Top Builders

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

Bright Data

Bright Data (formerly Luminati Networks) is a web data collection platform founded in 2014 and headquartered in Netanya, Israel. The platform gives developers and data teams access to proxy infrastructure, web scraping APIs, browser automation, and pre-built datasets, all backed by a network of over 400 million IP addresses across 195 countries.

The company powers data pipelines for more than 20,000 organisations in AI, eCommerce, finance, and market research, and has established legal precedents around public web data collection through court rulings against Meta and X (Twitter).

General
CompanyBright Data
Founded2014 (rebranded from Luminati Networks in 2021)
HeadquartersNetanya, Israel
Websitebrightdata.com
Documentationdocs.brightdata.com
GitHubgithub.com/brightdata
TypeWeb Data Platform, Proxy Infrastructure, Scraping APIs

Core Products

Proxy Networks

Bright Data operates four types of proxy networks: residential (400M+ real-user IPs), datacenter, static ISP, and mobile proxies. Each type is suited to different scraping workloads, from high-volume crawling to bypassing geo-restrictions. Proxies are billed per GB or via monthly plans.

Web Scraper API

The Web Scraper API extracts structured data from 120+ websites with automatic unblocking, CAPTCHA solving, and JavaScript rendering built in. It includes 600+ ready-made scrapers for popular platforms and delivers results in JSON or structured formats.

SERP API

The SERP API returns real-time, structured search engine results from Google, Bing, Yandex, and four other engines. It covers 195 countries, supports geo-targeting, and charges only for successful requests.

Scraping Browser (Browser API)

The Scraping Browser is a fully managed browser that runs Puppeteer, Playwright, and Selenium scripts on Bright Data infrastructure. It handles fingerprinting, CAPTCHA solving, proxy rotation, and JavaScript rendering automatically.

Web Unlocker

Web Unlocker is a middleware layer that automatically bypasses bot detection, CAPTCHAs, and IP blocks. It sits between your scraper and the target site, handling the unblocking layer transparently.

Datasets

Ready-made datasets from 100+ popular platforms are available for direct download or scheduled delivery. Data is pre-collected, validated, and structured, making it suitable for AI training, market research, and competitive analysis without writing any scraping code.

MCP Server

The Bright Data MCP Server provides 60+ AI-ready tools for web search, page navigation, structured data extraction, and browser automation. It integrates with Claude, Claude Code, Cursor, and other AI coding environments that support the Model Context Protocol.

Developer Resources

Bright Data maintains Python and JavaScript SDKs, a CLI tool, and MCP server for AI agent integration. All products are available via REST API and work with standard HTTP client libraries.

Key Features

400M+ IP Network The proxy pool spans residential, datacenter, ISP, and mobile IPs across 195 countries, with city and carrier-level targeting available.

Built-in Unblocking Proxy rotation, CAPTCHA solving, browser fingerprinting, and retry logic are handled automatically across all product tiers, so scrapers do not need to implement these independently.

AI and Agent Integration The MCP server and AI SDK connect Bright Data tools directly to Claude, Cursor, and other LLM-based agents, giving them real-time access to web data without leaving the development environment.

Pay-per-Result Pricing Several products (SERP API, Web Scraper API) charge only for successful responses, reducing waste on failed requests.

Use Cases

AI Training Data Collection Teams use Bright Data's datasets and scraping APIs to gather public web data for fine-tuning models, building RAG corpora, and benchmarking.

Competitive Intelligence eCommerce and finance teams use SERP and Web Scraper APIs to monitor prices, rankings, and market signals across geographies in real time.

Market Research Ready-made datasets from social platforms, marketplaces, and review sites let analysts skip the scraping layer and work directly with structured data.

AI Agent Web Access Developer teams integrate the Bright Data MCP Server with Claude and other agents to give them live access to search results, page content, and structured extracts during task execution.

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Bright Data AI Technologies Hackathon projects

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

ConsultIn

ConsultIn

Quantivo AI, also known as BOA (Business Opportunity Analysis), is an AI-powered SaaS platform that helps small business owners and entrepreneurs make data-driven decisions about their business opportunities. Given a business's context — category, location, growth stage, and goals — the system automatically scrapes real local market data, routes and filters it through a deterministic classification pipeline, and runs parallel sentiment and SWOT analysis using LLM agents orchestrated via LangGraph. The result is a comprehensive report featuring an executive summary, market insights, actionable recommendations, and a visual heatmap of the local competitive landscape. The platform is built around a contract-first architecture: a shared Pydantic schema and Protocol-based interface layer let independent workstreams — scraping, routing, retrieval, agent reasoning, and orchestration — develop and test against mocks in parallel before wiring in production components. Under the hood, Quantivo AI uses a hybrid dense-and-sparse retrieval system (Qdrant with BGE-M3 embeddings) fused via reciprocal rank fusion, and every confidence score is computed quantitatively from source count, agreement, and recency rather than left to subjective LLM judgment. The system is designed for graceful degradation: if any single data source or agent fails, the pipeline still produces a partial, clearly-labeled report instead of failing outright. Quantivo AI was built for the AMD Developer Hackathon (ACT II, Track Unicorn), with LLM inference and embedding generation running on AMD MI300X/MI350 GPU hardware via Fireworks AI and a self-hosted BGE-M3 embedding server, demonstrating a production-realistic AI pipeline built entirely on AMD's AI stack.

ConsultIn

ConsultIn

Quantivo AI, also known as BOA (Business Opportunity Analysis), is an AI-powered SaaS platform that helps small business owners and entrepreneurs make data-driven decisions about their business opportunities. Given a business's context — category, location, growth stage, and goals — the system automatically scrapes real local market data, routes and filters it through a deterministic classification pipeline, and runs parallel sentiment and SWOT analysis using LLM agents orchestrated via LangGraph. The result is a comprehensive report featuring an executive summary, market insights, actionable recommendations, and a visual heatmap of the local competitive landscape. The platform is built around a contract-first architecture: a shared Pydantic schema and Protocol-based interface layer let independent workstreams — scraping, routing, retrieval, agent reasoning, and orchestration — develop and test against mocks in parallel before wiring in production components. Under the hood, Quantivo AI uses a hybrid dense-and-sparse retrieval system (Qdrant with BGE-M3 embeddings) fused via reciprocal rank fusion, and every confidence score is computed quantitatively from source count, agreement, and recency rather than left to subjective LLM judgment. The system is designed for graceful degradation: if any single data source or agent fails, the pipeline still produces a partial, clearly-labeled report instead of failing outright. Quantivo AI was built for the AMD Developer Hackathon (ACT II, Track Unicorn), with LLM inference and embedding generation running on AMD MI300X/MI350 GPU hardware via Fireworks AI and a self-hosted BGE-M3 embedding server, demonstrating a production-realistic AI pipeline built entirely on AMD's AI stack.

ConsultIn

ConsultIn

Quantivo AI, also known as BOA (Business Opportunity Analysis), is an AI-powered SaaS platform that helps small business owners and entrepreneurs make data-driven decisions about their business opportunities. Given a business's context — category, location, growth stage, and goals — the system automatically scrapes real local market data, routes and filters it through a deterministic classification pipeline, and runs parallel sentiment and SWOT analysis using LLM agents orchestrated via LangGraph. The result is a comprehensive report featuring an executive summary, market insights, actionable recommendations, and a visual heatmap of the local competitive landscape. The platform is built around a contract-first architecture: a shared Pydantic schema and Protocol-based interface layer let independent workstreams — scraping, routing, retrieval, agent reasoning, and orchestration — develop and test against mocks in parallel before wiring in production components. Under the hood, Quantivo AI uses a hybrid dense-and-sparse retrieval system (Qdrant with BGE-M3 embeddings) fused via reciprocal rank fusion, and every confidence score is computed quantitatively from source count, agreement, and recency rather than left to subjective LLM judgment. The system is designed for graceful degradation: if any single data source or agent fails, the pipeline still produces a partial, clearly-labeled report instead of failing outright. Quantivo AI was built for the AMD Developer Hackathon (ACT II, Track Unicorn), with LLM inference and embedding generation running on AMD MI300X/MI350 GPU hardware via Fireworks AI and a self-hosted BGE-M3 embedding server, demonstrating a production-realistic AI pipeline built entirely on AMD's AI stack.

Slack data wizard

Slack data wizard

Every company has data. Most don't have a data team. That gap is the market. In a small business, the people who own the data can't query it. The office manager holds the signup sheet. The clinic administrator holds scanned invoices. Neither writes SQL; neither has an engineer to ask. So the question never gets asked. Slack Data Wizard is that data team. Drop a CSV and it becomes a typed table, named in your words. Ask "how many signups per country?" and Gemma writes the SQL. Say "create a schema called sales" and Gemma writes the DDL. Say "build a medallion pipeline" and get bronze, silver and gold tables. Say "create a dashboard" and Gemma picks the chart and publishes a real Tableau workbook. Ask for "the top 10 countries by population" and Perplexity pulls the real figures from the internet, with citations — or OpenAI generates synthetic rows for testing. You can even ask by voice through an ElevenLabs agent, or reach the same tools from Claude and ChatGPT via MCP. Then drop in a scanned PDF — the case that matters most. Hospitals and billing offices still run on paper. Today a human retypes it. Gemma's vision reads the table straight off the page. And that changes who touches the data: the person who produces it loads the lakehouse directly — no analyst, no engineer, no untracked copies in between. For sensitive records, the fewer people in the chain, the smaller the leak surface. So the AMD GPU is not an implementation detail. A scanned patient record is exactly the data you may not paste into a closed third-party API — HIPAA, GDPR. An open Gemma on your own AMD Instinct GPU (ROCm) means the page never leaves the building. Take it away and in regulated industries you get no product. A model that writes CREATE TABLE can also write DROP TABLE — so every statement is classified before it runs, and destructive ones wait for a click. This deserves to win because it solves a real problem: it makes data handling faster, simpler and accessible to everyone.

GateTrack Sentinel

GateTrack Sentinel

GateTrack Sentinel is a human-governed visitor-risk operations platform designed for regulated and security-sensitive environments. It validates each visitor request, blocks unsafe or manipulative input before model inference, applies deterministic risk scoring and routing, and retrieves controlled read-only policy context. Fireworks AI is then used only to produce a bounded advisory narrative. The model cannot change the authoritative risk score, route, selected policies or final human decision. Every workflow stage is captured through bounded-loop contracts that record permitted tools, verification results, attempt limits, stop reasons and audit events. Each completed case can generate a portable SHA-256 proof packet containing the case record, decision lineage, source-confidence map, runtime evidence, loop-control records and a tamper-evident audit chain. The public demonstration uses synthetic data only. It demonstrates routine visitor clearance, escalated human review, prompt-injection blocking, structured live-provider reviews, deterministic replay and independently verifiable evidence. GateTrack Sentinel is designed for security, compliance and audit teams in regulated SMEs, casinos, DNFBPs and other organisations that need explainable and accountable AI-assisted operations. Its commercial pathway includes containerised subscription deployment, implementation support, policy configuration and compliance services through AUREX SICOS Advisory Ltd.

AITinerary

AITinerary

AITinerary – Your AI Travel Co-Pilot AITinerary is an AI-powered travel planning platform designed to simplify every stage of a trip—from discovering destinations to creating personalized itineraries and exploring hidden gems. Instead of spending hours researching across multiple websites, users simply describe their travel preferences, budget, trip duration, and interests, and AITinerary generates a complete travel plan tailored to them. One of the core ideas behind AITinerary is bridging the gap between travel inspiration and actual trip planning. Today, many people discover amazing destinations, restaurants, and experiences through Instagram Reels and YouTube videos, but planning a trip around that content is still a manual process. AITinerary aims to let users provide a Reel or YouTube link and transform that inspiration into a practical itinerary with recommended attractions, restaurants, accommodations, transportation, and nearby experiences. The platform also acts as an intelligent travel companion throughout the journey. It recommends hidden gems beyond popular tourist attractions not to miss, adapts plans based on user preferences, provides contextual information about places, helps optimize travel budgets, and enables expense tracking and bill splitting for groups. For the MVP, the focus is on AI-generated itineraries, social media-inspired trip planning, personalized recommendations, and intelligent travel assistance. The architecture is designed to integrate with travel providers and booking platforms in the future, allowing users to seamlessly transition from planning to booking within a single experience all at one place. By combining generative AI, travel data, and personalization, AITinerary aims to become an all-in-one travel assistant that helps users spend less time planning and more time experiencing memorable journeys. "From inspiration to itinerary in seconds. See it. Plan it. Experience it."