Polign: Corrective Recall for Agents
Strongly typed memory matters
Get picks like this daily. Today's launch numbers, the top launches, AI and tech news, and a daily opportunity pick, straight to your inbox.
Want to reach these readers? Sponsor an issue.
When a user changes a preference, an agent has to stop using the old value without losing the record of it. Recall is a memory layer built on Polign. Each kind of fact declares how a new value applies, so a correction follows a rule rather than a model's judgment, and every earlier statement stays queryable.
PH · launched Sep 23, 2026 · 2 upvotes (top 26%) · 0 views
Niche: ai agent memory infrastructure · 350 launches, 16 in the last 7 days ▼ -27% · Explore this niche →
Category and tags
- Horizontal
- Data infrastructure
- Developer
- AI-native
- Commercial product
- User Experience
- Artificial Intelligence
- Tech
Visit website ↗ Source listing ↗
More like this: all 350 launches in ai agent memory infrastructure →
Could you build this?
No Polign is custom database and vector/hybrid search infrastructure (polign_db) built to run serverless, distributed, and directly on top of raw object storage with strong consistency guarantees. Developing a novel, scalable distributed storage engine with custom indexing and node-level encryption requires deep systems and database engineering expertise.
What it would actually take: Building polign_db requires designing a distributed storage engine using systems programming (Rust, C++, or Go) that indexes data directly onto object stores like S3/GCS using custom file formats (similar to LanceDB or DuckDB). It requires implementing transactional consistency models (e.g., MVCC or Raft-backed metadata), stateless caching layers, and high-performance ANN vector indexing with hybrid BM25 fusion. Deep expertise in distributed systems, database internals, and systems-level cryptography is essential.
Competitors
Other products that read as similar to this one : 122 launches clear the similarity bar, closest 8 shown.
Attention rank: #43 of 123 (itself plus its competitors, highest first, normalized so YC and Product Hunt are compared fairly).
Launched 268 days after the earliest competitor.
- REcall · github · 2026-09-29 · 21 upvotes · similarity 0.56
- memory-pulse · ph · 2026-09-09 · 1 upvotes · similarity 0.50
- Remembrane · hn · 2026-08-07 · 13 upvotes · similarity 0.49
- tensemem · ph · 2026-10-27 · 33 upvotes · similarity 0.48
- A lightweight, stateless database for agent memory · hn · 2026-08-26 · 36 upvotes · similarity 0.48
- Memorable: graph procedural memory for AI agents. Stop re-teaching your agents! · yc · 2026-09-17 · 17 upvotes · similarity 0.47
- Memori · ph · 2026-05-28 · 168 upvotes · similarity 0.47
- Brethof-Brain · ph · 2026-10-06 · 1 upvotes · similarity 0.46
The niche, labels, vibe code rating and competitor comparison on this page are analysis by Nicheloom. If you use them, please credit nicheloom.com. How you may use our data.