#TextToSQL

AI-to-SQL is not solved. Most demos prove the model can write SQL. Production asks a harder question:can the agent understand which table, join, metric, filter, and business rule actually apply? That is where most failures start. #TextToSQL #SQL

👀 WHAT ARE YOU SHIPPING? Built a SaaS people actually need? Drop your product below 👇 No pitch. No hype. Just show us what you built. 🚀 Let’s discover the next underrated SaaS. 🔥

@TanzilaSha9574 Built Zeroquery: connect any database, get a working AI app - no hand-built APIs, no admin panel. DAB-powered SQL MCP + dynamic UI + human-in-the-loop writes. Open source, MIT 🧵 #MCP #textToSql #OpenSource

𝗧𝗲𝘅𝘁-𝘁𝗼-𝗦𝗤𝗟 𝗜𝘀 𝗡𝗼𝘁 𝗮 𝗣𝗿𝗼𝗱𝘂𝗰𝘁𝗶𝗼𝗻 𝗔𝗿𝗰𝗵𝗶𝘁𝗲𝗰𝘁𝘂𝗿𝗲 Generating SQL is easy. Guaranteeing trust, permissions, and stable semantics is the hard part. AI should assist exploration. Not become the runtime layer. #ai #texttosql #llm #dataengineering

Point at any database → get a working AI app in 60 sec. ⚡ Zeroquery auto-generates a scoped SQL MCP server, then renders your natural language queries as live tables, charts & cards with human-confirmed writes, not autonomous ones. #TextToSQL #mcp #ai

piglets is a text-to-SQL toolkit. Current features: Planning Pruning More features coming soon. All LLM providers supported (via @LangChain). Databases: @googlecloud BigQuery @duckdb @motherduck @Snowflake #texttoSQL

Built a self-correcting text-to-SQL agent: LangGraph state machine + Ollama (local LLM) + ChromaDB for schema-aware retrieval, with a read-only SQL validator. A Multi-source orchestration 🧠🗃️🔒 #LangGraph #Ollama #TextToSQL

Built Zeroquery: connect any database, get a working AI app — no hand-built APIs, no admin panel. DAB-powered SQL MCP + dynamic UI + human-in-the-loop writes. Open source, MIT 🧵 #MCP #textToSql #SqlToUi #SQL #OpenSource #DAB @tom_doerr @GithubProjects

Just published my new Udemy course: Chat with Your Business Data: LLM, RAG, SQL and NoSQL Build an AI data assistant with Text-to-SQL, RAG, Ollama, SQL Server, PostgreSQL, MongoDB, pgvector, FastAPI, and guardrails. #LLM #RAG #TextToSQL #AI

AI can generate SQL that runs perfectly and still returns the wrong number. The real problem may be your schema, joins and metric definitions. #sql #texttosql...Show more

🚀🤖Dynamic text-to-SQL for enterprise workloads with Amazon Bedrock Agents #GenerativeAI #TextToSQL #AmazonBedrock #DataInsights #CloudComputing

Trying to create a single AI that can answer all business analytics questions is challenging, if not impossible. - #artificialintelligence #texttosql

Day 85 of #100DaysOfLearningChallenge!🌉 1. 1 LeetCode 2. Today's highlight was this research paper: Innovative approach to building state-of-the-art text-to-SQL models For those curious to explore further, check out the link in the comments. #TextToSQL #AI #LLM #SyntheticData

Text-to-SQLの“6つの壁”をAIエージェントで突破！ 自然言語でのデータ分析がうまくいかない…そんな悩みをGoogle Cloudが解決します。 具体的な失敗パターンと解決策を解説！ 詳細はこちら👇 #TextToSQL #AIエージェント #GoogleCloud

📢Gretel Releases World's Largest Dataset @Gretel's release of the world's largest text-to-SQL dataset is revolutionizing AI training, unlocking new possibilities for businesses worldwide. Know more: #AI #SyntheticData #TextToSQL #OpenSource #AITraining

Data Exploration & Database Tools Kanaries/pygwalker → Turn any dataframe into an interactive Tableau-like UI → Best industry: Business intelligence, data analytics, fintech, internal tools, startups #TextToSQL #DataExplorer #OpenSource #DataScience

🚀🤖Build your gen AI–based text-to-SQL application using RAG, powered by Amazon Bedrock (Claude 3 Sonnet and Amazon Titan for embedding) #SQL #GenerativeAI #TextToSQL #DataAnalysis #NLP

🎉 Thrilled to share that my internship at Microsoft, titled "MAGIC: Generating Self-Correction Guideline for In-Context Text-to-SQL" has been accepted at the at AAAI 2025 (Main)! together w/ Christian Pölitz and Xinye Tang! #AAAI2025 #AAAI #NLP #Microsoft #SelfCorrection 1/9

@arian_ask Impressive work! Have you considered tò test your approach on other less known benchmarks? Zero-shot Performances seems to be overestimated for famous benchmarks. See how #DataContamination impact on #TextToSQL at

🔥: Check out the awesome benchmarking work from Alibaba DAMO Academy! Large databases and the grounding should never be underestimated. #DataAnalysis #TextToSQL @huybery Congrats 🎉 (sorry I cannot find others in twitter)!

Can LLM Already Serve as A Database Interface? A BIg Bench for Large-Scale Database Grounded Text-to-SQLs abs:

Key takeaways from the hands-on workshop on building a lightweight #knowledge layer with @neo4j! ✨Why vector search & Text2SQL offer incomplete context for agents ✨How Communities & Connections uncover patterns and create semantic layers ✨Building a knowledge layer on a lakehouse to turn mixed data into agent context Watch the workshop recording here👇 @neo4j @alexandererdl @emileifrem #Neo4j #GraphDatabase #DataScience #Community #NODES2026

The @neo4j webinar is officially live! I'm already tuned in for the hands-on session and live Q&A. Hop in right here: @neo4j @alexandererdl @emileifrem #Neo4j #GraphDatabase #DataScience #Community #NODES2026

We plugged Beam into @opencode, asked it to look at @UnslothAI, and create a fine-tuning notebook for the latest and smallest Gemma-4 model on a Text2SQL task – an out of distribution domain for Beam. The model successfully researches the model cards, Unsloth documentation, and available READMEs, and implements the fine-tuning logic and surrounding machinery. As a result, Beam is able to successfully finetune Gemma, increasing Gemma’s accuracy on its heldout test set by 66.5%.

@reflection_ai @opencode @UnslothAI Beam researching model cards and building a fine-tuning notebook for Gemma-4 Text2SQL out-of-distribution is exactly the agentic future we want.