Agx is live · pricing not published · last verified 22 Oct 2026 · viability monitor
Agx
Agx turns plain-English questions into SQL and charts against your connected data warehouse.
The prompt-to-SQL-plus-chart loop is the entire product, and for the right team that is enough. Agx is worth a look if your specific problem is "I have a warehouse and my team can't write SQL." Because the pricing, docs and integrations pages were not retrievable this run, verify tiers and connectors with the vendor before you commit a team to it.
Verdict generatedVerified 22d ago · liveness 64/100 · cite: rightaichoice.com/tools/agx
- Growth and product teams that have warehouse access but thin SQL coverage
- Analytics teams fielding the same repetitive ad-hoc question tickets every week
- Marketers who can read SQL but would rather not write it
- Early adopters comfortable piloting a v0 analytics tool on one schema
- Teams that need governed, single-definition metrics across the whole company
- Anyone who needs analytics to work offline or without warehouse access
- Organisations where every query must be reviewed before it runs
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Skip Agx if your priority is a governed semantic layer where every team gets the same number for the same metric, rather than an AI that writes fresh SQL per question.
We could not reach Agx's pricing page this run, so we cannot place it against Metabase, Mode or a warehouse-native BI tool on cost. Ask the vendor for current tiers and any query or seat caps before you budget — for a small team the deciding cost is usually how many people need to ask questions, not how many data sources you connect.
In short
Agx — Agx turns plain-English questions into SQL and charts against your connected data warehouse. Best for Growth and product teams that have warehouse access but thin SQL coverage, Analytics teams fielding the same repetitive ad-hoc question tickets every week, Marketers who can read SQL but would rather not write it. Pricing not published.
What is Agx?
Agx — Agx turns plain-English questions into SQL and charts against your connected data warehouse. Best for Growth and product teams that have warehouse access but thin SQL coverage, Analytics teams fielding the same repetitive ad-hoc question tickets every week, Marketers who can read SQL but would rather not write it. Pricing not published.
Agx is an AI analytics workspace built around one loop: connect a data source, type a question in plain English, and get the generated SQL back next to a chart of the result. The scraped surface is deliberately narrow — a Sources panel for connections, a Queries panel listing generated SQL, a History panel of past questions, and a Data/Chart/Logs view for each request. A chat-style prompt box labelled "Agnostic AI (v0)" with a Send shortcut drives the whole thing. The product is aimed at people who know what they want to ask but not how to write the SQL — growth and product teams with warehouse access, analysts fielding repetitive ad-hoc questions, marketers who can read a query but would rather not author one. Connectivity documented in our seed notes covers Snowflake, BigQuery and PostgreSQL, with scheduled reports and alerts, shared workspaces, SQL export, and role-based access control listed as supporting capabilities. The honest read from the current scrape is that Agx is early-stage. The interface is minimal, the AI is versioned v0 in the UI itself, and most of the deeper capability claims in our notes are not visible on the pages we could reach this run. A login gate sits in front of the actual workspace, so the screenshot of the product is what we can verify. That narrowness is the positioning. You are not buying a BI suite to configure for six months — you are buying a conversational query layer over tables you already own, with the SQL exposed so you can check the machine's work. Against Metabase or Mode you give up dashboard depth and governed metric modelling; against a general chatbot you gain a live connection to your own warehouse.
Key features
- Generate SQL from a plain-English question in a chat prompt
- Render query results as a chart beside the generated SQL
- Side-by-side view of generated SQL and request logs for each prompt
- Sources panel for managing connected data warehouse connections
- Queries panel listing previously generated SQL statements
- History panel of questions asked in the workspace
- Keyboard send shortcut (⌘⏎) in the prompt input
- Toggle between Data, Chart and Logs views for a result
- Documented connectivity to Snowflake, BigQuery and PostgreSQL
- Scheduled reports and alerts on saved queries
- Shared collaborative workspaces for teams
- SQL export for query transparency and review
- Role-based access control for workspace users
- Embedded analytics for sharing results outside the workspace
- Anomaly detection surfaced on AI-generated insights
Behind the verdict
Pick Agx when the bottleneck is query authorship. If your analysts spend their week rewriting the same five joins for the marketing team, a chat box that emits checkable SQL removes a real queue. The side-by-side SQL and logs view matters more than it sounds — it is the difference between trusting the output and forwarding it to someone who can audit it. Pass when you need governed, single-definition metrics. Nothing on the scraped surface suggests a semantic layer, a metrics catalog, or a review gate before a query runs. Teams whose problem is "our numbers disagree across dashboards" are solving a different problem, and Agx will not solve it. In practice, treat this as a query accelerator, not a BI replacement. Dashboard depth and scheduled distribution against a modelled warehouse are where Metabase and Mode live, and Agx does not appear to compete there yet. Where it does compete is against pasting your schema into a general chatbot — you get a live connection and generated SQL rather than a plausible-looking guess. The caveats are mostly about maturity. The AI is labelled v0 in the product's own interface, and the login gate means we could not exercise the workspace ourselves. Seed-documented features — scheduled reports and alerts, shared workspaces, SQL export, role-based access control, embedded analytics, anomaly detection — should be treated as unverified until the vendor confirms them against your environment. One more thing worth flagging for buyers: the Sources/Queries/History layout implies per-user history rather than a shared query library. If your team's real need is a durable, reviewed repository of canonical queries, ask directly how history is scoped and shared before you roll it out. Our recommendation is a narrow pilot. Point it at one schema,
Limitations
- The product surface we could reach is a single query workspace and a login gate, so the draft features our earlier notes carried — scheduled reports, alerts, anomaly detection, embedded analytics, role-based access control — should be treated as unconfirmed until you see them in your own account.
- Agx is a query translator over data you already host; it does not replace a modelled semantic layer, so the same metric asked two ways can produce two different SQL statements.
- The prompt layer is labelled v0 in the interface, which means behaviour can shift between builds and any workflow you validate is worth re-checking after an update.
- We could not reach the pricing, documentation or integrations pages this run, so we make no statement about cost, API access, documentation coverage or connector availability.
as of 2026-10-05
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Is Agx still active?
Agx is live · pricing not published · last verified 22 Oct 2026 · viability monitor.
Viability score
How well maintained and how widely used is Agx? Built from what the vendor actually publishes (docs, changelog, tutorials, integrations, pricing), whether the site is live, and how much real users discuss it. How we calculate this
Last calculated: November 2026
How we score →What do users say about Agx?
What people actually say about Agx — is it worth it?
We ran a structured research pass across product reviews, community discussions, and post-purchase forum threads to surface the patterns vendors won't publish themselves. Below: the recurring strengths, the hidden costs people mention most, and the cohort that consistently regrets adopting this tool.
ResearchedDiscussed by users across 6 sources (Hacker News, YouTube, Product Hunt, Stack Overflow, GitHub, Lemmy) · researched Sep 24, 2026.
Weighted by the 71 posts each of 6 sources contributed.
- +Plain-English querying over Snowflake, BigQuery, and PostgreSQL removes SQL barrier for non-technical teammates
- +GitHub issues get fixed fast — three user-filed requests closed as resolved on 2025-11-07
- +SQL transparency with export means analysts can audit and reuse AI-generated queries
- +Freemium entry keeps evaluation cheap for small growth and product teams
- +Collaborative workspaces and AI-generated dashboards match how PM and marketing teams actually share insights
- −Real user reviews are almost nonexistent — Reddit, Trustpilot, and the App Store show nothing
- −The name collides with Jetson AGX, Darktable AgX, and AGX golf clubs, burying genuine discussion
- −No public performance benchmarks on large warehouses or high-volume queries
- −Product Hunt launch flopped with a single upvote, signaling weak early traction
- −The community is tiny — 262 GitHub stars and limited forum presence
- • Actual free-tier limits (queries, seats, data sources) aren't documented clearly, so unexpected upgrade pressure is plausible
- • Warehouse compute costs from AI-generated queries aren't included — heavy usage bills you on Snowflake/BigQuery side
- • No public enterprise pricing means sales calls are required for a real quote
How we verified this
Every listed fact about Agx — pricing, features, links, status — is re-read from the vendor's own pages by our verification pipeline and each change is logged with a date; the last pass ran on 22 Oct 2026. Analysis is drafted with AI models and checked against our editorial standards before publishing; see how we verify.
Verification history
We have re-verified Agx 11 times since . Each pass re-reads the vendor's own pages and re-checks every listed field against that evidence; passes where nothing had changed are marked as such.
- — changed our verdict, description, features, who should skip it, who it suits
- — changed SSL certificate
- — changed limitations, switching in, switching out, use cases, who it suits, description, our verdict, features, hidden costs, who should skip it, pricing fit, setup time, summary
- — changed pricing fit, setup time, who should skip it, hidden costs, switching out, switching in
- — changed domain expiry
- — changed SSL certificate
Showing the 6 most recent of 11 verification passes.
Free to cite with attribution — this page re-verifies continuously.
How much does Agx cost in 2026?
Agx: Pricing not published. Pricing last verified 22 Oct 2026.
Where the pricing makes sense
The company stage and team size where Agx's pricing actually pencils out — and where peers do it cheaper.
We could not reach Agx's pricing page this run, so we cannot place it against Metabase, Mode or a warehouse-native BI tool on cost. Ask the vendor for current tiers and any query or seat caps before you budget — for a small team the deciding cost is usually how many people need to ask questions, not how many data sources you connect.
Has Agx's pricing changed?
No plan price for Agx has moved since we began logging in Aug 2026; the pricing page is re-read on every verification pass.
Who should pick Agx?
Pick Agx if you are Growth and product teams that have warehouse access but thin SQL coverage, Analytics teams fielding the same repetitive ad-hoc question tickets every week, Marketers who can read SQL but would rather not write it, Early adopters comfortable piloting a v0 analytics tool on one schema.
Look elsewhere if you are Teams that need governed, single-definition metrics across the whole company, Anyone who needs analytics to work offline or without warehouse access, Organisations where every query must be reviewed before it runs, Buyers who need a mature, battle-tested BI suite with deep dashboarding today.
Skip it if Skip Agx if your priority is a governed semantic layer where every team gets the same number for the same metric, rather than an AI that writes fresh SQL per question.
GeneratedReal-world workflow fit
Concrete scenarios for the personas Agx actually fits — and what changes day-one when you adopt it.
You open Agx, connect the warehouse source your team already uses, and type a question about week-over-week signups by channel instead of filing an analyst request.
Outcome: You get the generated SQL and a chart in one pass, and you can paste the SQL into the request thread so an analyst can confirm the logic before the number travels.
You ask a follow-up question about activation by cohort, then keep going in the same session rather than resetting context each time.
Outcome: A short chain of answers replaces what used to be a multi-day back-and-forth, and the History panel leaves a record of exactly which questions produced which numbers.
You use Agx as a first pass on ad-hoc requests, reading the generated SQL and fixing it rather than writing from scratch.
Outcome: Routine requests get answered faster and you keep review control over anything that ships, which is the only way an AI query layer stays trustworthy on a team with real reporting obligations.
Use cases
- Ask a business question in plain English and get the SQL plus a chart in one step
- Let product and marketing teammates query the warehouse without an analyst ticket
- Reuse a saved question from History instead of rewriting SQL each week
- Inspect the generated SQL before a number goes into a deck
- Keep a running log of what the team has asked and what came back
Setup time & first value
How long it actually takes to get something useful out of Agx — broken out by persona, not the marketing-page minute.
For a growth or product user with existing warehouse credentials, first useful answer is a single session — connect the source, type a question, read the SQL. For an analyst wiring up a new connection and validating that the generated SQL matches your existing definitions, budget an afternoon. Team-wide rollout depends on how much access review your organisation requires before pointing a new
Switching to or from Agx
How to bring data in from common predecessors and how to get it back out — written for the switcher, not the buyer.
- →From a general-purpose chatbot: point Agx at the warehouse so answers come from live tables and you can read the SQL behind them, rather than pasting schema into a chat window.
- →From manual SQL ad-hoc requests: let requesters ask Agx first and use the generated SQL as the starting draft for the analyst review.
- ↗To Metabase or Mode: rebuild your saved Agx questions as governed models and dashboards when you need consistent metric definitions across teams.
- ↗To a semantic-layer-plus-BI stack: move the metrics people ask about most into a modelled layer so the phrasing of a question no longer changes the SQL behind it.
Integrations
Resources & guides
Tutorials & Learning
YouTube returned 6 videos for “Agx”, and we withheld 6: 6 could not be judged, because “Agx” is a single word that other videos use for other things. We are showing none, because we could not prove any of them are about Agx.
Official links
What are the best Agx alternatives?
The closest alternatives to Agx we list are Definite, DataLab and Julius AI. Ranked by direct product-type match, not category overlap.
| Alternative | Pricing | Starts at | Last verified |
|---|---|---|---|
| Definite | Freemium | Pricing not published | — |
| DataLab | Freemium | Pricing not published | — |
| Julius AI | Freemium | Pricing not published | — |
Alternatives to Agx
View all
Tools that pair well with Agx
Common stack mates teams adopt alongside Agx, with the specific reason each pairing earns its keep.
Definite
Definite turns plain-English questions into self-hosted data apps backed by 500+ connectors and an AI analyst named Fi.
DataLab
DataLab turns plain-English questions into runnable SQL, Python and R inside an AI data notebook you can review and share.
Julius AI
Julius AI turns plain-English questions about your CSV, Excel, or Postgres data into charts, statistical tests, and regression models.
Agx vs its closest rival
Agx's closest head-to-head is with Screenplayiq.
Our Agx vs Screenplayiq verdict written Jul 3, 2026 is more than 90 days old, so it is being re-reviewed against current data and is not shown.
Frequently asked questions
Best-of guides
For makers of Agx
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