Cipta Nilawan AI processes market data through a layered predictive model and publishes the outcome of every signal. No curated case studies — the full log, updated per trading session, is open for review.
Dashboard view: signal accuracy, exposure by asset class, and drawdown, recalculated continuously during market hours.
Most trading tools report what already happened. Cipta Nilawan AI models probable near-term outcomes from live order flow, volatility structure, and cross-asset correlation, then ranks the resulting signals by statistical confidence. The shift is from reacting to price to positioning ahead of it.
Every recommendation passes through four distinct processing layers. Each layer is logged, so a given output can be traced back to the data that produced it.
Raw market feeds, order book depth, and macroeconomic releases are normalized into a shared time series, filtered for exchange-reported anomalies before entering the model.
Pattern recognition layers evaluate volatility regime, liquidity conditions, and historical analogues, producing a probability distribution rather than a single price target.
Position sizing and hedge ratios are adjusted against a defined risk budget, so signal strength and account exposure remain proportionate.
Final output is delivered as a structured recommendation with entry range, invalidation level, and confidence score — logged for later verification.
Instead of testimonials, Cipta Nilawan AI maintains a running record of every signal issued, including the ones that missed. The community can audit the log directly rather than take a claim on trust.
Every entry in the log carries an immutable timestamp and outcome status. Community members can flag discrepancies for review, and disputed entries remain visible until resolved rather than being removed.
See the full community log →The same predictive core serves short-horizon execution and longer-term capital allocation. What changes is the time window the model is asked to evaluate.
Day traders and analysts use Cipta Nilawan AI to rank intraday setups by model confidence rather than scanning charts manually. Signals refresh as new order flow arrives, with invalidation levels attached to each entry.
Portfolio-level risk is recalculated against changing correlation structures, flagging concentration before it becomes a liquidity problem. Alerts are triggered by threshold breaches, not by a fixed reporting calendar.
Longer-horizon allocation decisions draw on the same data layer, weighted toward macro and volatility-regime inputs. The output is a suggested rebalance, not an automatic trade — execution remains with the user.
Account and usage data are processed under Article 6(1)(b) GDPR for contract fulfillment. Data is stored on servers within the EU, and users can request export or deletion of personal data through the account settings at any time.
Latency from data ingestion to signal output varies by asset class and market conditions. The current figure for your account tier is displayed live inside the dashboard rather than quoted as a fixed number here, since network and exchange conditions affect it.
Accuracy is calculated per signal against its stated invalidation level and published in the transparency log, including losing signals. We do not exclude unfavorable outcomes from the public record.
No. The platform produces recommendations with defined entry, invalidation, and confidence data. Execution decisions remain with the user or their existing brokerage integration.
Access to Cipta Nilawan AI includes the full historical performance record, not a curated highlight reel. Request access to review live signals and evaluate the model on your own terms.