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Anomalo
Autonomous data quality platform that monitors tables, catches anomalies, and helps data teams investigate issues before dashboards go wrong. Anomalo raised a $10 million Series B extension in November 2024 and took a strategic investment from Snowflake Ventures in 2025.
Data teams that need automated anomaly detection and investigation across warehouse tables feeding AI and BI.
Teams that only want a few SQL assertions and will not invest in a dedicated data quality platform.
Verdict
Anomalo is a data quality and observability product that watches tables, flags anomalies, and helps teams find why numbers broke. Data and analytics engineers use it to protect dashboards and AI features that depend on clean inputs. It matters when silent data bugs cost more than another alerting tool.
Score Breakdown
How Anomalo scores in the categories that matter to its buyers.
Pricing
Anomalo prices through sales-assisted enterprise packages. Model below reflects common mid-market packaging themes for 2026; confirm warehouse scope and table volume directly.
Sales-assisted data quality platform. Expect annual packages sized by tables, warehouses, and seats; ask what autonomous monitoring versus custom rules are included.
The Field at a Glance
How Anomalo compares with other AI data quality & observability vendors we reviewed, by Overall Score and relative typical engagement cost.
Anomalo scores 7.6 in AI data quality & observability, ahead of Soda (7.4), Bigeye (7.3), and Sifflet (7.3). Relative cost lands upper-mid for this subcategory.
Use-case matrix
| Use case | Fit | Notes |
|---|---|---|
| Autonomous anomaly detection | Strong | Learns each table's normal pattern and flags deviations. |
| Root-cause investigation | Strong | Points to the rows and columns behind an anomaly. |
| Warehouse coverage | Strong | Connects to cloud warehouses such as Snowflake. |
| Simple SQL assertion kits | Mixed | Soda Core covers rule checks written as code. |
| Full AI governance suite | Mixed | Bigeye adds lineage and policy controls. |
| Compliance automation | Poor | Anomalo does not cover compliance automation. |
Review Excerpts
Representative buyer views drawn from public information about Anomalo. Paid reviews and pay-for-play sites were excluded.
“It flags unusual values in our tables without us writing a rule for each one.”
Representative buyer view
“Alerts show which rows and columns changed, so triage starts from evidence.”
Representative buyer view
“Pricing is by quote, and a team with a few key tables may find simpler rule-based tools enough.”
Representative buyer view
Where customer reviews couldn't be found, our analysts attempted to give a voice to buyer sentiment, drawing on real information from review sites, forums, and product documentation.
Based on: Anomalo’s website
Company Facts
- Founded
- 2018 (CB Insights)
- Headquarters
- Palo Alto, California, United States (CB Insights)
- Total funding raised
- $81.95M (CB Insights)
- Key investors
- Snowflake Ventures, Smith Point Capital, Foundation Capital, Deviation Capital, Norwest (CB Insights)
- Customers
- Discover, Block, Notion and Buzzfeed (CB Insights)
- Website
- anomalo.com
Key Leadership
Elliot Shmukler
Co-founder and CEO
Methodology
This page is an independent evaluation of Anomalo for buyers comparing options in AI data quality & observability. AI Industry Reviews accepts no sponsorships, advertising, or pay-for-placement fees. Anomalo did not pay for this review.
What we scored
The headline number is an Overall Score on a 0-10 scale. Eight criteria sit under it in two groups.
- Buyer outcomes (for AI data quality & observability)
- Autonomous data quality monitoring
- Issue investigation & root cause
- Warehouse & lake coverage
- Lightweight rule-only setup
- Company & commercial
- Innovation & product leadership
- Project management & communication
- Pricing
- Contract fairness
Pricing measures whether the price looks fair for the value delivered, including packaging and renewal friction that show up in real buying cycles.
Score Composition
| Input | Weight | What it covers |
|---|---|---|
| Reviews | 40% | A proprietary read of what practitioners say about likes, complaints, and day-to-day use, including public review sites, forums, and private chat rooms. Paid reviews and pay-for-play sites are out of scope. |
| Product | 35% | Hands-on look at screens and workflows. |
| Pricing | 15% | Whether the price looks fair for what you get. |
| Docs & training | 10% | Docs, tutorials, and training material. |
How we balanced the evidence
The Overall Score is the simple average of the eight criteria. Recommendation language follows that score and the use-case matrix above.
Scope
Anomalo is graded here as AI data quality & observability. Criteria scores can move as more review volume and product checks are added.