Ad-Hoc Analytics Answerer Agent

Turn plain-English data questions into sourced answers with a chart, a narrative, and the exact query in minutes.

Updated Jun 23, 2026

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The problem it solves

Routine data questions pile up in the BizOps queue while people wait days for a number they need now. This agent watches your team's question channel, writes and runs read-only queries against your warehouse using your own metric definitions, and replies with a sourced answer, a chart, and the exact SQL, so analysts stop fielding repetitive requests and answers arrive in minutes.

Who it's for

BizOps and analytics teams drowning in ad-hoc requests
Data and analytics engineers who own the warehouse
Founders and operators at data-driven SaaS, fintech, and e-commerce companies
RevOps and finance teams that need numbers on demand
Any company with a Snowflake, BigQuery, Postgres, or Redshift warehouse

What it does

1
Watch the question channel
The agent monitors the Slack channel where your team asks data questions in plain English.
2
Interpret against your definitions
It restates the question and resolves every metric, filter, and time window against your real metric definitions and business rules instead of generic ones.
3
Find the right tables
It identifies the minimum set of tables and join keys from your schema, preferring the semantic layer or modeled tables over raw source tables.
4
Write a read-only query
It writes a deterministic, reproducible SELECT statement in your warehouse's SQL dialect, applying every business rule and respecting your row limit and cost cap.
5
Run and join the data
It executes the query through a read-only role and joins results across sources, including a small CRM pull when a question needs it.
6
Build the right chart
It picks the appropriate visualization for the question, builds it in your BI tool or renders it inline, and labels axes, units, and date range.
7
Reply with a sourced answer
It posts a headline number, the chart, how it got there, assumptions and caveats, and the exact SQL it ran.
8
Log the question
It appends each answered question, query, and row count to a log, building a reusable library and an audit trail.

Key benefits

Routine questions answered in minutes instead of waiting in the BizOps queue
Every answer is auditable and reproducible, with the exact query attached
Uses your metric definitions, so a number means what your team means by it
Read-only by design, so it can never write to or change your warehouse
Assumptions and caveats spelled out on every answer, so you can trust or check it
Guardrails on row limits and cost keep queries from running up your warehouse bill

Sample use cases

A sales leader asks in Slack how many net-new logos closed last quarter by region.

The agent confirms the exact date range, queries the right tables read-only, and replies with a bar chart, the regional breakdown, and the SQL it ran.

Finance needs MRR churn for May before a board update.

The agent applies your churn definition, drops deals with null close dates, flags that May is partial through the 28th, and returns a big-number callout with prior-period comparison.

An operator asks for the top 10 accounts by usage this week.

The agent excludes test accounts per your business rules, runs an aggregated query within the cost cap, and posts a ranked chart plus the caveats.

Someone asks a question using an undefined metric.

Instead of guessing, the agent stops and asks one specific clarifying question so the answer is correct the first time.

Key integrations

Snowflake
Cloud data warehouse the agent queries through a read-only role.
BigQuery
Google's data warehouse, connected read-only as a query target.
PostgreSQL
Relational database the agent can query read-only for analytics.
Amazon Redshift
Cloud data warehouse supported as a read-only query target.
Slack
Where people ask questions in plain English and receive the sourced answers and charts.
Looker
Optional BI tool for building and linking charts instead of rendering them inline.
Tableau
Optional BI tool the agent can build or link visualizations in.
Metabase
Optional open-source BI tool for charting query results.
Mode
Optional analytics and BI platform for building shared charts.
Salesforce
Optional CRM the agent pulls fields from when a question needs CRM data.
HubSpot
Optional CRM source for questions that span warehouse and pipeline data.

Ad-hoc questions are where analytics teams quietly lose the most time: each one is small, but the steady stream of "what was churn in May" and "top accounts by usage this week" never stops. This agent handles that long tail directly in the channel where people already ask, so a sourced answer arrives in minutes and the BizOps queue stays clear for the work that actually needs a human.

Because it answers using your own definitions of customer, active, and revenue, and attaches the exact query and caveats to every reply, the results are trustworthy and reproducible. It pairs naturally with the business intelligence dashboard software you already run: dashboards cover the standing metrics, and the agent fields the one-off questions no dashboard anticipated.

Getting started

Import the workspace — Add the Ad-Hoc Analytics Answerer template into Gamut to get the agent and its onboarding skill.
Run the onboarding skill — The agent-onboarding skill launches automatically and asks for your warehouse and read-only role, known tables or schema doc, metric definitions, default date grain, question channel, and guardrails.
Give it a first task — Ask a real question in dry-run mode so the agent tells you which tables and joins it would use and the exact query, and confirm before it executes.

Frequently asked questions

Will the agent run queries or take action without my approval?

It only ever runs read-only SELECT queries, never writes or DDL, and you can start it in a dry-run mode where it proposes the tables, joins, and exact SQL for you to confirm before anything executes. It also asks one clarifying question rather than guessing when a metric or table is ambiguous.

Which systems and warehouses does it work with?

It connects read-only to Snowflake, BigQuery, Postgres, or Redshift, posts answers in Slack, and optionally links charts in a BI tool like Looker, Tableau, Metabase, or Mode and pulls fields from a CRM such as Salesforce or HubSpot.

How is this different from doing the query myself or using generic business intelligence software?

Most business intelligence software relies on prebuilt dashboards or your own SQL skills; this agent answers a one-off plain-English question on the spot using your specific metric definitions and business rules. Every answer ships with the exact query, assumptions, and caveats, so it is auditable rather than a black box.

Can it replace our BI dashboards or our analysts?

No. It takes routine, repetitive ad-hoc questions off your analysts' plate so they can focus on deeper work, and it complements dashboards by answering the long tail of one-off questions a fixed dashboard cannot. Treat it as a fast first responder for questions, not a replacement for your business intelligence reporting software.

How does it keep my warehouse safe and my costs controlled?

It connects through a read-only role and can never INSERT, UPDATE, DELETE, or run DDL, and warehouse credentials are stored as environment secrets, never written into the prompt. Guardrails enforce a maximum row limit and a cost cap, and the agent narrows or aggregates a query rather than exceeding the cap.

Is there a separate cost or subscription for this template?

The template is free to import into Gamut and needs no extra API keys. You only need your existing accounts, the data warehouse you already pay for, and a Slack channel for questions; a BI tool and CRM are optional.