Financial decision-making requires quick, personalized analysis that most individuals cannot access without expensive advisory services. Traditional financial advisors are costly, slow, and not available 24/7. Users need instant, AI-powered insights tailored to their financial profile.
The Challenge: Build a scalable SaaS that delivers real-time financial analysis through a familiar interface (Telegram), with user behavior modeling, usage-based monetization, and structured AI outputs that users can act on immediately.
Goal: Create a fully automated financial advisor flow — from user query to AI-generated structured insight — delivered via Telegram with persistent user profiles and usage tracking.
The system is built as a webhook-based backend that orchestrates the entire pipeline: receiving user input from Telegram, processing it through OpenAI, storing structured data in PostgreSQL, and returning personalized responses.
// Express webhook handler for Telegram bot
bot.on('text', async (ctx) => {
const userId = ctx.from.id;
const message = ctx.message.text;
// 1. Get or create user profile (Financial DNA)
const user = await prisma.user.upsert({
where: { telegramId: userId },
update: { lastActive: new Date() },
create: { telegramId: userId, tier: 'free' }
});
// 2. Check usage limits (SaaS logic)
const usage = await checkUserLimits(user);
if (!usage.allowed) {
return ctx.reply('Daily limit reached. Upgrade for more.');
}
// 3. Process through OpenAI with user context
const analysis = await openai.chat.completions.create({
model: 'gpt-4',
messages: buildContext(user, message),
response_format: { type: 'json_object' }
});
// 4. Store interaction and increment usage
await prisma.interaction.create({
data: { userId: user.id, query: message, response: analysis }
});
// 5. Return structured response
ctx.reply(formatResponse(analysis));
});