Positioning: A service dedicated to providing high-quality, optimized information for large models
High-quality information retrieval and processing are fundamental to building large model and agent applications. Information Query Service (IQS) addresses key challenges for both end-users and developers. For end-users, it mitigates model hallucinations and fills knowledge gaps. For developers, it simplifies extracting and processing high-quality information.
As various agent frameworks like Openclaw, Cowork, and Coding emerge, they require skills such as web search and web parsing to expand their capabilities. IQS provides these skills to unlock the full potential of your agents.
Background and challenges
Challenge 1: Limited Knowledge
Providing high-quality, timely, authoritative, and highly credible information sources can greatly enhance the capabilities of large model applications.
Reliability: Large models are limited by their training data. They may hallucinate and provide incorrect answers to complex or specialized questions.
Timeliness: Large models are unaware of current events, such as breaking news and recent trends. This affects the timeliness of their responses.
Comprehensiveness: Training data often lacks long-tail knowledge and new concepts. This can result in incomplete answers or knowledge gaps.
Traceability: Responses lack source citations. This makes it difficult to determine the origin of the information or to verify how it was found.
Challenge 2: Out-of-the-box
Refined processing: Filter, extract, and process large volumes of data to lower the recognition costs of large models.
Engineering solutions such as query rewriting, post-retrieval processing, and information filtering improve retrieval quality and efficiency. These solutions are packaged into out-of-the-box, atomic capabilities to simplify application development and enable processing beyond raw data.
Core Advantages
Feature 1: Semantic search
This feature uses Qwen3-Embedding and Qwen3-Reranker to shift from simple matching to semantic understanding. It accurately captures paraphrases and context. A two-stage retrieval process with coarse and fine ranking improves the results.
Feature 2: Full-text rich text output
Five output modes are supported: short summary, long text, Markdown, rich text, and enhanced summary. The rich text mode supports Automatic Speech Recognition (ASR) for audio and video content and Optical Character Recognition (OCR) for images. The maximum output length is 12,000 characters, with a recall rate of over 98%.
Feature 3: Flexible search conditions
Customize precise searches for your enterprise. Prioritize results from seven major vertical industries, such as finance, law, and healthcare. Use allowlists and denylists for up to 100 domains. Filter results by time range and apply authoritative site scoring.
Feature 4: Extra-long queries & low latency
Supports extra-long queries of up to 500 characters, an end-to-end average latency of 500 ms (LiteAdvanced) / 950 ms (Generic), high concurrency for up to 1 million requests per day, and a Service Level Agreement (SLA) of 99.5% or higher.
Feature 5: High-quality results
Based on the ChineseSimpleQA and SimpleQA test sets, the overall performance and performance in six core scenarios are industry-leading. The results significantly outperform competing products such as Exa and Google.
Feature 6: ReadPage web parsing
The feature includes built-in web crawling and targeted indexing. It reduces HTML parsing latency by more than 1 second and avoids secondary queries. This design also reduces the need for URL whitelisting in the firewall and lowers security risks to your internal network.
Feature 7: Nearby information search
Integrates Amap location data to provide route planning, address searches, and location information for lifestyle services, such as hotels, restaurants, gas stations, and tourist attractions. This empowers agents for travel and transportation.
Feature 8: Flexible integration methods
Supports multiple integration methods, such as API-Http, API-SDK, MCP, and Skill. It also enables easy integration with mainstream agent platforms, including Dify, n8n, Model Studio, PAI, OpenClaw, Qoder, and Manus.
Scenarios
AI agent: Provides agents with real-time web access and supports web searches for task planning, information gathering, and autonomous decision-making.
OpenClaw agent: Integrates with the OpenClaw platform to provide powerful web search support for general-purpose agents.
DeepResearch: Supports agents for in-depth research. It automatically collects, organizes, and analyzes vast amounts of web information.
Intelligent customer service, investment research, and shopping assistants: Provides real-time data for agents in specific industries to improve the accuracy and professionalism of their responses.
Intelligent assistants on endpoint devices: Smartphone assistants, in-vehicle intelligent cockpits, and web queries for IoT devices.
Intelligent financial applications: Robo-advisors, investment research and analysis, real-time market data, and financial Q&A.
AI search and omniboxes: Intelligent search engines, information feeds, and code search for coding agents.
Functional architecture
