Web Data Landscape
Web Agent sits across search, extraction, browser execution, data monitoring, and deep research. The market ranges from crawler infrastructure to AI-native DeepSearch.
Product patterns
| Pattern | Representative products | Strength | Fit |
|---|---|---|---|
| DeepSearch Agent | Parallel | Multi-hop research, structured facts, source validation | Deep research and autonomous web research |
| Independent search index | Brave | Low-latency search, independent index, privacy | Fast search and RAG summaries |
| Trend intelligence | MeetGlimpse | Trend discovery, prediction, marketing data | Brand, e-commerce, investment, and consulting |
| Proxy and scraping infra | Bright Data | IP pools, geo targeting, mature scraping | Large-scale compliant collection |
| API marketplace | RapidAPI | Third-party API aggregation and billing | Rapid API discovery and integration |
What Web Agent should pursue first
The first phase should prioritize AI-native data capability instead of becoming a heavy crawler platform:
- Search: fast, dense, citable search results for agents.
- Extract/Textify: webpage, PDF, and dynamic content to Markdown.
- Do/Track: controlled browser action and page change monitoring.
- Sandbox: isolated browser and file-processing runtime.
SAK differentiation
Web Agent differentiates by combining with other SAK modules:
- More accurate: GUM enables profile-aware query rewriting.
- Safer: GenAuth applies explicit identity and authorization boundaries.
- More controllable: Source and execution traces make search, extraction, and action reviewable.
- More engineered: Textify and Sandbox reduce browser/runtime maintenance work.
Product posture
Web Agent should be expressed as web action and data infrastructure for agents, not as a traditional crawler SDK.