JSON Schema App
JSON Schema App is a no-code structured data automation platform designed to improve Google rankings, rich results eligibility, and AI visibility. The app automatically detects page types and applies the correct JSON-LD schema across your website, including product, FAQ, article, organization, and breadcrumb markup. It continuously monitors for errors, duplicate schema, and compliance issues to keep your structured data search-ready. By providing clean, machine-readable signals, it helps search engines and AI systems clearly understand your content. This increases your chances of earning rich snippets, appearing in AI-generated answers, and strengthening entity recognition in search. Built for businesses, ecommerce stores, and content-driven websites, JSON Schema App simplifies technical SEO without requiring coding knowledge.
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Crawleo
Crawleo is a privacy-first real-time web search and crawling API for AI applications. It lets developers search the live web, crawl specific URLs, and extract clean AI-ready content through simple API endpoints. The Search API returns structured web results and can optionally auto-crawl result pages. The Crawler API lets users crawl one or multiple URLs directly. Crawleo supports outputs such as Markdown, plain text, cleaned HTML, and raw HTML, making the data easy to use in LLM prompts, RAG pipelines, AI agents, automation workflows, research tools, and internal dashboards. It also supports REST API access, MCP integration for AI assistants and IDEs, and LangChain tools for agentic and RAG-based applications.
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Jockey
Jockey is a unified video intelligence agent that reasons across collections of videos and images, turning raw media into something users can search, question, organize, and act on through natural-language instructions. It automatically processes visual, audio, motion, speech, text, and contextual signals without requiring users to choose individual modalities. Teams can ask for a person, place, object, logo, quote, scene, action, topic, sentiment, or moment and receive ranked results linked to frame-accurate timestamps. Jockey can summarize themes and patterns across a knowledge store, explain why results match, extract entities, categorize content, track a subject across multiple videos, reconstruct timelines, and assemble matching moments into highlight reels. Multi-turn sessions preserve conversational context for follow-up requests, while structured output returns timestamped, machine-readable metadata according to a defined JSON schema.
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Parallel
The Parallel Search API is a web-search tool engineered specifically for AI agents, designed from the ground up to provide the most information-dense, token-efficient context for large-language models and automated workflows. Unlike traditional search engines optimized for human browsing, this API supports declarative semantic objectives, allowing agents to specify what they want rather than merely keywords. It returns ranked URLs and compressed excerpts tailored for model context windows, enabling higher accuracy, fewer search steps, and lower token cost per result. Its infrastructure includes a proprietary crawler, live-index updates, freshness policies, domain-filtering controls, and SOC 2 Type 2 security compliance. The API is built to fit seamlessly within agent workflows: developers can control parameters like maximum characters per result, select custom processors, adjust output size, and orchestrate retrieval directly into AI reasoning pipelines.
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