What it is
Tessera reports include AI-assisted written analysis that interprets your trade data in plain language. This layer turns statistics and condition breakdowns into readable findings and a narrative summary - scoped to the report you generated, not a general chat about markets.
What you can do
- Read findings (structured insights) and a narrative (markdown summary) on completed reports
- Trust that analysis stays within the purpose of the report type (behaviour vs conditions vs exits)
- Use written insights alongside the numeric tables and charts in the same report
How it works
Grounded in your data
Before any narrative is written, Tessera prepares statistics and evidence from your cohort: aggregated performance, session and time breakdowns, condition tables, or exit-placement slices - depending on report type. The analysis interprets that prepared material, not a live internet feed or unrelated accounts.
Scoped by report type
Each report type has a clear job. The analysis is validated so it does not stray:
| Report type | Analysis focuses on | Analysis avoids |
|---|---|---|
| Performance Review | Behaviour, sessions, timing, distribution, risk | Prescribing stop/target levels or regime “playbooks” |
| Regime Analysis | Where you win or lose by condition | Exit-distance prescriptions unrelated to context |
| Exit Placement | Stop and target distance ideas backed by excursion evidence | Unrelated entry filters or session-timing advice |
This keeps each report useful for its intended decision - not a mix of everything at once.
Quality and validity
- Minimum trade counts: Patterns are only highlighted when enough trades support them - reducing noise from one-off results.
- Market data gate: Reports that need price candles will not complete if coverage is too thin for the period; you will not get analysis built on missing charts.
- Validation: Outputs are checked against the report type so recommendations stay in scope.
What it is not
- Not a trading chatbot - it does not answer arbitrary questions or give live trade signals.
- Not financial advice - it summarises your historical cohort.
- Not a simulator - it does not replay stops or filter entries; use the simulator for that.
Limitations
- Analysis quality depends on cohort size, data quality, and market data coverage.
- Written summaries can still mis-emphasise a pattern you should cross-check in the tables.
- AI analysis complements - does not replace - your own judgement and forward testing.