Show HN: Lians AI, Token-bounded memory and evidence for AI workflows
Website - Docs - Install - Quickstart - Star Lians Reproducible benchmark evidence and offline quality gates RIAD-1: decision reconstruction benchmark · CI receipts Lians is the cross-platform decision evidence and reconstruction layer for regulated AI. It gives compliance, model-risk, and operational-risk teams one record of what an agent knew, what it retrieved, which policy governed it, which tools ran, who reviewed it, and what changed later. A firm can run agents across Bedrock, Azure OpenAI, Anthropic direct, and open-source runtimes while keeping one portable evidence record outside every provider.
- ▪Website - Docs - Install - Quickstart - Star Lians Reproducible benchmark evidence and offline quality gates RIAD-1: decision reconstruction benchmark · CI receipts Lians is the cross-platform decision evidence and reconstruction layer for
- ▪It gives compliance, model-risk, and operational-risk teams one record of what an agent knew, what it retrieved, which policy governed it, which tools ran, who reviewed it, and what changed later.
- ▪A firm can run agents across Bedrock, Azure OpenAI, Anthropic direct, and open-source runtimes while keeping one portable evidence record outside every provider.
Hacker News (AI / LLM) files mainly under ai. We currently carry 4,328 of its stories.
Story provenance
Source · retrieval · rights · ranking — open for full record
inspect →
Story provenance
Attribution is not the same as permission. This drawer separates discovery metadata, excerpts, WeSearch-generated summaries, reuse status, and whether the publisher receives the visit. Nothing here claims a legal grant the publisher has not made.
Record
| Original publisher | GitHub |
| Canonical URL | https://github.com/Lians-ai/Lians |
| Publication time | Mon, 10 Aug 2026 18:54:01 +0000 |
| Retrieval time | 2026-08-10T18:55:47.481Z |
| Last seen | 2026-08-10T18:55:47.481Z |
| Headline source | Publisher (no WeSearch rewrite) |
| Excerpt source | publisher body |
| Excerpt method | First ~120 words (~800 chars) of extracted publisher body, fair-use limited. |
| Summary | WeSearch · cerebras-chat (WeSearch summarizer) |
| Summary source text | contentText |
| Citation coverage | Summary is a WeSearch-generated derivative; primary citation is the original publisher URL. |
| Cluster | EHgDkcehJDUu · 1 stories |
| Cluster logic | Grouped by semantic title/content similarity across sources within a rolling window. Same-publisher template collisions are excluded from coverage comparison. |
| Ranking reason | Story pages are not engagement-ranked. Hub feeds use recency, with optional source-diversified chronological ordering (cap consecutive stories per source). No personalized ranking. |
| Publisher visit | Yes — open original |
| Substitutes article? | No — link-out required for full text |
Rights status (four layers)
WeSearch handling by dimension
| Indexing | May the item be indexed (stored, ranked, made findable)? | Allowed |
| Snippet | May a short excerpt of the publisher's text be shown? | Allowed |
| AI summary | May WeSearch generate its own short summary of the article? | Limited |
| Retrieval / RAG | May the content be exposed for third-party retrieval-augmented generation? | Not asserted |
| Model training | May the content be used to train AI models? | Not asserted |
| Commercial reuse | May the content be reused commercially? | Not permitted |
Basis: Derived from the published RSS/Atom feed. Contact: [email protected]. Reviewed: 2026-07-24.
Opening excerpt (first ~120 words) tap to expand
Website - Docs - Install - Quickstart - Star Lians Reproducible benchmark evidence and offline quality gates RIAD-1: decision reconstruction benchmark · CI receipts Lians is the cross-platform decision evidence and reconstruction layer for regulated AI. It gives compliance, model-risk, and operational-risk teams one record of what an agent knew, what it retrieved, which policy governed it, which tools ran, who reviewed it, and what changed later. The durable moat is neutrality. A firm can run agents across Bedrock, Azure OpenAI, Anthropic direct, and open-source runtimes while keeping one portable evidence record outside every provider. Every write is preserved as a governed temporal record and compiled into a typed memory artifact.
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Excerpt limited to ~120 words for fair-use compliance. The full article is at GitHub.