Business teams ask questions from whichever AI they already use — Claude via MCP, Gemini via A2A, Slack, or any AI assistant. Nodal's trust layer intercepts the request and checks it against your organization's verified query library.
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Nodal maps questions to verified query templates built from your existing dashboards, notebooks, and SQL. This is your organization's verified query library — the encoded institutional knowledge of how your business measures itself. The answer is consistent whether asked Monday or Friday, in Claude, Gemini, Codex, or Snowflake Cortex, because it comes from the same verified source.
When a question is ambiguous or genuinely new, the trust layer routes it to your data team with full context — not a blank email thread. This is the governance model: analysts review, verify, and approve. The verified answer then becomes part of the query library, available to every AI platform in your organization.
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Every question your team asks, every answer your analysts validate, every caveat they add — all of it grows the verified query library. Over time, more questions resolve instantly and fewer require analyst time.
A company using Nodal for a year has a verified query library that reflects a year of real business questions and real analyst decisions. That asset is yours — portable across any AI platform.
Nodal is built on open protocols — MCP for Claude, A2A for Gemini, API for Codex, plus Snowflake Cortex and Databricks Genie, with more coming. Connect the trust layer once and every current and future AI agent your organization uses gets access to your verified query library. As the AI landscape shifts, your institutional knowledge stays portable, governed, and protocol-native.
A business user asks "How does NRR compare between APAC and LATAM?" in Gemini. Nodal retrieves a verified query from a trusted dashboard — the same logic your analysts already use — and returns an answer in seconds.
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The same question asked through Claude Code with only a Snowflake MCP connection. The AI spends dozens of tool calls discovering tables, guessing at schema, and generating SQL — with no guarantee the result matches how your organization defines the metric.
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The trust layer gives Claude Code access to your verified queries. Instead of spending dozens of tool calls exploring your schema, it retrieves the right query in milliseconds and builds from there.
Without the trust layer, Claude Code connects directly to Snowflake and starts from zero — discovering tables, inspecting columns, guessing at joins. Slower, more expensive, and the results may not match your team's definitions.