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Arlong
$3/mStarting price
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About Arlong
Arlong provides search infrastructure designed to prepare the web for reasoning by AI systems and people. It helps users decide what is worth reading before untrusted or expensive web content enters a context window. The tool structures search output so agents can select sources before incurring the cost of reading full pages. Potentially unsafe or instruction-shaped content is assessed upstream, preventing it from entering model workflows. Arlong emphasizes inspectability, preserving sources and traces so answers can be verified rather than merely trusted. The system treats useful retrieval as a decision process, completing a request only when the right evidence reaches the right consumer at the right cost. It supports independent analysis by isolating claims that require corroboration and providing primary documentation with current release notes.
Key features
- Evidence-first search output
- Upstream content screening
- Source preservation and traceability
- Cost-aware retrieval decisions
- Independent claim analysis
- Primary documentation access
- Release notes tracking
- Agent-ready structured data
Use cases
- Pre-screening web content for AI agents
- Verifying claims with preserved sources
- Reducing context window costs by filtering content
Pros
- Structures search output for pre-reading selection
- Screens unsafe or instruction-shaped content upstream
- Preserves sources and traces for inspectability
- Reduces costs by avoiding full-page reads
- Supports independent analysis of claims
Cons
- No free tier or pricing details provided
- Limited to web-based use cases
- Requires integration with existing systems
Frequently asked questions about Arlong
What does Arlong do?
Arlong provides secure web retrieval for AI agents by searching the live web, isolating hostile instructions, and returning a contract-complete evidence set with claim-level citations. It structures search output to help users decide what is worth reading before untrusted or expensive web content enters a context window.
Who is Arlong designed for?
Arlong is designed for AI agents and systems that require reliable, inspectable, and secure evidence from the web. It suits users who need to verify claims, avoid unsafe content, and ensure evidence meets specific contractual requirements before ingestion.
How does Arlong ensure security for AI workflows?
Arlong scans raw HTML and concealed instructions before model ingestion, isolating hostile page content and prompt injection signals. It prevents unsafe or instruction-shaped content from entering AI workflows, ensuring only verified evidence is processed.
What is an Answer Contract in Arlong?
An Answer Contract defines the evidence required for a request, including entities, fields, constraints, freshness, and verification obligations. Arlong uses this contract to compile a measurable set of evidence that satisfies the entire request while identifying missing requirements.
Does Arlong support inspectability of search results?
Yes, Arlong is designed to be inspectable by providing the Answer Contract, safe evidence atoms, contract coverage, independent-source counts, missing requirements, and each source's marginal contribution in its responses.
How does Arlong handle redundant or copied claims?
Arlong maximizes marginal evidence by prioritizing useful, independent sources over redundant or copied claims. Pages that do not contribute new evidence lose value, even if they are popular, ensuring only distinct and reliable sources are included.
