V7 gives AI agents institutional memory
How is the same entity named across three systems?That context lives in documents, data rooms, spreadsheets, emails, and internal tools: scattered, unresolved, and invisible to agents. For teams in finance, insurance, and real estate, retrieval accuracy within workflows is non-negotiable.After building a widely used computer vision accessibility app together, Rizzoli and Edwardsson started V7(opens in a new window) in 2018 to help companies teach AI systems how their businesses work. For Workflows, V7 Go uses GPT‑5.6 Terra and Sol for reasoning and tool use across complex, multi-step instructions that take humans dozens of hours to complete.
- ▪How is the same entity named across three systems?That context lives in documents, data rooms, spreadsheets, emails, and internal tools: scattered, unresolved, and invisible to agents.
- ▪For teams in finance, insurance, and real estate, retrieval accuracy within workflows is non-negotiable.After building a widely used computer vision accessibility app together, Rizzoli and Edwardsson started V7(opens in a new window) in 20
- ▪For Workflows, V7 Go uses GPT‑5.6 Terra and Sol for reasoning and tool use across complex, multi-step instructions that take humans dozens of hours to complete.
2 outlets in our directory ran this story, first to last over 6 hours. All of the coverage we found sits in one bucket: centre. That one-sidedness is itself worth noticing.
- ▪ How V7 gives AI agents institutional memory - OpenAI — Google News
Hacker News (AI / LLM) files mainly under ai. We currently carry 5,889 of its stories.
Story provenance
Source · retrieval · rights · ranking — open for full record
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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 | OpenAI |
| Canonical URL | https://openai.com/index/v7/ |
| Publication time | Mon, 21 Sep 2026 19:09:21 +0000 |
| Retrieval time | 2026-09-21T19:28:48.970Z |
| Last seen | 2026-09-21T19:28:48.970Z |
| 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 | P2hOye4GVeet · 2 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
September 21, 2026StartupHow V7 gives AI agents institutional memoryV7 turns company files into agent context, with GPT‑6 Astra reaching 89% accuracy on its hardest graph-query tests.Start building with OpenAICompany size: StartupRegion: Europe & UKIndustry: FinanceResults89%Accuracy for GPT-6 Astra on the hardest queriesResults78%Lower cost per document with GPT-5.6 LunaResults+11.6 ptsHigher accuracy with GPT-5.6 LunaLoading…ShareGiving agents the context to understand the whole businessGiving agents the context to understand the whole businessChoosing OpenAI to keep complex workflows on trackBringing what the business knows into ChatGPT and CodexGiving agents the context to understand the whole businessChoosing OpenAI to keep complex workflows on trackBringing what the business knows…
Excerpt limited to ~120 words for fair-use compliance. The full article is at OpenAI.
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