TPS AI
CoderPush helped Tien Phong Securities build TPS AI, an AI-powered product layer embedded into the TPS Mobile AI app. The experience combines AI Chatbot T'FOX with AI Insight to support investors across key moments in their mobile trading journey.
Banking & FintechExpertise
- AI product strategy for financial services
- Natural-language investment support
- Contextual AI insight surfaces in mobile trading flows
- Multi-method investment analysis experience
- Product engineering delivery for an AI-enabled launch
Overview
Tien Phong Securities (TPS, ticker ORS) is a Vietnam-based securities firm within the TPBank ecosystem, serving retail and corporate clients through brokerage and investment banking services.
As TPS strengthened its mobile trading product, the company identified a strategic opportunity: use AI to improve decision support, simplify the trading experience, and create clearer differentiation in a competitive securities market.
Rather than treating AI as an isolated add-on, CoderPush helped TPS shape TPS AI as a continuous decision-support experience designed to bring users from information to action with less friction and better context.
Challenge
TPS was facing three connected challenges:
- 01
Retail investors were overwhelmed by raw market data, delayed flows, and limited personalized guidance.
- 02
TPS needed clearer differentiation in a competitive securities market where product depth and user experience were becoming more important.
- 03
The team needed a product engineering partner that could understand the business problem, collaborate with internal stakeholders, and move quickly.
Solution
CoderPush's solution was to develop TPS AI as a core product capability within the new TPS Mobile AI app.
Instead of adding AI as a separate feature or chatbot tab, CoderPush helped TPS design an AI layer that could support users across the investment journey.
Architecture & Deployment
- Built TPS AI as a product layer embedded into the new TPS Mobile AI app.
- Developed AI Chatbot T'FOX as the conversational interface for natural-language investment support.
- Developed AI Insight as an embedded intelligence layer across the Home, Stock Detail, and Order Placement screens.
- Connected proactive insight surfaces with on-demand chatbot conversations so users can move from information to action with less friction.
AWS-backed infrastructure for financial AI
To support TPS AI as a production product capability, CoderPush used AWS as part of the infrastructure foundation for the system. This helped the team design TPS AI for secure data handling, reliable service availability, and scalable usage as more investors interact with AI features inside TPS Mobile AI.
For a financial product, the infrastructure decision mattered because AI was not only a demo layer. TPS AI needed to respond inside real user journeys such as market exploration, stock review, and order preparation. AWS provided a cloud foundation that could support these AI workflows with operational control, availability planning, and room to scale as adoption grows.
- AWS-backed infrastructure foundation for TPS AI.
- Designed for secure data handling in financial product workflows.
- Architecture prepared for high-availability AI experiences across investor touchpoints.
- Scalable foundation for growing investor usage inside TPS Mobile AI.
- Cloud environment suitable for production AI deployment and ongoing product evolution.
Multi-method analysis
- Fundamental analysis
- Technical analysis
- Quantitative analysis
- Sentiment analysis
Outcome
- Stronger market differentiation through AI embedded across the investment journey, not limited to a standalone chatbot.
- Better decision support for retail investors through contextual analysis and natural-language assistance.
- Higher product usability by making information more accessible at the moments where decisions happen.
- More practical value from AI by connecting proactive AI Insight with on-demand AI Chatbot support.
- Faster execution to market through close collaboration between TPS stakeholders and senior product engineers from CoderPush.