LIVE STUDY / 001

What you imagine.

What we can build.

AI assistants · Learning systems · Intelligent software
MEET NYX

Meet Nyx.

Local AI models. An interface that makes sense.

01 / VISUAL GUIDANCE

A clearer next step.

Explanations and highlights. You stay in control.

02 / APPLE-NATIVE

At home on your Mac.

macOS first. iPhone and iPad support planned.

03 / SCREEN-AWARE

Starts with your screen.

Designed to understand visible context through OCR.

04 / LOCAL-FIRST

Intelligence, on device.

On-device AI. iCloud sync for chats and files is planned.

SCROLL TO EXPLORE
NYX / IN DEVELOPMENT
BY ARJIA

Introducing

COGNITIVE LAYER UTILITYv0.1.0a3 · PRE-ALPHA
EXPLORE THE BOUNDARY06 / 10

Look past the wording.

Move over the request to inspect the proposed change.

Tap to reveal the full inspection.

One rule. Three possibilities.

Choose an action. Watch the rule route it.

Example policy: reading is allowed. Changes need review.

CLULLM

Code changes today. Support for actions in other apps is planned.

ARES ENGINEBY ARJIA

MACHINE LEARNING · MARKET RESEARCH

Ares

Question
the signal.

An open-source engine that turns public market data into tested models and paper signals.

Move or touch to explore

Public Coinbase and Kraken candles. Checked together before they become a research dataset.

OPEN SOURCE / MITRESEARCH & PAPER INFERENCESCROLL TO EXPLORE

INSIDE THE ENGINE

Trust is a condition.
Not a default.

Ares checks the input before it trusts the output. Change the feed below. See what gets through.

DATA INTEGRITY LAB
INTERACTIVE SIMULATION
03 / ACCEPTED28 / 28 CANDLES VERIFIED
PUBLIC INPUTETH / USD
Coinbase Kraken
ENGINE DECISION
Ready for research

Fresh, complete data passes every check.

PASS / VALIDATED INPUT
FreshnessPASS
Venue agreementPASS
ContinuityPASS

Illustrative scenarios, including simulated recovery. No live exchange connection or orders.

EVIDENCE OVER INSTINCT

The future stays
out of training.

Learn from the past. Leave a gap. Test on what the model hasn’t seen.

Ares uses chronological evaluation with fees, slippage, and doubled-cost stress. Models earn their place through evidence.

Read the research protocol
WALK-FORWARD VALIDATION01 / 04
Train Gap Test
PASTTIME →UNSEEN

Window 01. Train on the earliest data, then evaluate on the next unseen period.

Select a window to follow the expanding training history.

BUILT TO BE EXAMINED

Open the hood.

Explore the research. Inspect the decisions. Make it better.

Explore Ares Engine on GitHub
ARJIA / ARES ENGINEResearch software. Paper signals only. No live orders or promise of returns.Back to the beginning ↑