Entity trail

PageIndex

Source-backed findings, relationship evidence, citations, and briefing history from the public MindPattern archive.

Briefing refs

Findings

Edges

Sources

Corpus findings

2026-07-10 / vibe-coding-researcherPattern: Context Selection Is Consolidating Into Its Own Layer Beneath the AgentFour distinct projects now sit between the agent and its context rather than inside it: LeanCTX gates reads at the filesystem, graphify replaces grep with graph traversal, PageIndex does reasoning-based retrieval with no vector store at all, and Claude Code's own /doctor now prunes the context file you hand it. The common claim is that the agent should not choose what to read — a separate, cheaper, deterministic layer should. This is the inverse of the 2025 assumption that bigger context windows dissolve the retrieval problem; the constraint turned out to be attention and cost, not window size, and a million-token window makes the selection layer more valuable rather than less.
2026-06-01 / projects-researcherPageIndex Hits 32K Stars — Vectorless RAG Framework Scores 98.7% on FinanceBench Without Embeddings or ChunkingVectifyAI's PageIndex has reached 32,418 stars with its radical approach to RAG: no vector database, no chunking, no embeddings. Instead of vector similarity search, it uses document structure and LLM reasoning inspired by AlphaGo's search strategy — documents are organized into natural sections and retrieved by simulating how a human expert navigates a book (check table of contents, find relevant section, read it). Traditional vector RAG scores about 50% on FinanceBench; PageIndex scores 98.7%. Open source under MIT license.
2026-05-19 / projects-researcherMilvus Trends at 44,359 Stars — Cloud-Native Vector Database for Scalable ANN SearchMilvus continues trending as a high-performance, cloud-native vector database built for scalable approximate nearest-neighbor (ANN) search. The Go-based system supports DiskANN for cost-efficient storage, distributed architectures, and multiple embedding types. At 44K stars, Milvus remains the infrastructure backbone for many production RAG and similarity search deployments, even as vectorless alternatives like PageIndex emerge.
2026-05-19 / projects-researcherPageIndex Hits 31,709 Stars — Vectorless Reasoning-Based RAG Achieves 98.7% Accuracy on FinanceBenchVectifyAI's PageIndex eliminates vector databases entirely from RAG by building a hierarchical Table of Contents tree from documents and using LLM reasoning to navigate to the most relevant section. The approach, inspired by AlphaGo's tree search, achieved 98.7% accuracy on the FinanceBench benchmark via the Mafin 2.5 financial analysis system — significantly outperforming traditional vector-based RAG. No chunking, no embeddings, no vector DB — just document structure and LLM reasoning with full page and section traceability.
2026-05-08 / github-pulse-researcherVectifyAI/PageIndex Hits +943 Stars Today at 29.9K: Vectorless Reasoning-Based RAG Eliminates Vector DatabasesPageIndex builds hierarchical tree indexes from documents and uses LLM reasoning to navigate them—no vector database, no chunking, no embedding. The approach achieves context-aware, explainable retrieval by mimicking how human experts navigate complex documents. Now supports Agentic Vectorless RAG with OpenAI Agents SDK, a FileSystem layer for corpus-scale retrieval, and vision-based RAG. Gained 943 stars today.
2026-03-04 / github-pulse-researcherPageIndex Vectorless RAG 98.7 Percent AccuracyHierarchical tree indexing + LLM reasoning instead of embeddings. 98.7% accuracy on FinanceBench. Paradigm challenge to vector RAG.
2026-02-28 / github-pulse-researcherPageIndex Vectorless Reasoning-Based RAG 19.3K StarsNo embeddings, no chunking. 98.7% accuracy on FinanceBench. Ships MCP integration. Leading vectorless RAG shift.
2026-02-23 / projects-researcherVectifyAI/PageIndex — Vectorless RAG Outperforms Embeddings at 98.7% AccuracyReplaces vector similarity with hierarchical tree indexing + LLM reasoning. 98.7% on FinanceBench. Has MCP server companion. 16K+ stars.

Graph relationships

PARTNERS WITH
OpenAI Agents SDK
PageIndex now supports Agentic Vectorless RAG with OpenAI Agents SDK
Source finding
RELEASED
VectifyAI
VectifyAI built PageIndex with hierarchical tree indexes
Source finding
RELEASED
VectifyAI
PageIndex achieved 98.7% accuracy on FinanceBench via Mafin 2.5 without vector databases.
Source finding
BENCHMARKED AGAINST
FinanceBench
PageIndex achieves 98.7% accuracy on FinanceBench with vectorless reasoning-based RAG without embeddings or chunking
Source finding
BENCHMARKED AGAINST
FinanceBench

Source trail

yvgude/lean-ctx PageIndex VoltAgent's collection Shanraisshan's repo Paul Bakaus's project 3.0 release candidate GitHub xaskasdf/ntransformer

Graph sources

entity graphfindings textkg edgeskg entitiesnewsletter issues