CropGuard is a cutting-edge AI-driven platform for enhanced crop management, focusing on disease detection and crop recommendation. By analyzing images of plants, CropGuard's model accurately identifies a wide range of diseases, from bacterial blight and rust to leaf mold and viral infections. It offers detailed information on each disease, including causes, prevention methods, and treatments, helping users effectively manage and mitigate crop issues.
The platform also features an advanced crop recommendation system. Users input data like temperature, humidity, soil pH, water availability, and season, and the system suggests the most suitable crops for their conditions. This helps optimize yield and resource use by providing tailored crop suggestions based on environmental data.
Additionally, CropGuard includes a conversational AI assistant that answers crop-related questions, offers advice on maintaining healthy crops, and provides guidance on agricultural practices. Designed to be user-friendly, CropGuard integrates seamlessly into farming workflows, offering actionable insights that drive better crop management decisions.
Overall, CropGuard aims to improve agricultural productivity and sustainability with its innovative AI technology and practical features. Whether addressing crop diseases or selecting the best crops for your farm, CropGuard provides intelligent solutions for informed farming.

AI Agents Hack with LabLab and MindsDB

CropGuard is an AI platform for crop disease detection and recommendation. It uses advanced models to identify plant diseases from images and suggest suitable crops based on environmental factors, enhancing farm productivity and health.

BinaryBlitz

OpenAI

Llama 3

AI/ML API

Upstage

streamlit

CropGuard

This project introduces an Agentic AI‑powered claims workflow solution designed to transform healthcare revenue cycle management. One of the most persistent challenges in the industry is claim denials and rejections, often caused by errors in patient information, coding mistakes, or insufficient documentation. These denials slow down reimbursement, create cash flow issues, and increase administrative burden. Leveraging agentic AI, the solution deploys autonomous agents that seamlessly handle training, inference, and routing of claims data. A Training Agent builds machine learning models from historical claims, while an Inference Agent applies those models to new encounters, predicting outcomes before submission. Data pipelines ensure inputs and outputs flow seamlessly between agents, IBM Cloud Object Storage, and Watsonx Orchestrate workflows. The result is faster claims processing, reduced manual workload, improved accuracy, and secure, reproducible integration with existing systems. This project demonstrates how agentic AI can move healthcare organizations from reactive claims management to proactive, intelligent automation — ultimately accelerating reimbursements and improving operational efficiency.



Agentic AI‑powered claims workflow that automates training, inference, and routing of healthcare claims. Seamless data pipelines reduce denials, accelerate reimbursements, and integrate securely with Watsonx Orchestrate + IBM Cloud.

Team AI Agent 007

Innovating the world with cutting-edge technology solutions and services since 1911.

The Granite AI Models by IBM offer advanced language models for chatbots, precise instructions, multilingual support, and Japanese text processing, providing high performance and accuracy for diverse applications.

IBM Granite

IBM watsonx Assistant is a no-code AI platform that helps businesses create intelligent, generative AI-powered assistants for seamless, multi-channel interactions.

IBM watsonx Assistant

AI-Agents Driven Claims Workflow Automation

BIMSHI is an intelligent store management system designed to simplify inventory tracking, stock management, and analytics for retailers. It allows store owners to monitor current inventory in real-time, update stock levels easily, and receive actionable insights about product performance, demand trends, and restocking recommendations. By integrating the InventoryAgent and AnalyticsAgent, BIMSHI provides a seamless workflow that highlights fast-selling and slow-selling items, predicts low-stock products, and helps prevent overstocking or shortages. The system is built for efficiency and accuracy, ensuring that every decision is data-driven. With a user-friendly Streamlit dashboard, retailers can visualize their store data clearly, interact with stock controls, and generate insights instantly, making BIMSHI a powerful tool for smarter retail operations and informed business decisions.

BIMSHI is a smart store management app that tracks inventory, updates stock, and generates analytics insights to help retailers make data-driven decisions efficiently.

BIMSHI

K-Sales Expert is an AI-powered sales assistant designed for KIEFZCO (Dubai) and KT1CO (Tehran) to transform the way solar equipment is sourced, evaluated, and purchased across the UAE–Iran trade corridor. Built with watsonx.ai, the agent introduces the companies, qualifies incoming leads, and asks all essential commercial and technical questions such as model, capacity, quantity, destination, network type, budget, and payment terms. It then recommends suitable inverter and panel models based on brand reputation, project requirements, and market availability.

The system is designed to streamline early-stage buyer engagement, reduce response time, and ensure consistent, professional communication. By acting as the first point of contact, it helps standardize sales interactions, improves customer confidence, and showcases how AI can enhance international trade operations, even in complex regulatory environments. The project demonstrates how intelligent assistants can automate initial sales workflows and support real-world procurement processes for solar and industrial equipment.

K-Sales Expert is an AI-powered sales assistant for KIEFZCO & KT1CO that helps buyers select solar equipment, recommends inverter models, asks clarifying questions, and provides fast, professional trade guidance for GCC markets.

Watsonx.ai by IBM is a cutting-edge AI technology offering advanced machine learning, natural language processing, and data analysis tools. Build, train, and deploy AI models easily to gain insights and automate tasks. Flexible and scalable for various industries.

watsonx.ai

Generative Agents are computational software that simulate human behavior in interactive applications.

Generative Agents

GPT-5 is OpenAI’s most advanced general-purpose multimodal AI model, offering deep reasoning, broad context, personalized interaction, and safer, more reliable responses.

GPT-5

OpenAI is an AI research and deployment company

 K-Sales-Expert-KIEFZCO-KT1CO

Finlog is an advanced AI-driven financial intelligence system designed to streamline access to market information, corporate fundamentals, real-time stock pricing, financial calculations, and news insights using a fully automated agentic workflow. Built on top of *IBM watsonx Orchestrate*, Finlog demonstrates how Large Language Models (LLMs), when combined with structured tool usage and business-grade orchestration, can deliver high-quality, data-backed responses with precision, reliability, and interpretability.

At its core, Finlog is designed as an *agentic assistant, meaning it does not rely solely on the language model’s reasoning. Instead, it uses a combination of custom-built tools, external APIs, intelligent prompt routing, branching logic, and structured summarization to deliver accurate financial information. The implementation includes **FMP (Financial Modeling Prep) API tools, **DuckDuckGo Search tools, custom **math reasoning tools, and a **LangGraph-inspired branching workflow* to determine the correct sequence of actions.

An agentic financial assistant which was build on ibm wastonx orchestrate. It is capable of combining real data,news intelligence and analytical resoning

FinLoggers

Llama 3.1 is an open-source, state-of-the-art large language model (LLM) by Meta AI. It’s optimized for advanced NLP tasks, offering various model sizes, and focuses on transparency, safety, and accessibility.

Llama 3.1

Meta is a US technology company that owns the social networks Facebook and Instagram, the instant messaging apps WhatsApp and Messenger, and the virtual reality device brand Meta Quest.

Finlog

Cloud CoPilot

A multi-agent system built with IBM Watsonx Orchestrate to analyze, review, and optimize IBM Cloud architectures in alignment with the IBM Well-Architected Framework.

Overview
Designing and maintaining cloud architecture is complex. Modern environments involve multiple services, networks, security configurations, and deployment patterns. Ensuring architectures are secure, efficient, cost-effective, reliable, operationally sound, and sustainable requires meticulous review against best practices.

Challenges

Time-Consuming: Manual review of diagrams and configurations can take days or weeks.

Error-Prone: Human reviewers may miss subtle misconfigurations or inefficiencies.

Multi-Domain Expertise Needed: Evaluating security, performance, cost, reliability, operational excellence, and sustainability is rarely within a single architect’s expertise.

Frequent Updates: Rapidly evolving cloud services require constant review.

Unstructured Documentation: Diagrams, PDFs, and text make extracting insights manually difficult.

Why a Multi-Agent Model Helps

Parallel Expertise: Each agent focuses on a specific pillar, enabling simultaneous evaluation.

Consistency & Accuracy: Structured frameworks reduce errors and ensure uniform reviews.

Scalability: Multiple architectures can be reviewed simultaneously, improving throughput.

Knowledge Aggregation: The Lead Architect Agent consolidates inputs into a comprehensive report.

Continuous Updates: Agents can be updated with new rules or best practices, keeping reviews current.

By combining automation, specialization, and coordination, the system turns cloud architecture review from a tedious, error-prone task into a streamlined, accurate, and efficient process.

Cloud Copilot helps cloud architects to review their cloud architecture in a comprehensive way on basis of IBM's well architected framework. 

Out of tokens

Explore Langflow's capabilities for seamless language model integration and interaction.

langflow

Llama 3.2 is Meta’s open-source AI model, optimized for edge devices with multimodal capabilities, enabling text and image processing for broader AI applications across platforms.

Qubic

Hack the Future