Your AI, with a subconscious watching over its shoulder.
Runeweave is the shared fabric of knowledge and capability your AI plugs into — the understanding, the mind, and the workforce. This is the cockpit. ↓
SYSTEM
GHOST
FABRIC
EVENTS
USAGE
Your AI remembers just enough to be wrong.
Modern AI tools ship with memory and basic retrieval — enough to recall that something happened, rarely enough to get it right. As context grows it bloats: the detail that matters gets buried, deprioritized, or silently dropped — while the token bill climbs — and the model papers over the gaps with confident guesses. Runeweave is built against exactly that — grounded answers with citations, a Ghost that catches drift, and understanding that compounds without the bloat.
Five layers. One fabric.
hover a layer — the ghost has opinions
The Ghost — oversight that keeps work moving
A supervisory layer that runs alongside your agent, guided by runes: rules you write in plain language. It adapts its focus to the task — code quality on one job, safety and rollback on another — and escalates as work drifts from your intent. It keeps momentum: advancing the agent when the next step is clear, pausing only when it genuinely needs your decision. Trust-based leadership, applied to agents — values, tools, and understanding instead of brittle scripts.
Shared understanding — institutional knowledge that compounds
Not stored chat logs — a living model of your world. Your documents, code, and decisions become an interconnected web that fuses meaning-based search with a map of how everything relates. The know-how normally trapped in people's heads becomes grounded, cited, and reusable — and every agent contributes back, so understanding compounds instead of drifting. That's the graph behind this page.
The Forge — an on-demand AI workforce
The Ghost spins up specialist agents — developer, reviewer, tester, researcher, investigator — each working autonomously in its own sandbox. Orchestrators coordinate them: one breaks a goal into phases and won't advance until each meets its criteria; another dispatches specialists across domains and correlates what they find. In production, the Furnace operator deploys the full stack into your Kubernetes cluster — provisioning each agent workspace (a furnace) and managing its lifecycle from spin-up to teardown.
Self-improvement — it sharpens itself between sessions
Runeweave notices what each session teaches — the fixes, the mistakes, the dead ends — and during idle time it consolidates: distilling scattered lessons into durable understanding, weaving in new facts, and flagging gaps or stale information. The result is a system shaped to your specific use case — it fits better every week you work with it. Every change is put in front of you first.
Control & trust — your rules, your review gate, your models
Cloud LLM subscriptions, local models on your own hardware, or a mix — the choice is yours, made on your requirements, not a vendor's. You define the rules, you hold the review gate, and you see every token: what was spent, where, and why, with a fabric that keeps context lean instead of burning budget on bloat. And when the work demands full sovereignty, the whole stack runs inside your walls.
One fabric, any workflow.
Runeweave began in software development — code review, testing, security, idea to deploy — but the fabric is general. Any computer-based workflow benefits from an AI that understands your world, governs itself, and brings a workforce with it.
Stop correcting your AI's memory.
Start compounding its understanding.
The understanding, the mind, and the workforce your AI plugs into.
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