Daana
Daana provides a declarative data modeling platform that lets teams define business entities, relationships, and transformations in YAML, while a CLI engine automates consolidation, historization, deduplication, testing, and lineage tracking. The platform connects technical and semantic lineage, enabling both humans and AI coding agents to understand and operate on a single, declared data model. Daana also offers embedded consulting services to help mid-market teams build and transfer data platform knowledge.
- Artificial Intelligence
- AI Agents
- Data & Analytics
- Developer Tools
- Software Only
Funding
Founders
Product
Problem
Data platforms often accumulate organically rather than being deliberately designed, leading to deteriorating architecture, unclear data definitions, and a growing gap between how data moves and what it means. This makes it difficult for both humans and AI coding agents to understand, build on, and maintain the platform reliably.
Solution
Daana provides a declarative data modeling engine where users define business entities, relationships, and transformations in YAML. The Daana CLI automatically handles consolidation, historization, deduplication, testing, lineage, and change tracking, reducing manual hand-coding. The platform connects technical lineage (fields, transformations, dependencies) with semantic lineage (definitions and meaning) at every layer, giving users a complete picture of both data flow and context. This unified model is readable and operable by both human engineers and AI agents, enabling collaborative development and maintenance.
Target Audience
Primary customers are mid-market companies with a mandate to redesign their data platform, typically those large enough to need a robust data infrastructure but small enough for key stakeholders to drive architectural change.
Features
- YAML-based declarative modeling for entities, relationships, and transformations, eliminating hand-coded pipelines
- CLI engine that automates consolidation, historization, deduplication, testing, and change tracking
- 3-layered architecture that separates technical and semantic lineage for full data context
- Source-to-metric traceability, illustrated through examples like subscription lifecycle modeling
- Single declared model that both humans and coding agents can understand and build on together