nlq

A solution guidance for Generative BI using Amazon Bedrock, Amazon OpenSearch with RAG

Demonstration of Natural Language Query (NLQ) of an Amazon RDS for PostgreSQL database, using SageMaker JumpStart, Amazon Bedrock, LangChain, Streamlit, and Chroma.

Self-hosted 4D spatiotemporal AI platform built on PostgreSQL, PostGIS, TimescaleDB, H3 and pgvector, with anomaly & threat detection, NLQ interface and full observability.

Parser for end-user search-like queries and rule-based named entity recognition (NER) in context of tabular dataset schema.

A two-step framework for extracting textual answers from egocentric videos via NLQ, combining VSLNet for segment localization and Video-LLaVA for efficient answer generation.

GenoQuery is an innovative tool designed to streamline the process of querying genomic and biological data through a user-friendly chatbot interface.

Application component that provides Natural Language Querying (NLQ) services, making knowledge stored in a graph database accessible for e.g. a ChatBot UI.

Description: Governed natural-language-to-SQL platform for finance teams with RBAC, audit logging, and KPI glossary

Python modules and Jupyter Notebooks demonstrating NLQ system using GraphDB

An advanced agentic system that converts Natural Language Queries (NLQ) into SQL, executes them against a database, and provides natural language responses.

30-query DoE stress-test of an enterprise NL2SQL semantic platform. Diagnosed 16 architectural failures across 5 bug classes using BigQuery ground-truth validation.

Local LLM pipeline translating natural language to SPARQL for OWL2-RL reasoning in GraphDB, validated by a structured benchmark.

A complete data journey is demonstrated. Data engineering -> Data analysis (EDA) -> Data visualization -> Data forecasting -> Data Science (GenAI LLM approach). Interactive Tableau and Power BI dashboard are included for non-technical stakeholders.

Query OpenSearch indices with natural language.

An AI-powered conversational chatbot built for the Central Ground Water Board (CGWB) that makes India's groundwater assessment data (INGRES) accessible through natural language. Ask questions in any of 11 Indian languages, get instant insights, and explore interactive visualizations — no technical expertise required.

Reads your financial documents and lets you ask questions about them in plain English.