All2WIKI Open Account

Source-grounded memory for serious LLM work

Turn books, docs, and URLs into an LLM-ready wiki vault.

All2WIKI converts raw resources into linked Obsidian and Markdown vaults with provenance, indexes, source pages, and agent guidance. Your coding assistant searches the vault first, then model memory, then the internet.

Create a vault See workflow

Built for source-heavy projects where repeated PDF uploads, long prompts, and drifting answers waste time and tokens.

70-90% target reduction in repeated source context for disciplined vault-first workflows.
2 LLMs optional dual-provider generation and merge for higher-value sources.
1 vault linked Markdown memory that agents can inspect without re-reading the whole book.

Workflow

From source pile to usable project memory.

All2WIKI is designed around the same operating flow we use for real technical libraries: validate first, analyse for price, process, audit, then package a vault that is ready for Obsidian and coding agents.

1

Validate sources

Check file readability, URLs, duplicates, size, and obvious bad inputs before spending paid tokens.

2

Analyse and quote

Choose free Ollama-backed analysis or paid Claude/OpenAI analysis for stronger cost and quality prediction.

3

Build vaults

Generate concepts, source pages, indexes, cross-links, manifests, and downloadable ZIP artifacts.

4

Audit and deliver

Run deterministic checks for missing pages, broken links, source coverage, and packaging consistency.

Why it helps

Stop asking the model to rediscover the same book.

Raw files are expensive context. A vault gives your assistant stable entry points, source references, and searchable concepts. The result is less repetitive prompting and a stronger path back to the exact source.

  • Traceable answers backed by source pages and provenance files.
  • Concept pages linked across books, notes, and project domains.
  • Agent instructions that enforce vault-first research behavior.
  • Master vaults for Java, Python, databases, DevOps, AI agents, and more.
memory/
memory/
  java-master-vault/
    concepts/
    sources/
    indexes/
    Agent_Coding_Guide.md
  python-master-vault/
  postgresql-master-vault/

Rule for agents:
1. Search vault first.
2. Use model knowledge second.
3. Research the internet last.

Pricing model

Transparent analysis, quote, and processing.

The service separates validation, analysis, and paid processing so customers know when tokens are being spent and what they are buying.

Free Analysis

Fast quote using subscription-backed Ollama/Qwen analysis. No customer charge for the analysis step.

Premium Analysis

Paid quote refinement using Claude/OpenAI when the source set is large, messy, or high value.

Standard Processing

Audited vault generation with deterministic repair, source checks, and packaging.

Extra Quality

Optional deeper verification, stronger merge checks, source-grounding review, and richer indexes.

Agent handoff

A vault your assistant can actually use.

Download the ZIP, open it in Obsidian, or place it in a project `memory/` folder. The vault is read-only source truth; agents can save derived notes in their own writable memory folders.

For developers

Turn Java, Python, PostgreSQL, Kafka, MongoDB, TypeScript, and AI-agent books into searchable coding references.

For teams

Give every assistant the same project memory instead of re-uploading the same manuals in every session.

For research

Keep source pages, page references, manifests, and audit reports next to the generated knowledge graph.

Build a memory layer before your next LLM project burns context.

Start with source validation, get a quote, and download a vault your coding agent can use immediately.

Open All2WIKI Portal