Tech riderRev. 30 Sept 2026

Quaeris Semantic Layer

Ch 106.6of 28 Semantic Layer Software

1Runs onAPI, Web
2Costsfree trial · paid from $1,000/mo
3Governed metricsYes
4Dimensions and joinsYes
5Row-level securityYes
6Certified modelsYes
7Query APIYes
8Deployment modelhybrid

8 lines stated Written from the maker's own pages: quaeris.ai

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Overview

Quaeris Semantic Layer is ranked #10 of 28 in semantic layer software on Specifiction. It runs on API, Web. There is no free plan. A free trial is offered. Paid plans start at $1,000/mo.

Quaeris Semantic Layer plans and pricing

All plans

Team $1,000/mo $1,000–$2,500 / month; billed annually or monthly, depending on number of Agents/Agent Runs, Users and Source Systems 1 warehouse connection · up to 200 certified metrics · 1 AI model provider slot · 90-day prompt-level audit log quaeris.ai · 30 Sept 2026

Professional $2,500/mo $2,500–$7,500 / month; billed annually or monthly, depending on number of Agents/Agent Runs, Users and Source Systems Up to 5 warehouse connections · 3 AI model provider slots · 1-year prompt-level audit log quaeris.ai · 30 Sept 2026

Enterprise Not published Custom pricing; contact sales for a configuration scoped to your environment Unlimited users · unlimited warehouse connections · unlimited AI model provider slots · custom audit-log retention · custom SLA quaeris.ai · 30 Sept 2026

Compared on semantic layer software

Free plan: Noquaeris.ai
Paid from: $1,000/moquaeris.ai
Governed metrics: Yesquaeris.ai
Dimensions and joins: Yesquaeris.ai
Row-level security: Yesquaeris.ai
Certified models: Yesquaeris.ai
Query API: Yesquaeris.ai
Deployment model: hybridquaeris.ai

Facts

Purpose: The Smart Semantic Layer learns metric patterns from user questions and lets a team certify, version, and govern shared metric definitions.quaeris.ai · 30 Sept 2026
Lineage: Quaeris says answers can trace metrics from dashboard values to source tables and record who approved metric changes and when.quaeris.ai · 30 Sept 2026
Learning and certification: The platform observes natural-language queries in real time, while the customer’s data team reviews and certifies proposed definitions.quaeris.ai · 30 Sept 2026
Warehouse support: Named warehouse connections include Snowflake, BigQuery, Databricks, Redshift, and Azure Synapse.quaeris.ai · 30 Sept 2026
Business system integrations: The integrations page names SAP, Salesforce, Oracle, Workday, and Microsoft Dynamics 365, and notes that availability should be confirmed with the account team.quaeris.ai · 30 Sept 2026
Model integrations: Quaeris says customers can connect OpenAI, Anthropic, Google, or Meta models and switch providers while retaining governance definitions.quaeris.ai · 30 Sept 2026
Data handling: Quaeris states that it queries warehouse data in place, does not use platform data to retrain models, and deletes session data after use.quaeris.ai · 30 Sept 2026
Access controls: The access-control page describes row-level security and column masking applied at query time, with policies intended to carry across UI, agent, API, and export paths.quaeris.ai · 30 Sept 2026
Compliance status: The pricing page says GDPR data-processing controls are included in Enterprise, SOC 2 Type II and ISO 27001 audits are in progress, and HIPAA controls are on the roadmap.quaeris.ai · 30 Sept 2026
Audit and retention: Prompt-level audit-log retention is listed as 90 days for Team, one year for Professional, and custom for Enterprise.quaeris.ai · 30 Sept 2026
Support: Team includes community support and documentation, Professional adds priority support and dedicated onboarding, and Enterprise includes a named Customer Success Manager.quaeris.ai · 30 Sept 2026
Who it is for: Quaeris describes the Semantic Layer as serving data teams and cross-functional users who need governed analytics, and identifies regulated industries among its target deployments.quaeris.ai · 30 Sept 2026
Platform access: The company offers a REST API and MCP tools for querying governed data from applications, workflows, and compatible AI hosts.quaeris.ai · 30 Sept 2026