Vector AI is the built-in analyst that sits beside you during a session. It interprets results that
VECTOR has already computed and answers questions about them in plain language, and it can compute
extra statistics on your real data on demand. It is a tool for analysis: it is not a financial
advisor, and the final decision is always yours.
Where you find it
The Vector glyph
Next to the title of every module you will find the Vector glyph — the same chevron mark as the app icon. Click it to open the chat from wherever you are; it carries which module you opened it from as context.
The analysis card
On the Metrics section a compact card reads the current results. It stays dormant until you press it (no tokens are spent until then), then expands into a short reading of the numbers.
The drawer
Open Vector AI from the pill in the session status bar. It opens chat-first: you can ask a question straight away, with a few suggested prompts to get going.
The drawer keeps its conversation on the server, so the thread survives closing and reopening the panel
within the session.
Tabs, clearing and exporting
The chat is organised into tabs, so you can keep different lines of enquiry apart instead of piling
everything into one thread.
New tab
Press the + in the tab bar to open a fresh, empty tab for a different kind of request. Each tab keeps its own conversation and its own awareness of the session — asking in one tab doesn't mix into another. A tab is named automatically from its first message; you can keep up to eight open per session.
Switch and close
Click a tab to switch to it; click its ✕ to close it (there is always at least one open). Closing a tab discards that thread's memory.
Clear chat
The ⋮ menu in the header has Clear chat — it empties the active tab and resets its awareness, so you can start over without opening a new one.
Download
The same menu offers Download .md and Download PDF. Markdown saves the active tab as a plain-text file; PDF opens a formatted, print-ready view and uses your browser's print dialog — choose Save as PDF. Both capture whatever the tab holds: the session verdict (its prose, confidence level, sample note and suggested analyses) when you've loaded one, the conversation when you've asked questions, or both together. The two actions enable as soon as the tab has a verdict or at least one message — a verdict-only tab is exportable even before you type anything.
Conversations are session-scoped and temporary
Tabs and their memory live in the session (up to 24 hours) and are not saved to disk — they don't
survive a much longer gap or a backend restart. Download a tab if you want to keep its reasoning.
Asking questions
Type any question about your session. When the panel is empty you get a few suggested prompts — one of
them, "Give me an overview of the session," produces a structured reading (a short verdict with a
confidence level and next analyses to try). That overview is on demand: it loads only when you ask for
it, not every time you open the panel.
Ask in your own words
You don't need to phrase things a special way. "How often do these two lose on the same day?", "Which day
of the week is worst for Trend?", "What are the five worst days?" all work. If a question needs a number
that isn't ready, Vector AI computes it on your real trades rather than guessing.
What it can answer
Reading your results
What the metrics show, what is notable or fragile, and where a result may be misleading (small sample, possible overfitting, in-sample caveats).
Co-movement between strategies
How often two strategies lose together, win together or move in opposite directions, plus correlation, beta and how much they diversify each other.
Single-strategy stats
Sharpe, Sortino, win rate, profit factor, drawdown and the best and worst day for one strategy on its own.
Day-of-week patterns
P/L, win rate and number of trading days per weekday, for a strategy or the book.
Worst days and monthly P&L
The worst days with their dates, and the monthly grid with the best and worst month of each year.
Free-form day counts
Arbitrary questions like "in how many days does A lose while B gains?" or "average combined loss on the days both lose" — counted, summed or averaged, optionally grouped by weekday, month or year.
Time of day
"Which hour loses the most?", "average P/L of trades after 15:30" — grouped by hour, weekday, month or exit reason. This works only where your file carries the date and time of each trade (see limits below).
What-if experiments
"What if I double the weight of A?", "what if I exclude the worst strategy?", "what if capital were 50,000?" — Vector AI recomputes the metrics on that hypothesis and shows the effect versus today, without touching your live session.
Optimization (best configuration)
"How many contracts of A and B for the highest MAR?", "pick the subset of strategies that stays under $10,000 of margin and maximizes Sortino." Vector AI searches the space of integer contracts or strategy inclusion, subject to your constraints (max margin, max drawdown, number of active strategies), and reports the combination that would have maximized your chosen metric on the backtest — a global optimum for small spaces, or the best configuration found for large ones — together with how well it holds out-of-sample and under resampling. See Optimization for the full module.
An optimized configuration is an in-sample result
Searching for the "best" contracts or subset maximizes a metric on past data, which also fits noise —
this is the single most overfitting-prone thing the analyst can do. Vector AI always frames it as "the
combination that would have maximized X on the backtest", never as advice or a prediction, and always
reports the out-of-sample check (the configuration found on the first part of the history, then measured
on the later part) and a resampling band. Read those before trusting the headline number. The decision
to trade, and how, is always yours.
Acting on a proposal
When Vector AI optimizes, it does not silently change your workspace — it shows an actionable proposal
card under its answer, and you stay the final switch. The card shows the configuration it found and the
key metrics before and after, with three actions:
Apply to session
Writes the proposed weights into the live session. Recorded in the Timeline, so it is undoable.
Save as variant
Freezes the proposal as a variant and pins it to the comparison, without touching the live session — compare it against your current setup before committing.
Open in Optimizer
Opens the Optimization module pre-filled with the same configuration, to review the surface and leaderboard or tweak and re-run.
The card stays with the message: it survives closing and reopening the chat for as long as the session
lives.
Methodology guidance
Beyond the numbers, Vector AI helps with how to analyse: which tool or statistical method fits your
data — for example, for returns with volatility clustering and fat tails (typical of 0DTE options) it will
point you to FHS + GARCH or a skewed Student-t Monte Carlo model, with block bootstrap as the
robust default. This is educational guidance about the tools inside VECTOR, and it can link you to the
relevant page (for example Monte Carlo).
How it stays accurate
Every number is computed, never invented
The figures Vector AI cites are produced by the same engine that powers the charts and tables — never
estimated by the model. A what-if is a real recomputation of the backtest, not a guess. If Vector AI does
not have the data to answer precisely, it tells you and offers the closest thing it can compute, instead of
inventing a number.
What it will not do
Vector AI is not a financial advisor
By design, Vector AI stays descriptive and impersonal. It will not tell you to buy, sell, allocate or
withdraw real capital; it will not call a portfolio "ready", "safe" or "validated" for live trading; it
will not predict future returns; and it will not tailor its answers to your personal situation
(real capital, goals, risk tolerance, horizon). Configuration ideas are framed as experiments — "try
this and observe the effect on a metric" — never as recommendations. The decision to trade, and how, is
always yours. Past performance is not indicative of future results.
Limits to be aware of
Time of day needs per-trade times
Intraday questions require the entry date and time of each trade in your imported file. Strategies loaded as a daily P/L series or an equity curve don't carry per-trade times, so hour-of-day analysis isn't available for them — Vector AI will say so.
Monte Carlo is a suggestion
The chat doesn't run Monte Carlo itself (it's heavy). Vector AI points you to the Monte Carlo tool with the model that fits your data.
Small samples stay uncertain
With few trades or days, a strong-looking result is still low confidence — Vector AI flags this rather than overstating it.
Usage limits
To keep the service responsive for everyone, Vector AI is rate-limited per account: session verdicts up to 6/minute and 60/day, chat messages up to 10/minute and 200/day. Past a limit the API answers with a retry-later message; identical portfolios reuse cached verdicts without consuming budget.
Model
Vector AI runs on Anthropic Claude (US): the session verdict uses an Opus-class model, the card
and the chat a faster Haiku-class model. Only the numeric digest of your session is sent — computed
metrics, never raw trades, files or personal data (see Data & privacy).
Language
Vector AI replies in the language selected in Settings (Italian or English). Change it under
Settings and the next question is answered in the new language.