April 8, 2025
Engineering, Phase 2 Labs

Imagine you’re an inventory manager for a retail business and you need to quickly verify stock levels for an unexpected large order while away from your computer. Instead of logging into a dashboard, navigating through menus, and analyzing spreadsheets, you simply send a text message: "Do we have enough iPhones to fulfill an order for 100 units?" Within seconds, you receive a reply: "You have 157 iPhones currently in stock, so you can fulfill this order. Based on your current sales rate of...

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April 2, 2025
Engineering, Phase 2 Labs

Introduction There’s been a lot of excitement lately in our P2 Labs team about the possibilities opened up by Anthropic’s Model Context Protocol, which enables AI tools to connect to a rapidly growing range of external tools and services. One question we've been exploring: how effectively can AI-powered coding assistants handle real-world development tasks when given access to the same resources a human would? The Experiment Since we’ve also been doing some work lately updating our Resume Sizzler demo, that provided use with...

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March 25, 2025
Engineering, Phase 2 Labs

Mobile application deployment has historically been a cumbersome process. Each deployment typically requires two builds (one iOS and one Android), each deployed to a separate store instance that must be manually configured and managed. While several effective tools have emerged in recent years to streamline this process, they all are understandably tuned to the most common use case: building one application for each platform and deploying those applications to the App Store and Play Store, respectively.  However, business needs are varied...

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March 17, 2025
Engineering, Phase 2 Labs

How Multi-Modal LLMs are Revolutionizing Document Processing Anyone who has worked with historical archives, ancestral records, or aged business documents knows the frustration all too well. You're staring at a handwritten letter from the 1800s, a faded hospital record, or a weathered legal document that holds valuable information—if only you could reliably extract it. Traditional Optical Character Recognition (OCR) promised to bridge this gap between physical documents and digital data, but for many challenging documents, it has fallen persistently short. For decades,...

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February 24, 2025
Artificial Intelligence, Engineering, LangGraph, Phase 2 Labs, Technical Tutorial

LangGraph is a framework designed for building and managing complex AI workflows using a graph-based approach. This article provides a comprehensive guide to its core components, implementation patterns, and best practices. Key Highlights: LangGraph Studio: A powerful IDE for real-time visualization, debugging, and monitoring of graph executions. Features include graph visualization, hot reloading, and interactive debugging. Graph Components: LangGraph workflows consist of nodes (processing units), edges (connections defining flow), and state (persistent context). Types of Nodes: Includes LLM nodes (leveraging AI models), agent nodes...

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