Digital Journal · Aug 2025
Profiles Query Vary’s work on custom AI reporting tools for oil and gas and other industrial workflows, highlighting its report automation approach and Walter Pintor’s role.
Public company, workplace, funding, and market signals
Updated Jul 30, 2026
Query Vary is a YC-backed no-code LLM workflow and prompt-evaluation platform for building AI-powered back-office automations, with template-based guardrails, multi-model support, team collaboration, and enterprise security.
Primary product
No-code LLM application / workflow builder for AI-powered automations
Founded
2021
Headquarters
Singapore
Team size
1-10
Industry
Technology, Information and Internet
Sub-industry
No-code LLM workflow automation / prompt testing
Offices
0 jobs at Query Vary
Check back later for new openings
Business model
Stage
pre-seed
Total raised
$500K
Latest round
Pre Seed Round · Mar 2022
Latest amount
$500K
Mar 2022 · Y Combinator
Collaborative, reliability-focused B2B startup culture centered on prompt testing, no-code workflows, domain-expert involvement, and enterprise security.
Compensation
No public salary bands or compensation details found; YC jobs page shows no open roles.
Benefits
Pricing
Freemium with credit-based usage and BYO-keys; demo/contact-led selling for larger deployments.
Differentiators
Technology
Customers
Competitors
Estimated revenue
≈$900K ARR (estimated)
Estimated monthly visits
2.8K
Traffic estimate as of May 2025
Digital Journal · Aug 2025
Profiles Query Vary’s work on custom AI reporting tools for oil and gas and other industrial workflows, highlighting its report automation approach and Walter Pintor’s role.
LinkedIn · Jun 2025
Company announcement that Query Vary joined Google’s AI Startup Program in Singapore.
Query Vary blog · Apr 2024
Company blog post discussing enterprise data privacy concerns, risks, and solutions for LLM use.
Query Vary blog · Apr 2024
Announces support for Claude 3 models and links to other company blog topics and product pages.
Query Vary blog · Apr 2023
Explains the report-generation workflow and how AI can turn field notes into standardized reports faster than manual processes.