TPS needed an AI experience that could support real investor workflows, not just answer generic finance questions. The product had to fit a brokerage context where accuracy, latency, data boundaries, and user trust all matter.
The problem
Investors need timely explanations, research support, and guided next steps. A useful assistant has to understand Vietnamese financial language, expose its reasoning clearly, and stay close to the trading product rather than living as a detached chatbot.
What we built
CoderPush helped shape an AI assistant with specialist agent workflows for investor support and research. The system was designed around task-specific agents, streaming responses, and UX patterns that make the assistant feel connected to the trading journey.
Engineering shape
- Specialist agents for different investor intents
- Vietnamese-language interaction patterns
- Cloud-hosted inference path with production deployment constraints in mind
- User experience designed around reasoning, response speed, and handoff back into the product
Why it matters
Financial AI products need more than model access. They need workflow design, domain vocabulary, evaluation habits, and architecture choices that a compliance-aware product team can understand.
Result
TPS became a proof point for CoderPush's banking and fintech AI delivery: a production-oriented assistant with 12 specialist agents and a clearer path from investor question to useful product action.