HPAR  ·  Hierarchical Path-Addressed Retrieval

Every business is leaking knowledge.
Silently. Expensively.
Continuously.

You've already paid for this knowledge. You just can't reach it.

It's in emails, docs, chats, decisions, and lessons from mistakes nobody wrote down properly. It exists. You just can't find the right version, in the right place, when you actually need it.

And when you do find something — you're not sure if it's still true.


This isn't a search problem.

You already have search. Google Drive, Notion, Slack, a CRM, an inbox.

The problem isn't finding text. It's knowing what that text means right now, in this situation.


Here's what it looks like in real life.

Pick a scenario

Someone key leaves your team. They had everything in their head — the workarounds, the client history, the why behind every decision. You do a handover. Three weeks later you realise half of it is already gone.

The knowledge existed. It just lived in one person, not in the system.


The hard part.

Things get busy. The catch is that nobody can maintain this perfectly on their own. Knowledge get added roughly, filed loosely, placed wherever made sense in the moment.

Over time, the system quietly falls apart. Not because people are careless, but because there was no system keeping it together.


What if the AI just kept it organised for you?

That's the idea behind HPAR.

You add things roughly. It places them correctly — right spot, right category, right level of detail.

You update one thing. It finds every place that concept lives and updates each one with the right language for that context.

Save once, update everywhere. Nothing missed. Nothing inconsistent.

When you update your pricing, it shouldn't require manual updates in every place it is used. It should just update everywhere — correctly, in the right language for each place.

Every piece of knowledge gets a full address:

Company → Products → Starter Plan → Pricing

That address isn't just a location. It's context. The AI knows exactly what role each node plays — because the full path above it is always visible.

The AI doesn't read everything. The path tells it where it is. It zooms out for broader context, drills down for detail, moves sideways to find related things — in order of what matters most.

That's how it knows exactly what needs to be updated:

Company
├── Products
│   └── Starter Plan
│       └── Pricing             ← single input
├── Sales
│   └── Pitch Deck              ← auto updated
├── Website
│   └── Pricing Page            ← auto updated
└── Proposals
    └── Standard Template       ← auto updated

When pricing is updated in plans, every surface reflects it — each in the right language for its audience.

The twelve properties that make this work

These are the architectural building blocks. Each is useful alone. Together, they're what makes HPAR different from anything built before.


It compounds.

Most systems degrade. More content means more noise, more outdated things, more places to look.

HPAR does the opposite.

Day one You capture what Sarah knows before her last day. It sits in one node.
Month three 200 nodes. The AI connects people, history, process, decisions. A question that took 20 minutes answers in seconds — because the structure already knows where everything relates.
Year one A new hire asks a question. The AI finds the answer and surfaces three things they should also know. The senior person who used to field that question is now free to do something harder.

Nothing gets left behind.

Big files. Videos. Databases. Live feeds. Any node in the tree can point to external data.

You're not storing everything in one place. You're mapping where everything lives — and what it means in context. The tree is a map, not a warehouse.


The stakes are real.

A nurse working from an outdated protocol. The update went out three months ago. The old version was never retired. Nobody knew it was still in circulation.

In a hospital, that gap isn't a process failure. It's irreversible.

The same structural problem exists in every organisation that holds knowledge across teams, locations, and time. The cost just looks different.

HPAR is designed for exactly this. From a solo consultant's working notes to an institution with thousands of people — same structure, same logic, same guarantee.


Why hasn't this existed before?

The structure is ancient. Outlines, hierarchies, trees — humans have organised knowledge this way for centuries.

The AI that can maintain it, navigate it, and propagate changes across it intelligently — that's new. Very new. HPAR gives it a better home.

Nobody had put the two together.
Until now.


This is an open idea.

The architecture is published — read it, use it, build on it.

Read the full research paper
Hierarchical Path-Addressed Retrieval (HPAR):
A Position Paper on Structural Grounding for AI Agents
Jeet Shah  ·  J33T.pro  ·  March 2026

The full architecture — all twelve properties, formal retrieval algorithm, and an honest comparison with flat RAG, GraphRAG, RAPTOR, and MemTree. Limitations and open questions included.

Read it here →

This came from running a business, not from a lab. — Jeet Shah, CraftyCrow.co

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This page is built the way HPAR works. You started at the top — broad, simple, human. The detail was there when you wanted it, hidden when you didn't. You chose how deep to go. That's the whole idea.