Use QVeris to help AI agents discover, inspect, and call verified research capabilities for source discovery, public information lookup, webpage extraction, topic research, and structured briefs.
AI agents can summarize and reason, but useful web research workflows need access to external research capabilities. A web research agent may need to discover sources, inspect webpages, extract public information, compare multiple sources, summarize documents, and generate structured briefs.
QVeris gives agents one capability layer for discovering, inspecting, and calling relevant research capabilities without hardcoding every provider or relying on manual copy-paste between search tools, webpages, and documents.
How QVeris connects a research question to a structured brief through discoverable, inspectable capabilities.
Each node represents a capability type the agent can discover, inspect, and call through QVeris — not a fixed integration.
Four core challenges that make repeatable web research workflows difficult to build and scale.
Useful research often spans search results, webpages, public databases, documents, reports, product pages, and company information — each with its own access pattern.
Before executing a research capability, agents need to understand required inputs, response format, provider behavior, cost signals, and output limitations.
Searching, opening pages, copying text, comparing sources, and formatting briefs manually makes repeatable research workflows slow and inconsistent across teams.
AI-generated research outputs should be reviewed, verified, and checked against sources before publication or use in high-stakes decisions.
The agent searches QVeris for relevant capabilities such as web search, source discovery, webpage extraction, document summarization, company research, or structured summarization.
The agent inspects schema, required inputs, response format, cost signals, and provider information before execution — no blind calls to unknown research tools.
The agent calls selected capabilities and turns returned outputs into a structured research brief with key findings, source notes, open questions, and next steps.
A research tasks board showing how capabilities map to concrete actions across the Discover, Extract, and Structure phases.
Illustrative example of a research brief generated through QVeris capabilities. Not live research data or verified source content.
This is an illustrative example. It does not represent real search results, verified sources, or factual claims about any company or topic. Research outputs should be reviewed before publication or high-stakes use.
QVeris helps agents discover and call research capabilities, but outputs still need human judgment.
| Requirement | Manual web research | Hardcoded research tools | QVeris for web research agents |
|---|---|---|---|
| Source discovery | Users manually search, open, and compare sources | Developers choose fixed providers in advance | ✓Agents can discover relevant research capabilities based on the task |
| Workflow repeatability | Flexible but slow and inconsistent | Repeatable but limited to predefined integrations | ✓Reusable Discover, Inspect, Call pattern across research capabilities |
| Schema understanding | No structured schema for agent workflows | Developers maintain provider-specific documentation | ✓Agents inspect schema, parameters, and cost signals before execution |
| Research output | Often copied links, notes, and unstructured summaries | Structured only where integrations are designed | ✓Structured outputs can be routed into briefs, tables, dashboards, or workflows |
| Review and visibility | Hard to track what was used and when | Usage spread across provider dashboards | ✓Usage can be reviewed through QVeris usage history and credits ledger |
Users who need repeatable workflows for source discovery, public information lookup, and structured briefs — without manual copy-paste each cycle.
Teams researching categories, competitors, positioning, content topics, product opportunities, or public market context.
Developers building research assistants, knowledge workflows, source-aware dashboards, or agent-powered research products.
Teams collecting topic context, source ideas, competitor pages, SERP patterns, and research outlines for content planning.
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Use QVeris to give AI agents access to research capabilities for source discovery, public information lookup, webpage extraction, topic research, and structured briefs.
