Holistics

Growth

Self-serve BI platform with a code-based semantic modeling layer that lets data teams define metrics once and share governed reports across the organization.

Self-Serve BI Platform
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Company Overview

About Holistics

Holistics is a business intelligence platform founded in 2016 and headquartered in Singapore, built around the idea that BI should be governed by data teams but accessible to everyone in an organization. Its core differentiator is a code-based data modeling layer — called AML (Analytic Modeling Language) — that allows analysts to define metrics, relationships, and business logic in version-controlled code rather than ad-hoc SQL. This single source of truth for metrics ensures consistency across all reports and dashboards, eliminating the discrepancy problem that plagues spreadsheet-driven BI workflows.

Business Model & Competitive Advantage

The platform supports a full self-serve workflow: data analysts define models and datasets in code, then business users explore and filter those datasets through a no-code interface without needing to write SQL. Holistics connects to all major cloud data warehouses including BigQuery, Snowflake, Redshift, and dbt-managed models, and its query caching and scheduling features reduce warehouse costs for high-frequency reporting. Report distribution via email and Slack, embeddable dashboards, and an API for programmatic report management complete the platform's feature set for data-driven organizations.

Competitive Landscape 2025–2026

Holistics has found strong product-market fit in Asia-Pacific, Southeast Asian tech companies, and mid-market SaaS businesses globally that prioritize governance and metric consistency over flashy visualization. The company competes with Looker, Metabase, and Mode but distinguishes itself with its opinionated code-first approach to the semantic layer, which resonates with data engineering teams already comfortable with dbt and version control. Holistics operates on a transparent, usage-based SaaS pricing model and has grown primarily through word-of-mouth and community in the modern data stack ecosystem.

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