Tag
Presents an LLM-driven framework for retrieving remote sensing data from cloud-based geospatial catalogues using natural language queries, with a focus on safety and adversarial robustness. The system integrates three agents for intent interpretation, API call generation, and risk management.
TwinBI is a framework that couples an LLM-based agent with an executable BI dashboard state to maintain consistency during multi-step analytical interactions, improving accuracy and reducing timeout rates in benchmarks.
QuantMind is an open-source framework for intelligent knowledge extraction and retrieval in quantitative finance. It can automatically fetch unstructured content like papers and news, build a queryable structured knowledge base, and support natural language retrieval.
OmniRetrieval is a framework that unifies retrieval across heterogeneous knowledge sources (text, tables, graphs) by dispatching native queries to appropriate execution engines, outperforming single-source baselines on a benchmark of 13 datasets and 309 knowledge bases.
DivSkill-SQL is a residual skill optimization framework that builds complementary agentic Text-to-SQL ensembles without model fine-tuning, improving selected accuracy by up to +11.1 points on Spider2-Lite by targeting examples that current ensembles fail on.
Skopx is a conversational AI analytics platform that lets users ask business questions in plain English, automatically generating insights from connected data sources without SQL. It provides transparent reasoning, role-based access, and integrates with existing tools.
OpenAI details an internal AI data agent built on GPT-5, Codex, and their Evals/Embeddings APIs that lets employees query over 600 petabytes across 70k datasets using natural language. The tool reduces time-to-insight from days to minutes and is used across Engineering, Finance, Research, and Go-To-Market teams.