Scry is an AI-powered tool designed to help professionals perform deep, programmatic research across the public web. It enables structured queries over fixed datasets—such as archives of Reddit posts, arXiv papers, Hacker News comments, and more—via SQL-like programs, allowing business users and organizations to search not just documents but aggregated patterns, trends, and relationships. It solves the common problem of piecing together fragmented public evidence manually by allowing agents like ChatGPT or Claude to tap into Scry’s searchable data engines in a single query.
Key Features
Programmatic Search & Turing-Complete Queries: Users can write recursive SQL and fixpoint programs—capable of joins, conditionals, aggregations, and graph walks—that operate across large corpora. These queries are resource-bounded (by time and compute), but the system gives control over budgets and deadlines. Answers are computed over the full matching population rather than paged results.
Wide Public Corpus with Provenance & Freshness Metadata: Scry indexes large public collections (Reddit, Hacker News, arXiv, etc.), each with measured coverage, sources, timestamps, authors, and indicators of how up-to-date the data is. The live schema reveals what each data source contains and where gaps or delays may exist.
Agent & API Integration: Scry can be added to assistants like ChatGPT and Claude through custom connectors, or used via its HTTP API. Users receive query results and provenance directly in the agent interface.
Web Search + Vector Reranking: It supports web search requests via configured providers (e.g., Google or custom sources), as well as reranking of documents already retrieved using embeddings, relevance models, or instructions.
Usage Metering & Bounded Execution: Each query or agent invocation is metered by factors like declared time, compute resource usage, or document size. Users see exactly what is run (“burden”) and what they are charged for. The tool also supports non-commercial free use under certain conditions.
Pricing
Researcher plan: Free. Includes API access, agent support via the MCP protocol, $5 of credit at signup, no credit card required; intended for non-commercial use.
Patron plan: $100 per month. Provides a monthly balance that rolls over; still for non-commercial use.
Team plan: From $2,000 per month. Geared toward commercial users; offers dedicated capacity and custom source integrations.
Agents: $0.05 per second declared usage, applicable when executing agent workflows without an account.
Who is it for?
Scry is suited for business decision-makers, researchers, analysts, and media or policy professionals who need high-fidelity insights drawn from public data. Specifically:
Market and Competitive Intelligence Teams can use Scry to analyze discourse around competitors, product sentiment, or technology trends by traversing forums, news sources, and academic papers with precision.
Regulatory, Legal, or Policy Professionals who must gather evidence or arguments over regulatory filings, research articles, public comments, or social media posts. They benefit from its provenance features and transparency.
Academic or R&D Departments needing to detect prior work, citation networks, or emergent research themes by walking graph or citation relations.
Small consultancies or enterprise teams with needs for scalable, commercial-grade web research who can invest in the Team plan to use custom sources or dedicated infrastructure.
Final thoughts
Scry stands out for its transparency, rigorous control over query behavior, and ability to compute structured insights across large public corpora rather than simply retrieving documents. While its metering model and requirements for understanding query logic may pose a learning curve, especially for those accustomed to simple keyword searches, its strength lies in rigor and reproducibility. For businesses and professionals who value credible, verifiable research and want to move from anecdote to evidence, Scry offers a strong option—but it’s less suitable for casual or marketing-driven use where simpler tools suffice.
Visit the official website for more.
Keep up to date with our stories on LinkedIn, Twitter, Facebook and Instagram.
Scry is an AI-powered tool designed to help professionals perform deep, programmatic research across the public web. It enables structured queries over fixed datasets—such as archives of Reddit posts, arXiv papers, Hacker News comments, and more—via SQL-like programs, allowing business users and organizations to search not just documents but aggregated patterns, trends, and relationships. It solves the common problem of piecing together fragmented public evidence manually by allowing agents like ChatGPT or Claude to tap into Scry’s searchable data engines in a single query.
Key Features
Programmatic Search & Turing-Complete Queries: Users can write recursive SQL and fixpoint programs—capable of joins, conditionals, aggregations, and graph walks—that operate across large corpora. These queries are resource-bounded (by time and compute), but the system gives control over budgets and deadlines. Answers are computed over the full matching population rather than paged results.
Wide Public Corpus with Provenance & Freshness Metadata: Scry indexes large public collections (Reddit, Hacker News, arXiv, etc.), each with measured coverage, sources, timestamps, authors, and indicators of how up-to-date the data is. The live schema reveals what each data source contains and where gaps or delays may exist.
Agent & API Integration: Scry can be added to assistants like ChatGPT and Claude through custom connectors, or used via its HTTP API. Users receive query results and provenance directly in the agent interface.
Web Search + Vector Reranking: It supports web search requests via configured providers (e.g., Google or custom sources), as well as reranking of documents already retrieved using embeddings, relevance models, or instructions.
Usage Metering & Bounded Execution: Each query or agent invocation is metered by factors like declared time, compute resource usage, or document size. Users see exactly what is run (“burden”) and what they are charged for. The tool also supports non-commercial free use under certain conditions.
Pricing
Researcher plan: Free. Includes API access, agent support via the MCP protocol, $5 of credit at signup, no credit card required; intended for non-commercial use.
Patron plan: $100 per month. Provides a monthly balance that rolls over; still for non-commercial use.
Team plan: From $2,000 per month. Geared toward commercial users; offers dedicated capacity and custom source integrations.
Agents: $0.05 per second declared usage, applicable when executing agent workflows without an account.
Who is it for?
Scry is suited for business decision-makers, researchers, analysts, and media or policy professionals who need high-fidelity insights drawn from public data. Specifically:
Market and Competitive Intelligence Teams can use Scry to analyze discourse around competitors, product sentiment, or technology trends by traversing forums, news sources, and academic papers with precision.
Regulatory, Legal, or Policy Professionals who must gather evidence or arguments over regulatory filings, research articles, public comments, or social media posts. They benefit from its provenance features and transparency.
Academic or R&D Departments needing to detect prior work, citation networks, or emergent research themes by walking graph or citation relations.
Small consultancies or enterprise teams with needs for scalable, commercial-grade web research who can invest in the Team plan to use custom sources or dedicated infrastructure.
Final thoughts
Scry stands out for its transparency, rigorous control over query behavior, and ability to compute structured insights across large public corpora rather than simply retrieving documents. While its metering model and requirements for understanding query logic may pose a learning curve, especially for those accustomed to simple keyword searches, its strength lies in rigor and reproducibility. For businesses and professionals who value credible, verifiable research and want to move from anecdote to evidence, Scry offers a strong option—but it’s less suitable for casual or marketing-driven use where simpler tools suffice.
Visit the official website for more.
Keep up to date with our stories on LinkedIn, Twitter, Facebook and Instagram.
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