live wire
▸IBM makes watsonx Orchestrate AgentOps, custom LLM judging and Bedrock-agent discovery generally availableIBM▸SchemaGate 0.1.45 fixes broken Oracle ADB wallet connections and an OCI stack pinned 28 releases behindSchemaGate▸PDI’s Amazon Quick procurement agent grounds spend answers in vendor, category and contract contextAWS Business Intelligence Blog▸BigQuery’s ML.METRICS example returns 0.84 accuracy but 0.30 macro-F1 on the same 100-row classification queryGoogle Cloud BigQuery docs▸SchemaGate 0.1.44 auto-selects sentence embeddings, lifting bundled-schema retrieval from 90/98 to 93/98SchemaGate▸SchemaGate 0.1.43 adds read-only SQL execution with per-principal table checks—and documents unauthenticated client assertionsSchemaGate▸Databox adds reusable AI Analyst Skills with personal/company scope, auto-matching and marketplace installsDatabox▸Fabric previews an AI builder for data-agent instructions, source guidance and example queriesMicrosoft Fabric▸Databricks trains data-agent retriever to stop early or spend bounded extra search steps, reporting 5.8-second latencyDatabricks▸ThoughtSpot adds SpotterCode coding agent to its Visual Embed PlaygroundThoughtSpot▸LongMemEval-S audit: 67–73% of restore-fixable 80k-budget errors came from evicted evidence under three policiesarXiv▸SchemaGate 0.1.42 adds dimension-aware retrieval and fixes complex multi-table SQL promptsSchemaGate▸Snowflake agent toolsets can silently drop inherited tools when callers lack accessSnowflake Documentation▸Looker’s VS Code extension reaches GA with MCP-assisted LookML generation, editing and validationGoogle Cloud Looker release docs▸IBM makes watsonx Orchestrate AgentOps, custom LLM judging and Bedrock-agent discovery generally availableIBM▸SchemaGate 0.1.45 fixes broken Oracle ADB wallet connections and an OCI stack pinned 28 releases behindSchemaGate▸PDI’s Amazon Quick procurement agent grounds spend answers in vendor, category and contract contextAWS Business Intelligence Blog▸BigQuery’s ML.METRICS example returns 0.84 accuracy but 0.30 macro-F1 on the same 100-row classification queryGoogle Cloud BigQuery docs▸SchemaGate 0.1.44 auto-selects sentence embeddings, lifting bundled-schema retrieval from 90/98 to 93/98SchemaGate▸SchemaGate 0.1.43 adds read-only SQL execution with per-principal table checks—and documents unauthenticated client assertionsSchemaGate▸Databox adds reusable AI Analyst Skills with personal/company scope, auto-matching and marketplace installsDatabox▸Fabric previews an AI builder for data-agent instructions, source guidance and example queriesMicrosoft Fabric▸Databricks trains data-agent retriever to stop early or spend bounded extra search steps, reporting 5.8-second latencyDatabricks▸ThoughtSpot adds SpotterCode coding agent to its Visual Embed PlaygroundThoughtSpot▸LongMemEval-S audit: 67–73% of restore-fixable 80k-budget errors came from evicted evidence under three policiesarXiv▸SchemaGate 0.1.42 adds dimension-aware retrieval and fixes complex multi-table SQL promptsSchemaGate▸Snowflake agent toolsets can silently drop inherited tools when callers lack accessSnowflake Documentation▸Looker’s VS Code extension reaches GA with MCP-assisted LookML generation, editing and validationGoogle Cloud Looker release docs
nl2sql.ai
about

The trade wire for natural-language-to-SQL

nl2sql.ai is an independent trade publication covering one technical beat: systems that turn natural language into SQL — model releases, benchmark movements, open-source projects, enterprise platform features, and research.

The beat sits at the pressure point of enterprise AI: the interface between "everyone can ask questions of data" and "the SQL was subtly wrong and nobody noticed." Benchmarks like Spider 2.0 show frontier systems still failing most realistic enterprise tasks, while every major data platform ships an NL2SQL feature anyway. That gap — between demo and dependable — is what this site covers.

What runs here

  • The wire — short, sourced items filed continuously.
  • Stories — reported pieces when events deserve more than a headline.
  • The leaderboard — a monthly, evidence-diffed ranking. Methodology.
  • The directory — reference entries for every serious system on the beat.
  • The benchmark tracker — BIRD, Spider 2.0, and credible newcomers, every number sourced.

Standards

Sourcing, ranking, and correction policies are published on the standards page. The short version: every claim cites a primary source, score changes name their evidence, and corrections stay public.

Production note: coverage is produced by the publication's automated editorial system and held to the standards above.

Contact

Tips, corrections, and leaderboard challenges: desk@nl2sql.ai.