Fragmented Research
Important assumptions and evidence are scattered across documents, datasets and code.
Paper-trading prototype in testing · Web MVP in development
Research faster. Test ideas. Audit every decision.
BW Digital Works is developing an AI-assisted quantitative research and decision-audit platform for independent researchers and small trading teams. The platform brings market research, strategy testing, paper-trading analysis and decision records into one auditable workflow.
Research workspace / simulated session
Conceptual product preview
The challenge
Quantitative research is powerful—but difficult to audit
Research notes, strategy code, backtesting results and trading logs often live in separate tools. When a strategy produces an unexpected result, it can be difficult to reconstruct what information was used, why a decision was made and whether the system followed its risk rules.
Unclear Decisions
Trading logs show what happened but often fail to explain why it happened.
Difficult Review
Reviewing strategy behaviour, backtesting results and risk-rule compliance can be slow and inconsistent.
The platform
One research and decision-audit workspace
The platform is designed to connect research, strategy development, testing and paper-trading review in a structured workflow.
Research Intelligence
Organise market research and turn evidence into structured strategy hypotheses.
Strategy and Code Review
Review quantitative logic, assumptions and code before testing or deployment.
Backtest Analysis
Summarise results, identify potential weaknesses and compare outcomes against the original hypothesis.
Decision Audit
Analyse paper-trading logs, explain strategy actions and check compliance with predefined risk rules.
Workflow
From research idea to auditable evidence
Step 1 — Research
Collect and structure relevant market research, assumptions and supporting evidence.
Step 2 — Test
Convert research into a testable strategy hypothesis and review the implementation.
Step 3 — Paper Trade
Run the strategy in a simulated environment with deterministic risk controls.
Step 4 — Audit
Review decisions, exceptions and risk-rule compliance through an auditable journal.
System boundaries
Clear separation of responsibilities
Claude-Assisted Work
- Research synthesis
- Structured reasoning
- Code and backtest review
- Trading-log analysis
- Decision explanations
- Audit-report drafting
Deterministic Systems
- Market-data processing
- Rule-based calculations
- Position and exposure limits
- Order-handling logic
- Hard risk controls
- System logging
Human Oversight
- Validate research assumptions
- Review model output
- Approve strategy changes
- Decide whether a strategy is suitable for deployment
- Monitor live operation
- Stop or override the system when required
Claude supports analysis and auditability. It does not independently control funds, override hard risk limits or approve live strategy deployment.
Product progress
In testing
In development
In development
Currently in development
Paper-Trading Prototype
Testing quantitative strategy workflows in a simulated trading environment.
Decision Journal
Building structured records that connect market context, strategy actions and risk-rule outcomes.
Web-Based MVP
Creating the first browser-based research and decision-audit workspace.
Claude integration in development
Responsible use
Built for transparent and responsible use
BW Digital Works is designing the platform around traceability, human oversight and clear system boundaries. AI-generated analysis should support informed review rather than replace professional judgement.
Traceable Outputs
Important conclusions should be connected to their source data and research context.
Human Approval
Material strategy changes and live deployment decisions require human review.
Independent Risk Controls
Hard trading and exposure limits are enforced outside the language model.
No Guaranteed Outcomes
Research and simulation results do not guarantee future investment performance.
BW Digital Works develops research and decision-support technology. Information provided through this website or future products is general in nature and does not constitute personal financial advice. The platform does not guarantee trading or investment performance.
The company
About BW Digital Works
BW Digital Works is a digital product studio developing practical AI-assisted tools for research, automation and decision transparency. Our current focus is building a more structured and auditable workflow for quantitative research and paper-trading analysis.
Bonnie Wong
Founder, BW Digital Works
Building digital products that combine practical automation, responsible AI and clear human oversight.
Get in touch
Interested in the product?
We are currently developing and testing the first version of the platform. Contact us if you are interested in following the project, providing feedback or discussing a potential pilot.