Not found at this URL
https://www.ragie.ai/llms-full.txt ↗- Discovery
- Conventional sibling path checked
- HTTP response
- 404 · text/html; charset=utf-8
Data platforms · llms.txt file breakdown
Ragie llms.txt
A directly retrieved Markdown index for Ragie, organized into Docs (start here), Quick API landings, Product & positioning, Examples & starters.
The actual file
Source Markdown
The saved llms.txt text, displayed as source. The file belongs to its publisher; the live endpoint may change.
Complete saved Markdown shown below.
# Ragie
> Ragie is a fully managed RAG-as-a-Service platform for developers - covering ingestion, extraction, chunking, multi-index (vector/keyword/summary) indexing, and high-precision retrieval, with SDKs and APIs for rapid production use.
Important notes:
- Built for production: multi-tenant architecture; enterprise features; does not use your data for training.
- Core pipeline stages are: parsing -> extraction -> refinement -> chunking -> indexing -> retrieval.
- Best entry points for developers are the "Getting Started" guide and the API reference.
## Docs (start here)
- [Getting Started](https://docs.ragie.ai/docs/getting-started): Overview, quick setup, key concepts.
- [API Reference](https://docs.ragie.ai/reference): REST endpoints including Documents, Retrievals, Connectors, Partitions, Entities, Webhooks.
- [Tools & SDKs](https://docs.ragie.ai/docs/tools-and-sdks): Python & TypeScript clients and helpers.
- [Connectors](https://docs.ragie.ai/docs/connectors/overview): Native integrations (e.g., Google Drive, Confluence, Notion, Slack, etc.).
- [Webhooks](https://docs.ragie.ai/docs/advanced-features/webhooks): Event flow for monitoring & orchestration.
- [Rate Limits & Errors](https://docs.ragie.ai/docs/troubleshooting/rate-limits): Operational guidance for robust integrations.
## Quick API landings
- [Create Document](https://docs.ragie.ai/reference/createdocument): Ingest; statuses progress through `pending -> ... -> ready`.
- [Retrieve](https://docs.ragie.ai/reference/retrieve): Semantic retrieval with options like rerank and metadata filtering.
- [Connections API](https://docs.ragie.ai/reference/list-connections): Manage connectors and trigger sync.
- [Partitions](https://docs.ragie.ai/reference/list-partitions): Multi-tenant or logical isolation for scoped retrieval.
## Product & positioning
- [Homepage](https://www.ragie.ai/): What Ragie is, pipeline highlights, and links to SDKs/docs.
- [Pricing](https://www.ragie.ai/pricing): Plan tiers and usage pricing for pages, audio/video, storage, connectors.
- Security & Compliance: "Ragie does not use your data for training" and enterprise compliance language are stated on the homepage. Contact support for Trust Center access.
## Examples & starters
- SDK snippets (TS, Python, cURL) are embedded on the homepage and docs; GitHub houses open-source tools/examples.
- [Homepage SDK snippets](https://www.ragie.ai/)
- [GitHub (Ragie org/examples)](https://docs.ragie.ai/docs/getting-started#more-resources) -> links to GitHub/Discord.
## Optional
- [Blog](https://www.ragie.ai/blog): Product updates and technical deep dives.
- [Benchmarks](https://www.ragie.ai/benchmarks): Retrieval quality/performance highlights.
- [Base Chat](https://www.ragie.ai/base-chat): Chat with your company knowledge base use case.
- [Integrations overview](https://www.ragie.ai/#connectors): Visual overview of connectors on marketing pages.
Measured from the saved file
Linked document
- UTF-8 text size
- 2.9 KB2931 bytes
- Token count
- 692o200k_base encoding
- Markdown links
- 1817 distinct URLs
- Fenced code blocks
- 038 lines in the file
Size measures the captured UTF-8 text, not compressed transfer size. Tokens are counted with a named tokenizer; other models can count differently. Neither measure establishes context compatibility or answer quality.
- Project H1
- Ragie
Opening blockquote
Ragie is a fully managed RAG-as-a-Service platform for developers - covering ingestion, extraction, chunking, multi-index (vector/keyword/summary) indexing, and high-precision retrieval, with SDKs and APIs for rapid production use.
Context architecture
How the content is divided
5 H2 sections organize 18 parsed Markdown links. 0 links point to .md or .markdown paths; 11 link occurrences use another hostname. Linked destinations have not been recursively validated.
| H2 section | Links | UTF-8 bytes | Tokens |
|---|---|---|---|
| Docs (start here)Line 10 | 6 | 728 | 182 |
| Quick API landingsLine 18 | 4 | 483 | 105 |
| Product & positioningLine 24 | 2 | 388 | 91 |
| Examples & startersLine 29 | 2 | 289 | 81 |
| OptionalLine 34 · Optional | 4 | 376 | 91 |
Link counts exclude parsed fenced and inline code and resolve relative destinations against the final endpoint. Section sizes cover the text below each H2 until the next H2.
Embedded material
Code, installation and API examples
- Fenced blocks
- 0 closed
- Declared languages
- No fenced blocks detected
- Package-install commands
- 0 detected in fenced or inline code
- Authentication examples
- 0 fenced lines match API-key, Authorization, Bearer, OAuth or access-token patterns
- HTTP request examples
- 0 fenced lines match request-method patterns
- Authentication links
- 0 links have authentication-related labels
Embedded example text and links to further documentation are counted separately. A code block does not establish that a sample runs or that an authentication flow succeeds.
Publisher prioritization
The Optional section
1 H2 section named “Optional” contain 4 parsed links. 14 links sit outside those sections. That puts 22.2% of the file’s parsed links under Optional.
The community proposal uses Optional by convention for secondary links that can be skipped for a shorter context. This label does not establish that everything outside it is critical, or that the material inside it is deprecated.
Machine-readable routes
MCP references and configuration text
No MCP or Model Context Protocol term was detected in the captured file. 0 links have MCP-related labels or paths. 0 fenced lines match mcpServers, mcp_servers or an mcp add command.
These are text and link observations. No MCP server connection, authentication or tool call was tested.
Index and bundle
llms-full.txt companion
Not found at checked URLs
A verified text response establishes a companion at the checked URL. It does not prove the bundle contains all product documentation, that generation is automated, or that it fits an assistant’s context window.
Change evidence
What can be said about freshness
This capture establishes a baseline. Update frequency cannot be determined from one observation.
File changes can reveal documentation edits or navigation changes. They do not by themselves measure product release velocity, accuracy, agent adoption or AI visibility.
Capture identity and measurement method
- Requested endpoint
- https://ragie.ai/llms.txt
- Final endpoint
- https://www.ragie.ai/llms.txt
- HTTP status
- 200
- Content type
- text/plain; charset=utf-8
- Text retrieval
- Firecrawl literal text capture
- Tokenizer
- tiktoken 0.14.0 · o200k_base
- SHA-256 of saved UTF-8 text
1f4cf008daf5e26dfc11f63a8606341f179da3512a3df359aff00abe8784d350
Counts use a deterministic parser, not a spec-compliance grade. Unusual Markdown and indented code can fall outside its recognized patterns. See the llms.txt proposal and tokenizer implementation.