Coginiti
SQL development and semantic layer platform with AI agent governance
💬 What is Coginiti?
Coginiti is a semantic intelligence platform that unifies how organizations develop, govern, and deploy trusted SQL business logic across heterogeneous data estates. It targets data engineering and analytics teams in government, defense, and regulated enterprises that need to author, test, version, and promote SQL across 21+ database platforms including Snowflake, Databricks, Oracle, IBM Db2, and Apache Hive. The platform combines a SQL data workbench, a CoginitiScript authoring layer, an analytics catalog, and a governed semantic layer that AI agents query for trusted metric definitions rather than raw column names. It is distinct from pure transformation tools like dbt or pure semantic-layer products like AtScale, Cube, and Kyvos by starting in SQL and capturing the full analytic context — queries, tests, collaboration, and assumptions — across cloud, on-prem, classified (IL2–IL6), and edge environments. Named customers include US NAVSUP, the US Army Corps of Engineers, and DHS CISA.
Who it's for
Best for: Data engineering and analytics teams in government, defense, and regulated enterprises that need to develop, govern, and deploy SQL logic across heterogeneous and classified data estates.
- Authoring, testing, and versioning SQL across multiple warehouse and on-prem database dialects
- Building a governed semantic layer for BI tools and AI agents
- Operationalizing trusted metric definitions from raw SQL logic
- Grounding AI agent answers in auditable, curated business knowledge
- Supporting classified (IL2–IL6) and air-gapped analytics environments
Pros & cons
- Broadest platform coverage cited at 21+ databases including Snowflake, Databricks, Oracle, IBM Db2, and Apache Hive
- Supports classified and air-gapped deployments (IL2–IL6)
- Captures full analytic knowledge (queries, tests, collaboration, context), not just metric definitions
- AI agents query a governed semantic layer for auditable answers
- Named US government customers including NAVSUP, USACE, and DHS CISA
- No public pricing — site requires a Request Demo to access pricing details
- No free tier or self-serve plan evident on the scraped site
- Enterprise/government focus and demo-gated sales motion likely不适合 small teams or individual users
- Semantic-layer positioning is a narrower niche than general-purpose SQL or BI tools
Key features
- SQL authoring and testing against live data across 21+ database platforms
- Multi-dialect support for Snowflake, Databricks, Oracle, IBM Db2, Apache Hive, and others
- Version control and collaboration for analytic SQL logic
- CoginitiScript reusable semantic definitions and analytics catalog
- Governed semantic layer that operationalizes metric definitions for AI agents and BI tools
- AI agent integration that returns auditable answers grounded in curated business knowledge
- Deployment to cloud, on-prem, classified (IL2–IL6), and edge/air-gapped environments
- Capture of queries, tests, collaboration, and context for organizational knowledge retention
Pricing
Pricing compared →Prices listed on the Coginiti pricing page: $189/user
Source: coginiti.co pricing page. Price checked 2026-10-08. Confirm current plans before buying.
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Frequently asked
What databases does Coginiti support?
21+ platforms including Snowflake, Databricks, Oracle, IBM Db2, and Apache Hive, across cloud, on-prem, classified, and edge deployments.
How is Coginiti different from dbt or AtScale?
dbt focuses on transformation pipelines and AtScale on semantic modeling; Coginiti starts in SQL, captures full analytic knowledge (queries, tests, context), and ships both a semantic layer and AI agent grounding.
Does Coginiti support air-gapped and classified environments?
Yes, including IL2–IL6 classified deployments used by US government customers.
Who uses Coginiti?
Government and defense agencies including US NAVSUP, US Army Corps of Engineers, and DHS CISA, plus commercial enterprise data teams.
Does Coginiti include AI agent features?
Yes — AI agents query the governed semantic layer for trusted metric definitions and auditable answers instead of inferring from raw columns.