AWS

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Explore the top contributors showcasing the highest number of app submissions within our community.

AWS

Amazon Web Services (AWS) is the world's most comprehensive and broadly adopted cloud platform, offering over 200 fully featured services from data centers globally. Since its launch in 2006, AWS has provided a highly reliable, scalable, low-cost infrastructure platform in the cloud that powers hundreds of thousands of businesses in 190 countries worldwide. AWS is a leader in cloud computing, offering services that span compute, storage, databases, networking, analytics, machine learning, artificial intelligence, Internet of Things (IoT), security, and enterprise applications.

General
Company	Amazon Web Services, Inc.
Founded	2006
Website	https://aws.amazon.com/
Documentation	https://docs.aws.amazon.com/
Technology Type	Cloud Provider

Start Building with AWS Products

AWS provides a vast array of services that enable developers and businesses to build sophisticated, scalable applications in the cloud. From foundational services like compute and storage to advanced machine learning and AI capabilities, AWS offers the tools needed to innovate and grow.

AWS SageMaker

AWS SageMaker is a fully managed machine learning service that enables developers to quickly and easily build, train, and deploy machine learning models at scale. You can find more information on our AWS SageMaker tech page.

AWS Kiro

Kiro is an AWS-powered agentic coding service that uses "spec-driven development" to turn prompts into code and tests. You can find more information on our AWS Kiro tech page.

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AWS AI Technologies Hackathon projects

Discover innovative solutions crafted with AWS AI Technologies, developed by our community members during our engaging hackathons.

HOLY-UNDERWRITERS

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FreshMart: A Multi-Agent Grocery Experience

FreshMart is a full-stack grocery ordering platform built on a multi-agent architecture using the Band SDK. Three specialized AI agents work together behind the scenes: a Manager agent that routes requests, a Query agent (LangGraph) that answers questions about products and orders, and an Action agent (CrewAI) that handles order mutations like cancellations and updates. On the frontend, customers get a polished Next.js portal where they can browse 30+ products with a shopping cart, place orders, and track them through the full lifecycle pending, processing, shipped, delivered. A built-in AI chat assistant (powered by Claude) lets customers view their orders, change quantities, or cancel — all in plain conversation. Key technical highlights: - Band SDK multi-agent orchestration across three frameworks (Anthropic SDK, LangGraph, CrewAI) - Supabase for auth, database, and real-time data - Background job that automatically advances order statuses over time - Cookie-based auth with scoped data access so each customer only sees their own orders - Full cart persistence, stock management, and server-side checkout validation

OmniSentinel: Watching Everything, Missing Nothing

OmniSentinel is an autonomous multi-agent crisis intelligence platform that helps organizations, governments, and emergency teams detect, understand, and respond to critical events in real time. Modern crises such as natural disasters, cyberattacks, infrastructure failures, and public health emergencies generate vast amounts of fragmented information that can overwhelm human decision-makers. OmniSentinel transforms this complexity into coordinated intelligence through a Band of AI Agents working together as a unified command center. The platform combines specialized agents that continuously monitor data, identify threats, gather intelligence, forecast potential developments, simulate response scenarios, and recommend optimal actions. Instead of operating independently, these agents collaborate, validate findings, and refine recommendations to provide accurate and actionable insights. This collective reasoning approach enables faster situational awareness and more confident decision-making during high-pressure events. OmniSentinel provides a real-time view of evolving situations, helping users understand current risks, anticipate future impacts, and evaluate possible response strategies before taking action. For demonstration purposes, the platform can simulate scenarios such as cyberattacks, severe weather events, infrastructure outages, or large-scale emergencies, showcasing how multiple AI agents coordinate autonomously to analyze information and generate strategic response plans within seconds. By turning information overload into coordinated intelligence, OmniSentinel empowers decision-makers to respond faster, smarter, and more effectively when every second matters.

Spec6: The enterprise intelligence operator

Spec6 uses Speechmatics in two distinct but connected ways: first as the live speech interface for the product, and second as a transcription engine for “spoken web” intelligence. That split is important, because this is not just “we added voice chat.” In the code, Speechmatics sits both at the front door of the system, where a user talks to Spec6 in real time, and deeper in the intelligence pipeline, where audio and video from the web can be converted into analyzable evidence. The live voice side starts in the frontend voice assistant at [/Users/nadhi/Desktop/win-win/src/frontend/react/chat/voice-assistant.tsx](/Users/nadhi/Desktop/win-win/src/frontend/react/chat/voice-assistant.tsx). The browser captures microphone input with `getUserMedia`, then converts the audio into the format Speechmatics expects: 16kHz mono PCM16. That matters because the browser does not just upload a blob after the user is done. It streams audio continuously in small chunks, which makes the experience feel like an actual assistant instead of a push-to-record form. The comment in that file describes the full loop clearly: mic input becomes PCM16, that stream goes to `/api/voice/transcribe/ws`, partial and final transcripts come back, and the final transcript is fed into the normal Spec6 agent loop. So the voice layer is not a separate AI product. It is an alternate input mode into the same reasoning engine that powers the rest of the app.

RevDev

CaliSignal is an AI SDR and GTM intelligence platform built for California startups. It uses Bright Data live web signals to discover high-fit accounts, detect buying windows, score ICP match, and identify the right stakeholders before competitors reach them. The platform turns fragmented public signals like funding news, hiring activity, job posts, reviews, and web changes into prioritized pipeline, account briefs, outreach drafts, alerts, and action workflows. Instead of making SDRs manually research accounts, CaliSignal gives teams a live revenue cockpit that shows who to contact, why now, what to say, and what action to take next.

MarketMindAI

MarketMind AI is an AI-powered business intelligence platform that turns any website into a complete marketing and growth audit. Simply enter a URL, and MarketMind uses Bright Data to crawl the website, discover competitors, gather customer sentiment from across the web, and analyze market positioning in real time. It then generates consultant-grade insights, including competitor intelligence, customer pain points, conversion opportunities, marketing campaigns, content strategies, and website redesign recommendations. What traditionally requires weeks of research and thousands of dollars in consulting fees is delivered in minutes through a single, intelligent dashboard.