Works with Cursor, Claude Code, Devin, and VSCode

Your AI doesn't have memory.
SUMA does.

K-WIL: gravity-based AI memory.

Receipts on every answer. Eight surfaces, one brain, any industry.

Persona-Octant Semantic Mapping

Memory in 3D.

Each sphere is one ingested memory. Spheres overlap where the same fact is visible to multiple personas. Same memory, multiple lens-views.

POSM 3D visualization — nodes × personas × topics with overlapping spheres

X = nodes (ingested memories) · Y = personas (lenses) · Z = Topics / Sub Topics. Each sphere's volume = its weighted reach across personas + topics + subtopics.

The Problem

Every conversation
starts from zero.

The Godfathers of AI didn't build the cure. Hinton resigned from Google in 2023 to warn about AI we can't audit. Bengio called it civilizational risk. LeCun says we don't understand what's inside.

They named the problem. We solved it.

  • 🧠Every chat starts at zero. Your AI forgot your codebase, your decisions, your style. You re-explain everything, every session.
  • 🔒No receipts. Why did it say that? Where did that come from? Black box in. Black box out. No audit trail.
  • 🌐Eight tools, eight amnesias. Cursor doesn't know what Claude Code knows. Each session is a stranger meeting a stranger.
"It's too late to stop this."
— Geoffrey Hinton, "Godfather of AI", Diary of a CEO 2024
AI in critical failure — memory loss
SYSTEM FAILURE
💸 The Cost

Every session, your AI forgets.
You waste 20 minutes re-explaining.

Yesterday's architecture decisions, last week's bug fix, the trade-offs you spent an hour debating — all gone the moment you open a new chat. Prompt caching doesn't fix this; cache TTLs expire, sessions reset. SUMA gives your assistant persistent, self-healing memory. K-WIL gravity injects the exact context that matters — instantly. No re-explaining. No flow-state loss.

The economics are real too. Below is one rough projection — your sprint cost depends heavily on caching and retrieval patterns.

Without SUMA

Black box. Re-uploads everything, every time.

Per turn
$0.47
Per sprint
$312
Per year
$15,600
12× CHEAPER
With SUMA

K-WIL gravity. Sends only what matters.

Per turn
$0.04
Per sprint
$26
Per year
$1,300

* Illustrative figures based on a 200-file project on Claude Code. Benchmarks measured on QUAD repository.

💸 The Cost

Where the 12× savings come from.

The math behind the previous slide. K-WIL gravity replaces brute-force re-uploading with semantically-targeted retrieval.

📦
200 files
$0.47/turn baseline
🌀
K-WIL Gravity
Recency × Emotion × Density × Semantic
📉
10–15× compression
on typical codebases
$300+ saved
per sprint, per dev
⚡ The Solution

One brain. Eight ways to plug in.

SDK, IDE, MCP, Mobile, Glasses, Browser, PM, Sandbox — same K-WIL engine, eight shapes. Same sk_live_ key. Same billing. Same graph.

🛠 The Solution

Four more surfaces. One brain.

AR overlays, weaver tools, offline twins, web absorbers — every entry point into the same Pāṇinian graph.

🔍 The Glass Box

The industry is building Black Boxes.

We built the Glass Box.

The Black Box (Standard LLMs)
The LLM acts as both the CPU and the Hard Drive.
Memories are baked into billions of invisible, autonomous weights.
If it learns something false or dangerous, you cannot find it or delete it.
When it answers, you get zero receipts. You hope it's not a hallucination.
The Glass Box (QUAD SUMA)
Separates Compute from Memory. The LLM is just a "Dumb" CPU. SUMA is the Enterprise SSD.
Memory lives in a deterministic, observable topological graph.
You can surgically find exactly where a memory lives and click delete.
Memory gains weight through human interaction, not autonomous updates. K-WIL gravity (Patent Filed USPTO 2026) keeps the graph anchored to reality.
🔍 The Glass Box

Receipts. Orchestration. No black box.

Every answer cites its source node. Every retrieval shows its math. The graph stays auditable end-to-end.

The Audit Layer: Receipts on Every Answer

Every answer points back to its exact source node. You catch the lie before it ships.

Question: "Where does user data leave the system?"
Black Box (ChatGPT)

"It exits via the API endpoints."

⚠ No source. Unverifiable.
Glass Box (SUMA)

"Through /api/export at rest_api.py:4521"

Node 402 · sphere: api
source_doc: rest_api.py
source_page: line 4521

What we DON'T claim

We don't fix the LLM. We don't solve alignment. We give you the receipts. Every answer points back to its source node. You catch the lie before it ships — that's more than any model offers today.

The Orchestration Layer

SUMA is the orchestrator, the router, and the memory. The LLM is just a pluggable utility — like a database connector. Swap Gemini for Claude in one config change. The brain stays. Only the voice changes.

🚀 The Vision

Memory anchored to humans,
not runaway weights.

From a developer's codebase to an enterprise's supply chain — same brain, any complex system. SUMA is the Hard Drive for AI. The Strait of Suma — where enterprise cognition flows.

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✓ 9 US Patents Filed (USPTO 2026) ✓ 12× cheaper than vanilla LLM · zero cold start
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