Five Whys
Three short chains covering need, market gap, and timing/execution.
1) Why build an AI CoPilot for retail traders?
- Why? Retail investors lack pro-grade decision support.→ Most Retail participants are self-directed and time-constrained due to their day jobs, and they need help turning data into disciplined actions.
- Why? Existing tools are either costly/complex or black-box alerts.→ High learning curves and opaque signals erode trust and adoption of any trading strategies.
- Why? Because multi-factor analysis is hard to do alone.→ Research Fundamentals, learn technical charts and price action, understand market sentiment, and decipher options flows. All live in silos, stitching them is non-trivial and requires experience.
- Why? Retail outcomes suffer from behavioral pitfalls.→ Overtrading, FOMO, and weak risk control measures drive avoidable losses.
- Why a CoPilot? It combines multi-factor AI + guardrails + explainability.→ Users stay in control, learn *why* trades happen, and execute with discipline.
2) Why hasn’t the market already solved this?
- Why? Most platforms optimize for either pros or passive investing.→ Active retail sits between: underserved on User Experience, education, and price.
- Why? Business models skew to high monthly fees or opaque signals.→ Prices exclude small accounts, opacity blocks trust, or the language used by systems requires time to learn.
- Why? Technical integration is a barrier.→ Real-time fundamentals, news NLP, and options flow require robust data pipelines.
- Why? UX rarely adapts to account size/experience.→ One-size-fits-all tools miss novice guardrails and advanced scale-up.
- Why is it now feasible? Broker APIs + mature AI lower the build/ops cost.→ Makes a transparent, affordable co-pilot viable for the mass market.
3) Why now (market timing) and why us (execution)?
- Why now? The retail base is large and active.→ >100M North America retail investors, and many of them trade tens of millions of stocks and options.
- Why now? AI and cloud are ready.→ Practical Natural Language Processing using LLMs + event models + low-latency infra enables multi-factor “always-on” assistance.
- Why now? Broker APIs = seamless execution.→ Aggregation or Direct Integration with brokerage systems is finally doable without becoming a broker.
- Why us? Persona-aware UX + built-in discipline.→ Small-account guardrails, high-capacity mode for advanced users, and a weekly plan, stops, and loss-pause discipline
- Why us? Transparent, affordable, defensible.→ Plain-English rationales, mass-market pricing, and a data flywheel (FQS/TMS/DVES/SMAS) that compounds.