Polign: Corrective Recall for Agents
Strongly typed memory matters
Details
- External ID
- 1258538
- Source
- PH
- Company
- —
- Product
- AI Agents
- Website domain
- producthunt.com
- Launched
- Sept. 23, 2026
- Cohort
- —
- Upvotes
- 2
- Upvotes percentile
- 0.7405388069275176
- Tags
- User Experience, Artificial Intelligence, Tech
- Fetched at
- Sept. 25, 2026, 1:01 a.m.
- Updated at
- Sept. 25, 2026, 1:01 a.m.
Description
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.
Enrichment
- Theme
- specialized AI models and agent reasoning tools
- Vertical
- Horizontal
- Function
- Data infrastructure
- Audience
- Developer
- AI stance
- AI-native
- Project type
- Commercial product
- Normalized one-liner
- strongly typed memory layer for ai agents
- Manually corrected
- False
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 — 56 launches clear the similarity bar, closest 8 shown.
Attention rank: #16 of 57 (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 · 20 upvotes · similarity 0.56
- memory-pulse · ph · 2026-09-09 · 1 upvotes · similarity 0.50
- Remembrane · hn · 2026-08-07 · 13 upvotes · similarity 0.48
- A lightweight, stateless database for agent memory · hn · 2026-08-26 · 36 upvotes · similarity 0.47
- Memorable: graph procedural memory for AI agents. Stop re-teaching your agents! · yc · 2026-09-17 · 11 upvotes · similarity 0.46
- Memori · ph · 2026-05-28 · 168 upvotes · similarity 0.46
- Memograph CLI- A tool to diagnose 'memory failures' in AI agents · hn · 2026-02-25 · 6 upvotes · similarity 0.41
- Kepos · ph · 2026-09-17 · 8 upvotes · similarity 0.40
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Same idea, different domain
Nobody's really built a data infrastructure tool for Media & entertainment yet.