---
title: "What is agentic ingestion?"
description: "Why an AI agent should decide how your documents get indexed — not a fixed pipeline."
canonical: https://ocho.bot/docs/market-comparison/what-is-agentic-ingestion
last_updated: 2026-08-21
---

# What is agentic ingestion?

> Why an AI agent should decide how your documents get indexed — not a fixed pipeline.

How documents get *into* an AI system decides how good every answer *out* of it will be. Most tools use one fixed pipeline: split every file into chunks of the same size, embed them, done. That works until it doesn't — scanned PDFs come out empty, tables lose their structure, and a legal contract gets chopped by the same rules as a Slack export.

**Agentic ingestion** puts an AI agent in charge of that decision. The agent inspects your actual documents and designs an indexing strategy for them: whether they need OCR, whether tables and figures need visual retrieval, how to chunk, what to enrich, whether a knowledge graph will pay off.

## How it works in Ocho

1. **Tell it what you have (optional).** A short questionnaire asks what the    documents are, who'll query them, and what matters. Skip it entirely with    "just build it for me" if you'd rather not. 2. **The agent scans and proposes.** After analyzing the content, it presents    a strategy in plain language: its reasoning, plus capability cards —    visual retrieval, scanned-document OCR, context enrichment, knowledge    graph — each marked recommended or not, with trade-offs and cost. 3. **Refine it in chat.** Disagree? Ask the strategy agent to adjust —    "enable visual retrieval," "why is OCR off?" — and accept or dismiss its    proposed changes. 4. **Prove it works.** Built-in evaluations score retrieval quality against    golden queries (recall, precision, ranking). If a rebuild regresses, roll    back to the previous strategy.

## Why this beats the alternatives

Manual-capture systems (Obsidian, classic "second brain" methods) make *you* the ingestion pipeline — every note handwritten, every link hand-made. Fixed-pipeline tools (most AI notebooks) treat a scanned blueprint and a markdown memo identically and silently lose whatever doesn't fit. Agentic ingestion adapts to the corpus you actually have — which is the whole point of building on what you already own instead of starting fresh.

The numbers back this up: ingestion-side decisions move answer quality more than model choice. Anthropic measured **49% fewer retrieval failures** from [contextual enrichment at ingestion time](https://www.anthropic.com/news/contextual-retrieval) alone — one of several build-time choices the strategy agent makes when your corpus calls for it. For the full argument, read the deep dive: [What is agentic ingestion?](/blog/what-is-agentic-ingestion)

Try it: [Create and build datasets](/docs/library/create-and-build-datasets).

All docs: https://ocho.bot/docs

---

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