The PageIndex Agent

Vectorless RAG for long, complex documents — accurate, traceable, context-aware, and cost efficient.

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Understands document structure. Uses fewer tokens.

PageIndex Agent will generate and understand your document’s tree structure, so it reads the relevant sections and keeps token costs low.

Annual report.pdf120 pagesBusiness overviewp. 1–24Financial resultsp. 25–78Revenue and costsp. 26–40Operating performancep. 41–52Risk factorsp. 79–120
Coming to PageIndex Agent soon

Finds the right pages. Gets answers faster.

With Page Search, PageIndex Agent quickly locates relevant pages and gets to the answer sooner.

p. 26p. 27p. 28p. 29p. 30p. 31p. 32p. 33p. 34p. 35p. 36p. 37p. 38p. 39p. 40Revenue and costsp. 26–40What drove revenue growth?only the relevant pages

Document Management

Organize documents in folders, or bring them together in collections with metadata.

Folder file system

Keep your documents in a familiar folder structure.

Workspace
  • Research
    • Acme
      • Annual report.pdf
      • Q4 earnings.pdf
      • Investor letter.pdf
    • Market reports

Collections with metadata Coming soon

Group related documents and give every file useful context.

Company research 3 documents
Example collection with document metadata
DocumentTypeYear
Annual report.pdfAnnual report2025
Q4 earnings.pdfEarnings2025
Investor letter.pdfLetter2025

Visual understanding, with visual citations

Understand charts, tables, and page layouts. See the evidence directly on the PDF, with the relevant region outlined.

ACME / SYSTEM DESIGNDocument intelligence01 / System architectureSOURCESPROCESSINGAGENTPDF documentsTables & figuresMetadataPage parserTree retrievalVisual contextQuery plannerReasoningCited answerFigure 1. Retrieval and reasoning across document sources.02 / Evaluation summaryMethodRecallLatencyFull document98.0%8.4sTree retrieval97.5%1.2sIllustrative example12

Read beyond the text

The evidence, in view.

Connect an answer to the diagram or table it comes from. Visual citations point to the specific region on the original page.

Select a citation to highlight its source.

Compatible and Scale with any LLMs

Bring your preferred LLM. PageIndex handles retrieval, so you can choose the balance of accuracy and cost that works for you — and switch models as your needs grow.

Accuracy and cost across selected LLMs using PageIndexAn illustrative pencil chart of DeepSeek, GPT Terra, Gemini, and Claude Opus. The blue line connects the Pareto frontier among these selected configurations. Positions reflect benchmark results; numeric scales are omitted.AccuracyHigherLower costHigher costDeepSeek V4.1 Flash (max)DeepSeek V4.1 FlashGPT-6.1 Terra (max)GPT-6.1 TerraGemini 4 Argon (high)Gemini 4 ArgonClaude Opus 5.5 (max)Claude Opus 5.5a model for every trade-off
Illustrative · frontier among selected modelsExplore the benchmark

Compare with Vector RAG

PageIndex gives LLMs a persistent structure to retrieve only the information they need.

vs Vector RAG

More accurate, at lower cost

Answer accuracy

40%60%80%100%top-10top-30top-50top-10092.1% · $134Voyage 4Voyage 4 LargeVoyage 4 LiteGemini Embedding 2OpenAI 3-largeOpenAI 3-smallPageIndex 100% · $110$0$25$50$75$100$125

Cost per 1,000 queries

63 questions on NVIDIA's 10-Ks, six embedding models at top-k 10 to 100. Every system answers with the same model and is graded against reference answers.

Run it anywhere

The same SDK runs on your laptop, on our cloud, or inside your own private cloud.

PageIndex Local

Open source, on your machine, with your own model key.

  • Documents never leave your disk
  • Cost-efficient indexing with PageIndex Flash
  • Text-based PDFs, read directly — no OCR
  • Open source, 35k+ stars on GitHub
View on GitHub

PageIndex Cloud

Managed indexing, storage, and retrieval. Nothing to run.

  • Our best indexing model, fully managed
  • Scanned files and image understanding
  • Hosted storage and file management
  • Free to start — 30k+ developers already building
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PageIndex Enterprise

All of Cloud, deployed in your own private cloud.

  • Runs in your VPC on AWS, Azure, or GCP
  • Documents and indexes stay in your cloud
  • customized integrated options
  • Audit logs, dedicated support, and SLA
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Simple usage billing for PageIndex Cloud#

Local stays free and open source. Start with $10 in free Cloud credits. No minimum monthly cost.

Free Starter

$10in free credits

  • No payment method required
  • Index up to 10,000 pages
  • 1,000 active pages free, every month
  • Unlimited retrieval on your active pages
  • Bring your own LLM
Start for free

Usage Billing Rates

I havepages
Indexingone-timeScanned and image-heavy documents work too. Line-level citations.$0.01 / page$10.00
Active pagesKept indexed and ready to query. First 1,000 free.$0.001 / page / mo$0.00/ mo
RetrievalNo retrieval fees on active pages. You pay your LLM provider directly.Unlimited

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