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mnemiq
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mnemiq

Active·★ 81·Apache-2.0·Updated 2026-10-22

mnemiq is an open-source Text-to-SQL engine designed to answer natural-language questions over databases, emphasizing tunability and transparency. It ensures verifiable results by separating SQL generation from execution, providing clear reasons for query refusals rather than generating incorrect answers.

#Text-to-SQL#LLM Applications#Database Query#Data Governance#SQL Generation#Evaluation Framework
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Guides
$ Install
$ git clone https://github.com/agenticfabriq/mnemiq.git && cd mnemiq && uv sync
↗ Visit site★ GitHub
01

Features

01Separates SQL generation from execution with a deterministic validation layer.
02Exposes tunable pipeline settings for LLM choice, schema context, and semantic enrichment.
03Offers tiered semantic enrichment from basic schema to certified business definitions.
04Includes an integrated evaluation harness for measuring performance on custom databases.
05Enforces robust access control and row/column level security policies.
02

Compatibility

Python
Runtime
Verified via docs
PostgreSQL
Database
Verified via docs
SQLite
Database
Verified via docs
DuckDB
Database
Verified via docs
Oracle
Database
Verified via docs
Snowflake
Database
Verified via docs
03

Quick start

1
$ git clone https://github.com/agenticfabriq/mnemiq.git
2
$ cd mnemiq
3
$ uv sync
04

Use cases

↳Answering natural language questions directly from relational databases.
↳Benchmarking and tuning Text-to-SQL solutions against proprietary enterprise data.
↳Integrating secure and verifiable database querying into AI agent workflows.
↳Implementing robust data governance for LLM-driven data access.
05

Alternatives

⚡Top VS:
VSorionbelt-semantic-layer★101→VSdst★16→VSpublisher★118→

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agenticfabriq /
mnemiq
↗

Open-source text-to-SQL engine you tune and measure on your own database

81Apache-2.0
Last commit1d ago
StatusActive
CategoryRAG / Knowledge Base
Links
Documentation↗Discussion↗Issues↗Releases↗
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