Finance Capability Routing

Finance AI Agent Tools, Routed Through QVeris

QVeris helps AI agents discover, inspect, and call verified finance-related tools, APIs, live data, and external services through one unified capability routing layer. Not a single API. Not a static directory. An agent-native routing network built for finance workflows.

QVeris finance capability routing network connecting Market Data, Research, Compliance, Crypto, Alt Data, and Macro data sources through one unified protocol

Why QVeris for finance AI agents

QVeris is not a single finance API, a generic marketplace, or a static directory. It is an agent-native capability routing layer purpose-built for how AI agents discover and use financial data.

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Agent-native discovery

Agents describe what finance data they need in natural language. QVeris returns ranked, verified matches — no pre-coded endpoints, no hardcoded provider logic.

Verified finance capabilities

Every capability includes quality signals — success rate, average latency, and estimated cost. Agents inspect before committing. Zero-cost decision-making.

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Unified routing layer

One API key. One protocol. Market data, research, compliance, crypto, macro, and alt signals all routed through the same discover-inspect-call workflow.

Production-ready execution

Sandboxed runtime, structured JSON responses, unique execution IDs, and full session tracing. Built for teams running finance agents in production.

Finance capability categories

QVeris provides verified access across six finance domains. Each category includes capabilities sourced from multiple providers, with transparent quality metrics.

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Market data & price intelligence

Access verified capabilities for equities, FX, commodities, and index data. Built for quantitative workflows, trading agents, and market monitoring systems.

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Investment research

Earnings data, analyst consensus, valuation models, and fundamentals. Give your research agent a complete data foundation for company and sector analysis.

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Macro & fixed income

Interest rates, yield curves, inflation data, and macroeconomic indicators. Support for fixed income analysis and top-down research workflows.

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Risk & compliance

KYC verification, sanctions screening, regulatory data. Full audit trail for every call — built for compliance-aware workflows.

Crypto & on-chain data

Blockchain data, DeFi metrics, stablecoin flows, and on-chain signals. Access blockchain data and on-chain metrics for cross-asset workflows.

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Alternative data & signals

News sentiment, social media analytics, event-driven indicators, and macroeconomic surprise data. Go beyond standard datasets for alpha generation.

See Pricing

Discover. Inspect. Call. — for finance workflows

Three steps. Discovery and inspection are always free. You only spend credits when your agent makes a call.

Finance agent workflow: Discover finance capabilities through natural language, Inspect schemas and costs before committing, Call with structured execution and audit trail
Always Free
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Discover finance capabilities

Your agent describes the finance data it needs — "today's S&P 500 movers" or "KYC check on this entity" — and QVeris returns ranked, verified matches with cost, latency, and success rate. No hardcoded endpoints needed.

Always Free
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Inspect before committing

Review the full parameter schema, billing rules, provider information, and quality metrics of any finance capability before your agent commits. Zero-cost decision-making with full transparency.

Credits-Based
Call with structured execution

Execute through a sandboxed environment. Structured JSON response with execution ID, billing details, and credit balance — fully auditable and ready for downstream finance workflows.

Finance use cases

From stock research agents to compliance automation, QVeris powers the tool-calling layer behind production finance AI agents.

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Stock research AI agents

Give equity research agents on-demand access to market data, fundamentals, and earnings data through one unified API. Agents discover the right data source dynamically.

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Investment research automation

Automate earnings analysis, peer comparison, and macro research. Agents discover and call the right data sources as research questions evolve — no pre-wired integrations.

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Market intelligence workflows

Power market monitoring agents with real-time data, sentiment signals, and cross-asset intelligence. Combine traditional and alternative data through one protocol.

Risk & compliance monitoring

Embed KYC, sanctions screening, and regulatory checks into agent workflows. Full audit trail with execution IDs for every compliance-related call.

Crypto & on-chain analysis

Build agents that monitor DeFi metrics, track stablecoin flows, and analyze wallet activity. Cross-asset workflows spanning crypto and traditional markets.

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Finance-enabled SaaS agents

Ship AI-native finance products where agents dynamically discover and call finance capabilities at runtime. Outsource the tool-integration layer to QVeris.

How QVeris compares

QVeris sits at a different layer of the finance data stack. Here is how it relates to other approaches.

Capability QVeris Manual Finance API Integration Generic API Marketplace Static Tool Directory
Agent-native discovery Natural language, dynamic Must pre-code each endpoint Keyword search, human-driven Browse by category
Cost & quality preview Cost, latency, success rate before calling No preview — call and see Pricing page, not programmatic Not available
Unified protocol One API for all finance capabilities N different APIs, auth, schemas Aggregated, limited depth No protocol — links only
Provider transparency Full provider visibility per capability Full visibility Often opaque Listed but unverified
Structured execution Sandboxed, JSON, execution ID, audit trail Direct call, provider-dependent Varies by provider None
Finance capability breadth 6 domains, 10,000+ capabilities Limited to integrated APIs Broad but shallow Listings only
MCP server support Native MCP server None None None

Integration options

QVeris meets your finance agent where it runs. All integration methods provide access to the same verified finance capabilities.

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MCP Server

Native Model Context Protocol support. If your agent speaks MCP — Claude Code, Cursor, and others — QVeris appears as an MCP server with 10,000+ discoverable finance tools.

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Python SDK

Typed client library with automatic retry, session management, and async support. Install in one command and start discovering finance capabilities from Python agents.

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REST API

Standard HTTP interface. Three endpoints: discover, inspect, call. Works from any language, any runtime. Finance data access without framework lock-in.

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CLI

Terminal-native workflow for scripting, CI/CD, and local development. Discover, inspect, and call finance capabilities without leaving the command line.

Built for production finance workflows

QVeris is designed for teams running finance agents in production — not just prototyping.

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Structured execution

Every finance capability call executes in a sandboxed environment with structured JSON output, full parameter validation, and consistent response schemas your agent can parse reliably.

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Auditability

Every call produces a unique execution ID linked to a search session and agent session. Full trace from intent to result — built for debugging, compliance, and cost analysis in finance workflows.

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Observability

Monitor success rates, execution latency, and credit consumption per capability, per session, and per agent. Make data-driven decisions about which finance capabilities your agents depend on.

Where to go from here

This page covers QVeris finance capabilities. Explore related product pages to learn more or contact us to discuss your team's finance AI agent needs.

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Platform Overview

See the full QVeris capability routing network and how it connects AI agents to verified real-world tools.

Explore Platform →

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Pricing

Understand QVeris plans, credit packages, and how pricing scales with your team's finance capability usage.

View Pricing →

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All Capabilities

Browse all 15+ capability categories beyond finance, including developer tools, document processing, and more.

Browse Capabilities →

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Contact QVeris

Discuss your team's finance AI agent requirements, enterprise needs, or custom capability access with our team.

Contact Us →

Frequently asked questions

What are finance AI agent tools?
Finance AI agent tools are verified capabilities that AI agents can discover, inspect, and call to access financial data and execute finance workflows. These include market data, investment research, risk and compliance data, crypto and on-chain data, macro indicators, and alternative signals. QVeris provides these through a unified capability routing network rather than requiring agents to integrate with each financial data source individually.
How does QVeris help finance AI agents?
QVeris acts as a capability routing layer between AI agents and financial data sources. Agents describe what finance data or capability they need in natural language, QVeris discovers matching verified tools, the agent can inspect schemas and costs before committing, and then calls the selected capability with structured parameters. This replaces manual per-API integration with a unified discover-inspect-call workflow across all finance capability categories.
Is QVeris a financial data provider?
No. QVeris is not a financial data provider. It is a capability routing network that connects AI agents to verified finance tools, APIs, and data sources from multiple providers through one unified protocol. QVeris handles discovery, inspection, routing, structured execution, and auditability — but the underlying data and capabilities come from a range of verified third-party sources. QVeris makes it easy for agents to find and use finance capabilities without managing each provider separately.
How is QVeris different from a finance API marketplace?
Unlike a finance API marketplace where developers manually search, read documentation, and integrate each API separately, QVeris is agent-native. AI agents discover finance capabilities using natural language, inspect costs and quality metrics before calling, and execute through one unified API. QVeris also provides structured execution with audit trails, execution IDs, and session tracing — capabilities not offered by standard API marketplaces that are designed for human developers rather than AI agents.
Can QVeris support investment research workflows?
Yes. QVeris supports investment research workflows by giving AI agents access to verified capabilities for earnings data, analyst consensus, valuation models, fundamentals, and market intelligence. Agents can discover and call the right data sources dynamically as research questions evolve, with structured JSON responses suitable for downstream analysis, modeling, and reporting.
Can QVeris support risk and compliance workflows?
Yes. QVeris includes verified capabilities for KYC verification, sanctions screening, regulatory data. Every compliance-related call produces a unique execution ID linked to a search session and agent session, providing a full audit trail suitable for compliance-aware environments. Enterprise plans add advanced RBAC. Enterprise options may include dedicated support, custom integrations, volume discounts, and custom SLAs.
Does QVeris support crypto and on-chain data workflows?
Yes. QVeris offers verified capabilities for blockchain data, DeFi metrics, stablecoin flows, and on-chain signals with access to blockchain data and on-chain metrics. AI agents can discover and call these capabilities through the same unified protocol used for traditional financial data, enabling cross-asset workflows that span both crypto and traditional markets in a single agent session.
How do AI agents call finance capabilities through QVeris?
AI agents call finance capabilities through QVeris in three steps: Discover — the agent describes what it needs in natural language ("today's sector ETF flows" or "earnings surprise for this ticker") and QVeris returns ranked capability matches with cost, latency, and success rate. Inspect — the agent reviews the full parameter schema, billing rules, and quality metrics at zero cost before committing. Call — the agent submits structured parameters and QVeris executes in a sandboxed environment, returning structured JSON with a unique execution ID, billing details, and remaining credit balance.
Does QVeris support MCP, CLI, Python SDK, or REST API?
Yes. QVeris provides multiple integration options that all provide access to the same finance capabilities: a native MCP server for Model Context Protocol compatible agents, a CLI for terminal-native scripting and CI/CD workflows, a Python SDK with typed client, async support, and auto-retry, and a standard REST API at api.qveris.ai/v1. Pricing is based on capability calls, not which interface your agent uses.
How can a team get access to QVeris finance capabilities?
Teams can start with a free QVeris account that includes 1,000 credits on signup plus 100 daily credits. The Pro plan at $19/month provides 10,000 credits and access to all 10,000+ verified capabilities including full finance domain coverage. Scale On-Demand credit packages are available from $1 with volume bonuses. For enterprise teams needing dedicated support, custom integrations, volume discounts, or custom SLAs, contact QVeris sales to discuss an Enterprise plan tailored to your finance workflows.