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Anomalo
Your data is always talking. Don't miss what it's saying.
350 followers
Your data is always talking. Don't miss what it's saying.
350 followers
Your data changes constantly. Anomalo Analyst tells you what matters before you know to ask. It proactively monitors your Snowflake, Databricks, or BigQuery data, surfaces important trends, anomalies, and shifts, and lets you investigate with follow-up questions in plain language. Every insight is verified against your data, with Anomalo helping distinguish real business changes from broken data.
Free
Launch Team / Built With
Anomalo
Hey Product Hunt, I'm Elliot, co-founder and CEO of Anomalo.
I've spent years working with data — growth and product roles at @instacart and @LinkedIn, then building enterprise data quality tools at @Anomalo . I’ve seen that some of the biggest lessons often came from changes in the data. At Instacart, launching one new retailer surfaced an engagement spike that reshaped our growth strategy for years. At LinkedIn, small experiments in network-building tools moved user behavior enough to reset our roadmap.
But spotting those data changes is hard. You need dashboards for everything that matters and someone watching obsessively. Even with teams of analysts, we missed a lot.
That's why we built Analyst. Using technology Anomalo pioneered for data quality monitoring, it learns what's normal for your data, then uses AI to spot and explain meaningful changes — creating an automatic news feed of what moved and why.
Most data tools only answer the questions you thought to ask. The valuable data changes are often the ones nobody asked about: a paid social campaign that spiked purchases but only for certain SKUs, a supplier whose delivery times crept up 52% over a quarter, a metric that degraded only because of a mix shift. Anomalo Analyst spots these changes for you.
Just connect @DataBricks , BigQuery, or @Snowflake , read-only, and tell Analyst what matters in each table so the insights are tailored. You’ll start seeing Analyst insights in the first few days. Each insight includes a business summary, a technical summary, and the underlying logic and investigative steps.
Free to start. Give it a try and then tell us what it found.
Do you show the SQ or logic behind each insight so teams can double check.
Anomalo
@simonclark55 yes, you can see all the logic the agent used including all the SQL queries it ran, precisely so teams can double-check and/or replicate its work.
Lancepilot
step 2 has AI agent decide what matters after statistical modeling ranks changes by magnitude. in practice painful work of framing question is where operators build mental model of the business. if tool decides what is worth noticing before human forms hypothesis, understanding of system atrophies or relevance just becomes whatever had highest statistical variance )
This feels like it could save a lot of time in standups. Instead of hunting for what changed you just get the story.
This makes data quality monitoring feel much more proactive and useful Love the focus on catching issues before they become bigger problems