Infrastruktur
Proxy-Routing, Browser-Ausführung, Wiederholungsversuche und Nutzungskontrollen sind operativer Aufwand.
Turn public web sources — search results, YouTube transcripts, Reddit discussions, and more — into normalized JSON your RAG pipeline can chunk, embed, and cite, without writing parsers.
Das Problem
Retrieval-augmented generation is only as good as the data you feed it. Scraping raw HTML for a knowledge base means brittle parsers, messy text, and stale content. Teams need clean, structured public web data they can chunk, embed, and refresh on a schedule.
Proxy-Routing, Browser-Ausführung, Wiederholungsversuche und Nutzungskontrollen sind operativer Aufwand.
Rohseiten müssen zu stabilen Datensätzen werden, bevor Produkte und Datenteams sie nutzen können.
Landingpages für Anwendungsfälle sollten sich direkt an Buyer-Workflows und internen Datenmodellen orientieren.
Workflows mit strukturierten öffentlichen Webdaten brauchen weiterhin klare rechtliche, datenschutzrechtliche und plattformseitige Grenzen.
Was du sammeln kannst
Example fields may include normalized text, titles, URLs, transcripts, and source metadata suitable for chunking and embedding.
Relevante Crawlora APIs
Starte auf der Plattformseite oder in der Endpunkt-Doku und teste dieselbe Route dann im Playground, bevor du sie produktiv integrierst.
Collect search results and snippets as retrieval sources.
ÖffnenPull video metadata and transcripts for grounding.
ÖffnenFetch a video's transcript by id for chunking and embedding.
ÖffnenSearch public posts and comment threads for community knowledge.
ÖffnenThe broader pattern for feeding agents structured public web data.
ÖffnenBeispiel-Workflow
Crawlora hält die Scraping-Ausführungsebene hinter dokumentierten APIs, damit sich dein Produkt auf Speicherung, Analyse, Alerts und Nutzer-Workflows konzentrieren kann.
01
Choose the search queries, videos, subreddits, or topics that should ground your model.
02
Call the relevant endpoints from a scheduler to gather clean text and metadata, not raw HTML.
03
Split content into chunks and keep source URL, title, and timestamp for citations.
04
Embed chunks into your vector store with the source metadata attached.
05
Serve grounded answers with citations and re-run collection to keep the index fresh.
API-Beispiel
Illustrative example using the documented YouTube transcript route. Check Docs for the current parameters and response fields.
GET https://api.crawlora.net/api/v1/youtube/transcript/dQw4w9WgXcQ
x-api-key: YOUR_API_KEY{
"code": 200,
"msg": "OK",
"data": [
{ "start": 0.0, "duration": 4.2, "text": "Welcome to the talk on retrieval pipelines" }
]
}Was du bauen kannst
Das sind praktische Workflow-Muster für SaaS-Produkte, Datenteams, KI-Agenten, Agenturen, Growth-Teams und interne Intelligence-Tools.
Build a retrieval index from search results and snippets for a topic.
Ground answers in YouTube transcripts for course, talk, or product content.
Index Reddit discussions to answer questions with real community context.
Re-collect sources on a schedule so the index does not go stale.
Give agents structured web data via documented endpoints or hosted MCP tools.
Keep source URLs and titles so generated answers can cite their sources.
Selbst bauen oder kaufen
Custom-Scraper funktionieren für Prototypen. Produktive Web-Data-Workflows brauchen Infrastruktur, Monitoring, stabilen Output und klares Fehlerverhalten.
| DIY-Ansatz | Crawlora-Ansatz |
|---|---|
| Scrape and parse raw HTML for each source | Receive normalized JSON text and metadata ready to chunk |
| Maintain parsers as pages and layouts change | Use documented endpoints with stable response shapes |
| Run proxies, browsers, and retries for collection | Managed execution behind the API |
| Build usage metering and refresh scheduling from scratch | Use API-key usage tracking and credit-based pricing |
Infrastruktur
Crawlora kombiniert plattformspezifische APIs mit verwaltetem Proxy-Routing, browserbasiertem Rendering, Wiederholungsversuchen, Rate Limits, Nutzungs-Tracking und Skalierungskontrollen.
Verantwortungsvolle Nutzung
Use public web data responsibly in RAG pipelines and comply with applicable laws, source terms, third-party rights, and copyright. Keep source attribution, avoid personal data, and do not republish content beyond fair use. Crawlora-Bedingungen lesen.
Verwandte Anwendungsfälle
Verlinke praktische Workflows, die oft dieselbe Dateninfrastruktur und dieselben Produkt-Buyer teilen.
FAQ
Antworten für Entwickler und Produktteams, die Crawlora für diesen Workflow evaluieren.
It is structured public web data — search results, transcripts, discussions — collected as normalized JSON so a retrieval-augmented generation pipeline can chunk, embed, and cite it.
Search results for breadth, YouTube transcripts for spoken content, and Reddit discussions for community knowledge, among other supported platforms.
Raw HTML is brittle and messy. Normalized JSON gives you clean text and metadata, so chunks embed better and citations are reliable.
Yes. Agents can call documented endpoints or Crawlora's hosted MCP tools to fetch grounding data at runtime.
Re-run collection on a schedule and re-embed changed content; cadence is up to your plan and responsible-use constraints.
Crawlora uses credit-based pricing per documented endpoint call. Estimate cost from the pricing page and endpoint docs.
Durchsuche die Crawlora APIs, teste einen Request im Playground und wechsle von Scraping-Infrastrukturarbeit zu produktiven Daten-Workflows.