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Added on Oct 27,2026
ekai is an AI platform that builds governed semantic models and production dbt pipelines for data warehouses by learning business meaning from a company's own experts.
It profiles data in place, asks the people who understand the data what fields and values mean, and turns their answers into documented definitions such as what counts as revenue or an active customer.
It then infers structure, including relationships between tables when no foreign key constraints are declared, and flags uncertain items for human review before generating models.
Key features include automated semantic modelling, dbt model generation with tests and documentation, glossaries, metrics and lineage, and verification of every definition against the warehouse before anything ships.
It works with Snowflake, Databricks, BigQuery, Azure Synapse, PostgreSQL, ClickHouse and DuckDB, versions every artifact to GitHub, GitLab or Bitbucket, and can route model traffic through your own LLM endpoints, including Vertex AI and Azure OpenAI.
ekai can be installed as a Snowflake Native App inside your account or run as dedicated SaaS on AWS, Azure or GCP, using read-only connections so rows, profiles and metadata stay within your boundary.
Pricing: Starter, Standard and Enterprise packages are offered on custom pricing, scaling by the number of semantic models and tables, so you need to talk to sales.
It is suited to data engineering and analytics teams in organisations that need trusted, documented semantic layers for reporting and AI use.
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