AI reads the pulse of a scrip and predicts tomorrow’s or the next hour’s drift.
An Ayantege construct. Built for closed-door evaluation and research.
Not open. Not public. Not yours to enter.
A paradox in motion: it inherits the rigor of time-tested TA, yet withholds every chart, every indicator, every table.
No results are displayed. No spreadsheets surface.
Instead, by leveraging a pre-trained intelligence, STAS whispers its counsel — a glimpse of tomorrow, or the next hour.
An Ayantege platform.
Evaluation only.
Off-limits beyond this point.
It carries STAS in silence, delivering raw streams of TA and candle data only in coded forms — JSON or tokens, never in charts or sheets.
Here, selection is by your own criteria; interpretation is left to your own intelligence.
You may call upon your in-house AI or ours — the choice remains yours, the privacy absolute, the data untrespassed.
An Ayantege domain.
Not an open gate.
Its lattice is woven in Python, accelerated by CUDA currents from Nvidia.
At its core breathes LLaMA 3 — though other entities, GPT4All or HuggingFace-born, may take its place without disturbance.
Beneath, the trade-day itself is stored in TimescaleDB, though QuestDB may be summoned as an alternate chronicle.
All internal data flows in JSON; the AI receives it tokenized, prepared for inference.
Django shapes the visible façade, while replies emerge in HTML — always shadowed by JSON echoes, should deeper connections be required.
An Ayantege construct.
Not an invitation.
Like NoSQL broke away from traditional databases, STAStrade breaks away from conventional algos — trading without the Algo, yet with far better intelligence.
STAS thinks in silence and directs; your algo app only executes — the counsel and the command remain separate, by design.
STAS reads the datafeed, decides in silence, and directs the algo — intelligence beyond algorithm or manual hand.
In algo trading, code loops through your presets — the machine never thinks, only executes. In STAStrade, the AI itself thinks and directs by reading market feed.”
STAStrade preserves the unemotional precision of algos, yet removes the burden of constant setup and fine-tuning. What remains is execution guided by foresight, not by parameters.
The AImsara platform remains in its Alpha stage, accessible only to a small circle of invited researchers for evaluation. It is a closed system, not available for public access or use.