AI Governance, Training and Solutions
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Consensus Is Not Correctness: What Multi-LLM Voting Can and Cannot Solve
A coalition of Swift, Euroclear, UBS and other financial market infrastructure providers has demonstrated a potential technical answer to one of enterprise AI's hardest problems.
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View all →Consensus Is Not Correctness: What Multi-LLM Voting Can and Cannot Solve
A coalition of Swift, Euroclear, UBS and other financial market infrastructure providers has demonstrated a potential technical answer to one of enterprise AI's hardest problems.
Small Open-Weight Models in Humanitarian Deployment: What a gemma-4-e4b Risk Assessment Reveals
The humanitarian sector is moving to small open-weight models for cost, data sovereignty, edge deployment and multilingual reach. An independent Sakshi evaluation of gemma-4-e4b found sycophancy under contradiction, self-verification regression, and overconfident calibration.
AI Policy and AI Governance Framework For Non-Profit
A public AI policy is a statement of commitments addressed to the outside world. An internal AI governance framework is an operational instruction set addressed to staff. Using the ICRC AI policy as a reference, this article explains why both are necessary.
Deep Dives
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The Agent Engineering Standard: A 13-Category Specification for AI Systems
Every category traces back to something that broke. Here's what broke, what we built, and how we enforce it.
ERC-3643 Tokens as Institutional-Grade Collateral for OTC Derivatives
This paper explores whether ERC-3643 compliant stablecoins can serve as eligible collateral for non-regulatory variation margin in institutional OTC derivative operations.
ERC-3643 tokens for Derivative Collateralization
ERC-3643 tokens for Derivative Collateralization explores how compliant tokenized collateral can improve bilateral OTC trading by embedding regulatory compliance directly into the token infrastructure while enabling automated settlement and risk management through smart contracts.
Case Studies
View all →Pre-Deployment AI Risk Assessment of gemma-4-e4b
QualitaX's Sakshi audit of gemma-4-e4b documented three structural failure modes accuracy benchmarks do not test for.
AI-Assisted Corporate Partnership Prospecting for a Non-Profit
An AI-assisted research-to-outreach engine that lets a two-person corporate-partnerships team source, qualify, and contact partners in a fraction of the time — delivering named, scored, contactable accounts with dated evidence and the right offer already attached.
Production Intent Pipeline for B2B Sales Intelligence
Managed pipeline that identifies in-market buyers from LinkedIn engagement signals, scores and enriches contacts against a custom ICP, and delivers qualified leads directly into HubSpot — designed for continuous weekly operation with resumable execution and conservative rate limiting.