Results for "ai integration".

Claude MCP Explained: Building Enterprise AI Integrations That Actually Scale

What the Model Context Protocol actually is, why it changes enterprise AI architecture and how to...…

Getting coupa procurement data into redshift for spend analytics and the api integration was not straightforward

AI Can Find the Code. It Didn't Know How the System Worked

21 bug fixes, two models, same failures. Better LLMs marginally improve things, but still failed on system boundaries and integration.…

When AI reviews science: Can we trust the referee?

The volume of scientific submissions continues to climb, outpacing the capacity of qualified human referees and stretching editorial timelines. At the same time, modern large language models (LLMs) of…

FAIR_XAI: Improving Multimodal Foundation Model Fairness via Explainability for Wellbeing Assessment

In recent years, the integration of multimodal machine learning in wellbeing assessment has offered transformative potential for monitoring mental health. However, with the rapid advancement of Vision…

Time-Series Forecasting in Safety-Critical Environments: An EU-AI-Act-Compliant Open-Source Package / Zeitreihenprognose in sicherheitskritischen Umgebungen: Ein KI-VO-konformes Open-Source-Paket

With spotforecast2-safe we present an integrated Compliance-by-Design approach to Python-based point forecasting of time series in safety-critical environments. A review of the relevant open-source to…

Terra API (YC W21) Hiring: Applied AI Strategist(Health Intelligence)

What this role actually is This is not “market research.” No 60‑page decks. No generic “digital health is big” observations. This is a continuous loop: market → signal → implication → decision → shi…

A Decoupled Human-in-the-Loop System for Controlled Autonomy in Agentic Workflows

AI agents are increasingly deployed to execute tasks and make decisions within agentic workflows, introducing new requirements for safe and controlled autonomy. Prior work has established the importan…

Don't Make the LLM Read the Graph: Make the Graph Think

We investigate whether explicit belief graphs improve LLM performance in cooperative multi-agent reasoning. Through 3,000+ controlled trials across four LLM families in the cooperative card game Hanab…

An Information-Geometric Framework for Stability Analysis of Large Language Models under Entropic Stress

As large language models (LLMs) are increasingly deployed in high-stakes and operational settings, evaluation strategies based solely on aggregate accuracy are often insucient to characterize system r…

An Analysis of the Coordination Gap between Joint and Modular Learning for Job Shop Scheduling with Transportation Resources

Efficient job-shop scheduling with transportation resources is critical for high-performance manufacturing. With the rise of "decentralized factories", multi-agent reinforcement learning has emerged a…

Interoceptive machine framework: Toward interoception-inspired regulatory architectures in artificial intelligence

This review proposes an integrative framework grounded on interoception and embodied AI-termed the interoceptive machine framework-that translates biologically inspired principles of internal-state re…