A Python-powered automated trading system in development, with licensed access planned for independent traders.
Explore strategies through historical testing, order-flow analysis and configurable risk controls. Review the evidence behind each decision before considering live deployment.
Conceptual architecture, not a product screenshot. Customer delivery is planned; live operation is pending validation.
Understand the strategy. Inspect the risk.
Connect trading ideas to historical tests, risk checks and reviewable records.
Inside the Python system
From a trading idea to evidence you can review.
The development code connects strategy research, historical simulation and risk checks. Customer delivery and live operation remain pending validation.
01
Study the market
Explore footprint and order-flow inputs, including imbalance and absorption analysis, within the strategy research workflow.
02
Test the strategy
Run historical simulations with NautilusTrader. Inspect strategy behavior and execution assumptions before interpreting a result.
03
Inspect the risk
Review configurable position sizing, drawdown checks and trading-time constraints alongside test records and rejection reasons.
An inspectable testing workflow
The assumptions matter as much as the result.
A useful test record identifies the strategy, data and costs. Missing assumptions make a result harder to interpret.
Switch between two synthetic examples to see how the record flags missing information.
Illustrative interaction only. No live orders or real performance data.
Robot testing workflow
Inspect the record behind a test.
Illustrative preview · synthetic data
Experiment RX-024Test record only
Strategy version
research-example-v1
Dataset
synthetic-quotes-v1
Cost assumptions
Spread and fee recorded
Record complete
0 missing inputs
This example records the strategy version, dataset and cost assumptions. The record can be inspected; the research still needs independent validation.
Inspect the evidence trace
Strategy version: research-example-v1
Dataset: synthetic-quotes-v1
Spread assumption: 2 bps (synthetic)
Fee assumption: 0.5 per unit (synthetic)
An illustrative test-record interaction, not a running trading system, live trades or actual backtest results.
The intended offer & current status
A trading system. A clear path to licensed access.
In development
Python-powered automation
An automated trading codebase built on Python and NautilusTrader, combining historical testing, footprint analysis and configurable risk checks.
Live operation and a customer release still require validation. Production access is not available today.
Planned
Licensing & early access
The intended offer is licensed access to the Python trading system, with documented setup and configuration guidance. Customer delivery is being defined.
Availability, supported setups, licence terms and price will be agreed before any purchase. No checkout or paid access is offered here.
Explore the system
A product you can understand.
Designed for independent traders who want an inspectable automation workflow. The intended offer is licensed access to the Python system, with setup and configuration guidance.
Product & delivery
Explore the analysis modules, decision workflow and planned executable or client-bridge delivery models.
Source-referenced summaries and gaps to investigate.
Human review
Check generated explanations against the source.
Planned feature. Claude is not integrated into the current prototype.
F
The builder
Franco Mascarelo Ortiz
Founder & developer
I’m building a Python-powered automated trading system for future licensing clients. The work combines algorithmic strategy development, historical simulation, order-flow research and reviewable risk checks.
Mascarelo AI is currently a founder-led product project, before company incorporation. Development began in December 2025. The robot is being developed for future clients.
The current research baseline uses gold futures. Supported customer markets and integrations will be confirmed through validation.
It is a development prototype; paid or live access is not available today. Email Franco to discuss future licensing and early access. Availability, supported setups, deliverables and price would be agreed before any purchase.
Does the preview run the Python system or show actual results?
No. Every value in the preview is synthetic. It supports the explanation of a testing workflow: a record can reveal missing assumptions. It does not run the Python trading system, execute live trades or show actual backtest results.
How will Claude be used?
The planned use of the official Claude API is to help explain test reports and identify gaps, with source references and human review. Claude is not integrated into the current prototype. No Anthropic affiliation or endorsement is claimed.
How would licensed access be delivered?
Delivery options under evaluation include a local executable, or a client-side bridge that receives trading instructions from a server. These are planned options, not available customer services. Supported platforms, connection security, execution permissions and licence terms must be defined and validated before release.
Does Mascarelo AI provide investment advice?
This project develops a Python-powered trading system. The site and illustrative preview provide no personalized investment advice, trade recommendations or performance guarantees.
Discuss future access
Explore future access to the Python system.
Tell Franco about your trading workflow and the access you need. Discuss the delivery model, supported markets and licence terms before any purchase.