Enterprise Integrations – AI Meets Enterprise Infrastructure
After three days of optimizing for performance, accuracy, and efficiency, today we’re making The Web MCP accessible to the enterprise ecosystem. Enterprise Integrations are here.
The Problem: Enterprise AI is Stuck in Silos
Enterprises are racing to deploy AI agents, but they face a critical bottleneck: data access.
Your data science teams work in Databricks. Your analysts live in Snowflake. Your workflow automation runs on IBM WatsonX. Your developers prototype with Google’s ADK.
But all of these platforms are isolated from the live web. If you want to:
- Enrich customer records with LinkedIn data
- Monitor competitor pricing
- Track brand mentions across social media
- Pull real estate comps from Zillow
You need to build custom ETL pipelines, manage API keys, handle rate limits, and maintain scraping infrastructure. That’s weeks of engineering work before your AI agent can even start.
The Solution: Native Enterprise Integrations
We’ve built first-class integrations for the platforms that power enterprise AI.
Google Agent Developer Kit (ADK)
Google ADK is the framework for building production-grade AI agents with Gemini. With our integration, you can connect The Web MCP server directly to your ADK agents.
Use Cases:
- Customer research agents that pull LinkedIn profiles and company data
- E-commerce intelligence bots that monitor Amazon, Walmart, and eBay
- Market research assistants that aggregate social media sentiment
IBM watsonx Orchestrate
IBM watsonx Orchestrate is the enterprise workflow automation platform that brings AI into business processes. Our integration enables your workflows to access live web data at any step.
Use Cases:
- Sales automation: Enrich CRM records with LinkedIn data before outreach
- Competitive intelligence: Trigger alerts when competitor pricing changes
- Lead generation: Auto-populate prospect lists with verified contact information
Databricks
Databricks is the unified analytics platform for data science and machine learning. With our integration, you can pull web data directly into your notebooks and pipelines.
Use Cases:
- Training data collection: Scrape product catalogs for ML models
- Feature engineering: Enrich datasets with real-time web signals
- Market analysis: Aggregate pricing data across multiple e-commerce sites
- Social listening: Build sentiment models from social media data
Integration Features:
- Native Spark DataFrame support
- Batch data collection for large-scale analysis
- Automatic schema inference from web data sources
- Delta Lake integration for incremental updates
Snowflake
Snowflake is the cloud data platform trusted by enterprises for warehousing and analytics. Our integration brings web data into your Snowflake tables with zero ETL.
Use Cases:
- Customer 360: Enrich user tables with social media profiles
- Pricing analytics: Store historical competitor pricing for BI dashboards
- Lead scoring: Append company firmographic data from Crunchbase
- Real-time monitoring: Stream search engine results into Snowflake tables
Security and Compliance
Enterprise data requires enterprise security:
Authentication
- API tokens stored in platform-native secret managers (never in code)
- OAuth2 support for delegated access (coming Q2 2025)
- IP whitelisting for sensitive environments
Data Privacy
- Zero data retention: Bright Data doesn’t store scraped content
- GDPR compliant: All requests honor robots.txt and privacy regulations
- SOC 2 Type II certified infrastructure
These integrations join our existing ecosystem, including Strands and other enterprise tools. See our integrations documentation for the full list.
What’s Next?
Tomorrow (Day 5), we’re wrapping up Launch Week with evaluations and observability tools to help you measure and monitor your agent performance.
Until then, start building with these enterprise integrations.