Bright Data Scraping Browser

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Bright Data Scraping Browser

The Bright Data Scraping Browser is a cloud-hosted, managed browser environment that developers control using Playwright, Puppeteer, or Selenium. Unlike a self-hosted headless browser, all proxy routing, CAPTCHA solving, browser fingerprinting, and retry logic are handled automatically by Bright Data's infrastructure, so scripts focus on data extraction rather than unblocking.

General
Developer	Bright Data
Type	Managed Cloud Browser API
Protocols	Playwright, Puppeteer, Selenium
Documentation	docs.brightdata.com/browser
Python Boilerplate	brightdata/bright-data-browser-api-python-playwright-project

Core Features

Playwright, Puppeteer, and Selenium compatible: connect your existing scripts to the managed browser via a CDP (Chrome DevTools Protocol) endpoint, no SDK change required.
Built-in proxy rotation: each session is automatically routed through Bright Data's residential or datacenter proxy network.
CAPTCHA auto-solving: CAPTCHAs are solved in the background without script-level intervention.
Browser fingerprint management: browser signatures are rotated and normalised to avoid detection.
JavaScript rendering: full JS execution before data extraction, suitable for SPAs and dynamically loaded content.
Auto-scaling infrastructure: browser instances scale with your request volume; no pool management required.

Tools and Resources

Python Playwright Boilerplate: ready-to-run Python example project connecting Playwright to the Scraping Browser.
API Documentation: endpoint reference and session configuration options.
Control Panel: create browser zones and retrieve CDP connection strings.

Ecosystem and Integrations

Works alongside Bright Data proxy zones for granular proxy type selection per browser session.
Output can feed directly into structured data pipelines, databases, or AI training corpora.
Combined with the Web Unlocker for layered unblocking on particularly difficult targets.
The MCP Server exposes browser automation capabilities to AI agents without requiring direct Playwright scripting.

Connect your Playwright or Puppeteer scripts to the managed browser at brightdata.com/products/scraping-browser or follow the quickstart documentation.

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Bright Data Bright Data Scraping Browser AI technology Hackathon projects

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

Reddit Intelligence Swarm

Reddit Swarm Intelligence is a full-stack, agentic AI system that transforms Reddit into a live, queryable knowledge base. Using BrightData's web scraping infrastructure, it collects posts and comments on-demand across user-defined categories. A multi-agent LangGraph swarm then processes the raw data: a Keyword Extractor identifies the most relevant search terms, a Database Writer archives everything into a structured PostgreSQL schema organized by hierarchical topics, and a Data Synthesizer generates natural-language answers grounded in the scraped content. The Vue.js dashboard offers a rich analytical surface — users can trigger batch scrapes, read AI-generated category summaries, explore topic metrics via bar charts, and dynamically extract subtopics through an on-demand LLM clustering agent that renders the results as an interactive pie chart. Clicking any pie slice fires an intelligent query directly into the Swarm chat, which synthesizes Reddit sentiment and key perspectives on that subtopic in real time.

AI Recruitment Platform

AI Recruitment Platform is a multi-agent system designed to automate and enhance the job discovery process for software and data professionals. The platform continuously collects job postings from multiple sources, including LinkedIn and staff.am, and processes them through a collaborative network of specialized agents. The system is built around a three-agent architecture. The Ingestion Agent is responsible for crawling, collecting, and normalizing job postings from various online sources. Once jobs are gathered, the Scoring Agent evaluates opportunities based on predefined criteria such as role relevance, skills, location, employment type, and other metadata. Finally, the Recommendation Agent analyzes the ranked opportunities and generates personalized recommendations for users. To demonstrate the agent workflow, the platform includes an interactive dashboard that visualizes the entire pipeline from data ingestion to recommendation generation. Users can monitor crawler activity, view job statistics, inspect processed opportunities, and observe how agents collaborate to transform raw job data into actionable recommendations. The project addresses a common challenge faced by job seekers: discovering relevant opportunities quickly across fragmented platforms. By automating job collection and leveraging agent-based processing, the system significantly reduces manual effort while increasing coverage and relevance. Key features include: • Multi-source job crawling and aggregation • Autonomous multi-agent workflow • Job scoring and ranking engine • Recommendation generation pipeline • Real-time dashboard and monitoring • SQLite-based persistence layer • Smart fallback mechanisms for high availability • Streamlit-powered user interface The platform demonstrates how multi-agent systems can be applied to real-world productivity and career development problems, showcasing autonomous collaboration, workflow orchestration, and practical AI-assisted decision-making.

PriceGhost: Dynamic Pricing Forensic Exposé

PriceGhost is a full-stack forensic intelligence platform that detects, measures, and cryptographically proves dynamic geographic pricing discrimination. THE PROBLEM: Corporations silently charge different prices based on your location, device, and browser fingerprint. 78% of consumers report feeling targeted by location-based pricing bias, yet proving it is nearly impossible. HOW IT WORKS: PriceGhost coordinates 10 simultaneous residential proxy scrapes across global coordinates (Mumbai, New York, London, Tokyo, Berlin, Sydney, Lagos, Buenos Aires, Dubai, Singapore) via Bright Data's Web Unlocker API. Each scrape rotates device fingerprints and captures raw HTML payloads. STATISTICAL FORENSICS ENGINE: Four custom mathematical algorithms run natively — Gini Coefficient of Spatial Inequality, Coefficient of Variation, Mann-Whitney U Significance Test (p < 0.05), and GDP Pearson Wealth Correlation — establishing courtroom-ready mathematical proof of pricing discrimination. AI-POWERED PARSING: When standard regex price extraction fails on complex HTML, Featherless AI's hosted Llama-3 model acts as a semantic fallback parser. AI/ML API generates authoritative natural language indictments styled as investigative exposés. COGNITIVE MEMORY: Cognee's semantic graph database indexes every pricing anomaly, enabling live queries against historical precedents to expose long-term corporate discrimination patterns. AUTOMATED ALERTS: TriggerWare webhooks automatically dispatch incident alerts to legal networks when Gini/Pearson indices flag "Severe" exploitation levels. EVIDENCE INTEGRITY: Every scrape result is sealed with SHA-256 cryptographic signatures and timestamp chains, producing immutable evidence packages exportable as courtroom-ready JSON dossiers. BUILT WITH: Next.js 16 (Turbopack), better-sqlite3 (7-table schema with WAL), Recharts composed visualizations, Leaflet dynamic trace maps.

VanTage - Due diligence, on a timeline

Private equity associates spend roughly 40 hours per target on preliminary due diligence—a full week lost to browser tabs, public filings, news archives, and litigation records, manually stitched into something an investment committee will trust. Most of that week isn't analysis; it's gathering. Vantage does it in 40 seconds. Point it at a company and it pulls from 12 distinct web sources at once, assembling them into a live knowledge graph: a connected map of the target's people, financials, legal exposure, customers, suppliers, and reputational signals. Relationships that normally take days to cross-reference appear instantly—the board member sitting on a competitor's audit committee, the lawsuit filed quietly three states away, the executive churn that began before the numbers softened. Red flags don't wait to be found. Vantage automatically surfaces litigation spikes, leadership departures, restatements, and regulatory actions, ranked and explained. A 90-day time slider lets you drag through recent history and watch the target's profile change—because knowing when something shifted is often more revealing than knowing that it did. Every claim is cited back to its source, so partners can audit it and committees can rely on it. Every memo lands IC-ready. This defensibility is powered by Bright Data, whose reliable, large-scale, structured web access makes a trustworthy knowledge graph possible where brittle scrapers and stale databases fail. We target middle-market PE associates—the highest willingness-to-pay segment in B2B software, where seats command $500–$2,000 per month. Their time is billed against nine-figure decisions, and a single avoided bad deal or faster close justifies the spend many times over. Vantage turns the most tedious week in the deal process into a 40-second starting point.

ROGUE: Open-web LLM Threat Intelligence Agent

A new way to jailbreak AI appears on Reddit, X, or arXiv almost every day. By the time a quarterly red-team catches it, it has already worked on a production chatbot. ROGUE closes that gap , the red-team that never sleeps. ROGUE is an autonomous red-team agent. It continuously harvests new LLM attacks from 19 live open-web sources — Reddit/X jailbreak communities, arXiv, GitHub (the Pliny umbrella), HuggingFace, MITRE ATLAS, OWASP, and vendor safety blogs — then reproduces each against YOUR deployment: your system prompt, your declared tools, your target model, scored together. Not a bare model. Not a frozen test bank. Your actual setup, against today's attacks. It's the only project here using Bright Data MCP on BOTH sides. As a consumer, the discovery agent reasons over Bright Data's MCP tools (Web Scraper, SERP, Web Unlocker, Scraping Browser) to reach sources that block bots. As a producer, ROGUE exposes its own MCP server. Try it now ,the dashboard has one-click "Add to Cursor / VS Code" buttons, and the hosted endpoint (rogue-api-mr5w.onrender.com/mcp) needs zero setup. Connect it and ask, from your own IDE, "what new attacks broke our support bot in the last 24 hours?" — live, during judging. The numbers are real, not a demo fixture. One live sweep: 8,321 breach trials across 6 deployment configs, a 16.5× vulnerability spread between weakest and strongest model. A separate judge scores every trial (REFUSED / EVADED / PARTIAL / FULL) and is calibrated against blind human labels, 98% breach-axis agreement, validated on WildGuardTest and StrongREJECT, not "trust the AI." Bright Data spend: $0.15 per detected breach. Publication-to-breach: ~2 minutes. It also red-teams multimodally, rendering text attacks as images and audio, because a jailbreak refused as text often succeeds as a picture of that text. Built solo in 6 days. Prior: GPTFuzz Grand Prize (Yonsei, 2024) and adversarial-ML research at AIM Intelligence.

SupplyPulse

SupplyPulse is an AI-powered delivery exposure platform for enterprise supply chain teams managing critical equipment deliveries across global suppliers, countries, and routes. The platform helps teams identify high-pressure deliveries, understand why they need attention, verify the external evidence behind the findings, and generate business-ready reports. For the demo, SupplyPulse is connected to the NorthBridge Energy Infrastructure workspace for the Singapore Data Center Phase 2 program. It analyzes equipment delivery records, planned need dates, forecast arrivals, source countries, destination countries, and external exposure queries. The user can ask one business question, and SupplyPulse runs an agent pipeline that checks schedule pressure, geopolitical issues, trade and tariff exposure, and route logistics concerns. Bright Data API is used to gather fresh external web evidence, a Source Quality Filter keeps useful sources, and Gemini reasons over the filtered evidence to generate summaries, recommendations, limitations, reports, and an audit trail. SupplyPulse turns static delivery tracking into an evidence-backed workflow for faster, more confident supply chain decisions.