OPEN_SOURCE ↗
X · X// 2h agoOPENSOURCE RELEASE
Postgres LLM pushes AI into database
JigsawStack’s Postgres LLM is an open-source Postgres trigger function that runs LLM calls directly on row changes and writes results back into columns. The new async queue-backed v2 keeps writes non-blocking and targets workflow-heavy tasks like translation, classification, summarization, OCR, and enrichment.
// ANALYSIS
This is less about “running a model in Postgres” and more about collapsing a common AI workflow into the database layer, which is where a lot of production state already lives.
- –The async queue design is the right call; it avoids turning LLM latency into application write latency.
- –It fits deterministic enrichment jobs far better than open-ended agent loops, especially when the output needs to land in structured columns.
- –The JSON-schema / structured-output angle matters more than the headline: bad LLMs near production data are mostly a data-quality problem, not a prompt problem.
- –It competes with app-layer automation stacks and low-code workflow tools, but wins on locality and simplicity when the database is already the system of record.
- –The tradeoff is tighter coupling to schema and trigger logic, so teams still need strong guardrails around retries, idempotency, and prompt changes.
// TAGS
llmstructured-outputautomationapiopen-sourcedevtoolpostgres-llm
DISCOVERED
2h ago
2026-05-07
PUBLISHED
3h ago
2026-05-07
RELEVANCE
8/ 10
AUTHOR
supabase