unit of organisational knowledge a computable epistemic status — typed, scored, dynamically maintained. The substrate your AI agents need to reason reliably, avoid contradiction, and scale institutional memory.
FEB 2026
Conference Paper
AI & Strategy
A Multi-Layer AI Framework for Venture Building
Maryam Fooladi, Federico Bottino
A framework proposing a multi-layer AI architecture for venture building — integrating strategic reasoning, operational automation, and human-AI collaboration across the full lifecycle of new ventures.
FEB 2026
White Paper
Media & Propaganda Analysis
Beyond Sentiment: Why Traditional NLP Fails Political News — and How LLMs Can Bridge the Gap
Maryam Fooladi, Federico Bottino
A comparative study identifying "neutral collapse" — the systematic failure of sentiment models to capture the rhetorical richness of political discourse — and demonstrating how LLMs can bridge the gap between surface-level polarity and deep narrative structure.
NOV 2025
Policy Analysis
AI Compliance & AI Law
AI Compliance, Simplified: Navigate the EU AI Act and Beyond with Confidence
Giacomo Conti, Alberto Trivero
ShikAI's first white paper maps the combined regulatory surface of EU AI Act, GDPR, DSA and DMA — and offers a practical path forward for European enterprises navigating compliance without sacrificing innovation.
“We are entering an era of associative intelligence — biological and artificial. Yet the driving force remains unchanged: human imagination. AI is not just computer science; it is applied philosophy, grounded in mathematics and logic. This is the era of philosophers and machines.”
Federico Bottino
CEO, Kakashi Venture Accelerator
Scientific Committee
Our research is reviewed and guided by prestigious academics and researchers.
Dr. Pierfrancesco Beneventano
— Massachusetts Institute of Technology (MIT)Dr. Pierfrancesco Beneventano
Massachusetts Institute of Technology (MIT)
Postdoctoral researcher at MIT, working under Prof. Tomaso Poggio on Machine Learning Theory. He completed his PhD at Princeton University under Profs. Boris Hanin and Jason D. Lee, and holds an MSc in Mathematics from ETH Zurich. His research focuses on understanding what neural networks learn, how optimizers shape them, and the dynamics of training stability.
He collaborated with KVA on the OIDA framework, a technical report on epistemic knowledge management for AI agents.
Prof. Giancarlo Ruffo
— University of Turin / Università del Piemonte Orientale
Prof. Giancarlo Ruffo
University of Turin / Università del Piemonte Orientale
Associate Professor of Computer Science at the University of Turin and the Università del Piemonte Orientale. His research spans Data Mining, Computational Social Science, and Network Science, with a focus on misinformation diffusion, stance detection, and social media analysis.
He is a member of KVA's Scientific Committee, contributing expertise in computational approaches to complex social phenomena.
Dr. Giuseppe Futia
— GraphAware / Politecnico di TorinoDr. Giuseppe Futia
GraphAware / Politecnico di Torino
Senior Data Scientist at GraphAware and Fellow at the Nexa Center for Internet and Society, Politecnico di Torino. He holds a PhD in Computer Engineering from the Politecnico di Torino, where he focused on Graph Representation Learning for the automatic construction of Knowledge Graphs.
He is a member of KVA's Scientific Committee, bringing deep expertise in knowledge representation and graph-based AI systems.
Dr. Ani Fox Bochenkov
— CIQ / Atrytone ConsultingDr. Ani Fox Bochenkov
CIQ / Atrytone Consulting
Entrepreneur and management consultant with two PhDs, founder and CEO of Atrytone Consulting, based in Luxembourg. His work sits at the intersection of AI and sustainability, helping organisations turn ESG mandates into competitive advantage. He has authored over 25 white papers for AWS and Oracle, with deep expertise in cloud computing, digital infrastructure, and international regulatory compliance.
He is a member of KVA's Scientific Committee, contributing a practitioner's perspective on AI adoption and enterprise strategy.
The problem isn't
a lack of research.
It's a lack of
translation.
Most AI research exists in a vacuum — either too academic for implementation or too promotional for objective strategy. We bridge this divide.
KVAi Research acts as the analytical layer for Kakashi Venture Accelerator, dissecting algorithmic shifts, regulatory changes, and market bottlenecks to provide actionable roadmaps.
Current Investigations
AI Compliance & AI Law
Regulation as competitive advantage, not a constraint.
Epistemic Knowledge Access
How we access knowledge — and how AI changes the rules.
Media & Propaganda Analysis
Beyond sentiment. Understanding the narrative, not just the tone.
AI Market Intelligence
Maps, numbers, and signals from the global AI market.
LLMs Performance Benchmarking
Independent benchmarks. No sponsors. No convenient rankings.
Neurocognitive Architecture & Organizational Psychometrics
How minds organize, decide, and adapt — measured, not assumed.
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