Head to head
AtScale vs Euno for AI agents
Short answer
On our default weights Euno scores 7.64 and AtScale scores 5.87. Euno scores higher on Lineage, Automation, Governance, Answer checks and Pricing; AtScale scores higher on Semantics and Deployment. They tie on Agent access and Integrations.
By The Lineage Desk · Best Data Catalogs · Published
Desk research from public vendor pages. Editorial assessment.
How do AtScale and Euno compare on each criterion?
| Criterion | Weight | AtScale | Euno | Higher score |
|---|---|---|---|---|
| Agent access to context | 15% | 9 | 9 | Tie |
| Cross-stack lineage | 13% | 2 | 9 | Euno |
| Automated context build | 13% | 4 | 9 | Euno |
| Governance agents can use | 13% | 8 | 9 | Euno |
| Business definitions and metrics | 12% | 9 | 7 | AtScale |
| Answer quality checks | 8% | 5 | 9 | Euno |
| Integration breadth | 10% | 5 | 5 | Tie |
| Pricing transparency | 8% | 4 | 5 | Euno |
| Deployment options | 8% | 5 | 4 | AtScale |
Why: Agent access to context
AtScale: An MCP server with named tools gives agents certified metrics by name; seven agent clients are named.
Euno: Serves context to agents through an MCP server and a Context API (up to 500K or 1M calls by plan), scoped by persona; Claude and Cursor are named.
Source: Euno: Context for AI Agents
Why: Cross-stack lineage
AtScale: A semantic layer, not a catalog; cross-stack lineage is not described.
Source: AtScale homepage
Euno: Column-level lineage from sources through BI dashboards to AI agents, including business logic inside BI workbooks.
Source: Euno: Context for AI Agents
Why: Automated context build
AtScale: Describes a 30-day workshop from kickoff to results; automated discovery is not described.
Euno: Maps assets automatically from day one and precomputes the context graph from APIs and query logs; Euno states zero onboarding lift.
Source: Euno homepage
Why: Governance agents can use
AtScale: Per-agent OAuth identity, row- and column-level security and a log of every call.
Euno: Governance rules become live labels (for example certified or PII-free) that propagate through the graph, with persona-based access to context.
Why: Business definitions and metrics
AtScale: A universal semantic layer serving certified metrics to BI and agents.
Source: AtScale homepage
Euno: Extracts definitions from BI workbooks and SQL and syncs dbt with Looker; it does not offer a semantic layer of its own.
Why: Answer quality checks
AtScale: Every call is logged, and AtScale cites a preliminary result of twice the accuracy on BIRD-Interact.
Euno: Context Calibration generates benchmark questions, checks agent answers and suggests missing rules and glossary terms.
Why: Integration breadth
AtScale: Agent clients are listed, but no data source count was read.
Euno: Plans cap integrations at 3, 5 or 10; the full source list could not be read.
Source: Euno pricing
Why: Pricing transparency
AtScale: The pricing model is published (deployed semantic objects, no per-seat or per-query fees) but no prices.
Source: AtScale pricing
Euno: Tiers, resource limits and a feature table are published, priced by data assets with unlimited users and agents, but no dollar prices.
Source: Euno pricing
Why: Deployment options
AtScale: Queries compute inside your data platform; hosting options are not stated.
Euno: Cloud-native SaaS only, reading metadata only; no self-hosted or open-source option is described.
Source: Euno homepage
Which hops from warehouse to agent does each document?
AtScale: documents 4 of 5 stages
Euno: documents 5 of 5 stages
How do pricing and deployment compare?
| AtScale | Euno | |
|---|---|---|
| Type | Universal semantic layer | AI context platform |
| Agent interface | AtScale MCP server (list_models, explore_columns, focus_columns, get_sml_skills, run_query, get_outbound_queries); AtScale Ava for chat users | MCP server, Context API, Euno Assistant |
| Lineage | Not described (a semantic layer, not a catalog) | Column level, from sources through BI dashboards to AI agents |
| Deployment | Queries compute inside your data platform; hosting options are not stated on the pages we read. | Cloud-native SaaS; reads metadata only. No self-hosted or open-source edition described. |
| Pricing | Not published Consumption pricing by deployed semantic objects, in Standard and Enterprise editions, with no per-seat or per-query fees. No prices are published. Source: AtScale pricing | Priced by the data assets you manage, with unlimited users and AI agents. Three tiers: Start (up to 150K resources), Scale (up to 1.5M resources) and Enterprise (any scale), each on request. No dollar prices are published. Source: Euno pricing |
| Entry price | Not published | Not published |
Which should you choose?
Choose AtScale if
- you need many ways for agents to reach context
- consistent metric definitions are the main gap
- Enterprises that need certified metrics served to many agent clients under per-agent security
Choose Euno if
- you need many ways for agents to reach context
- you need lineage from the warehouse through BI to the agent
- Data teams that want agents grounded in lineage and governance across warehouse, dbt and BI without finishing a semantic layer first
Frequently asked questions
Which is better for AI agents, AtScale or Euno?
On our default weights Euno scores 7.64 and AtScale scores 5.87. The better fit depends on which criteria matter most to you; the weight-your-own page lets you change the weights.
Which costs less, AtScale or Euno?
AtScale: no prices published. Euno: Priced by the data assets you manage, with unlimited users and AI agents. Three tiers: Start (up to 150K resources), Scale (up to 1.5M resources) and Enterprise (any scale), each on request. No dollar prices are published. We do not compare total cost because most of these prices are not published.
Can AtScale and Euno be used together?
They cover different layers (Semantic layer and Context platform), so they can sit side by side. The pages we read do not describe a direct integration between them.