Developer Guide 2026 Updated

How to Build an Astrology App Like Co-Star in 2026 (Complete Developer Guide)

Co-Star has 30M+ downloads and a $100M+ valuation. Here is how to build your own AI-powered astrology app for a fraction of the cost using React Native and Vedika API.

Published: February 9, 2026 | 18 min read
How to Build an Astrology App Like Co-Star in 2026 - Developer Guide
This is a complete developer guide on building an astrology app like Co-Star in 2026. Co-Star has over 30 million downloads and is valued at over 100 million dollars. Using Vedika API, you can build a comparable app for 5,000 to 15,000 dollars instead of 50,000 to 150,000 dollars from scratch. The guide covers React Native setup, daily horoscope screens, birth chart visualization, AI chat interfaces, push notifications, and monetization strategies.

Table of Contents

  1. Why Co-Star Dominates the Astrology App Market
  2. The Opportunity: Build Your Own Version
  3. Core Features You Need (and How Vedika API Handles Each)
  4. Step-by-Step: Build a Co-Star Clone with React Native
  5. Monetization Strategy
  6. Cost Comparison: Build from Scratch vs. Vedika API
  7. FAQ

Co-Star is one of the most successful astrology apps ever built. With 30 million+ downloads, a $100M+ valuation, and a loyal user base that checks daily horoscopes every morning, it proved that astrology apps are a real business opportunity, not a niche curiosity.

The astrology app market is projected to reach $4.2 billion by 2028. Yet most developers assume building a competitive app requires a massive team, years of work, and six figures in funding. That was true in 2020. In 2026, it is not.

This guide breaks down exactly how Co-Star works, what makes it successful, and how you can build a competitive alternative using React Native, Node.js, and Vedika API for a fraction of the cost. Every section includes working code you can ship today.

1. Why Co-Star Dominates the Astrology App Market

Co-Star did not succeed because of better horoscopes. It succeeded because of product decisions that turned astrology into a daily habit. Understanding these decisions is essential before you write a single line of code.

Co-Star's Winning Formula

Product Design

  • Minimalist black-and-white UI -- stands out against colorful competitors. Feels premium and editorial, not mystical or gimmicky.
  • AI-powered daily horoscopes -- personalized content generated from actual birth chart data, not generic sun-sign predictions.
  • Push notifications -- the single most important retention mechanism. Short, punchy, personalized daily nudges that bring users back.
  • Social features -- compatibility matching with friends. Users invite friends to compare charts, creating viral growth loops.

Technical Foundation

  • NASA JPL ephemeris -- real astronomical data for planetary positions. Not lookup tables or approximations.
  • AI content generation -- machine learning models that produce unique, personalized predictions for each user.
  • Real-time transit tracking -- monitors planetary movements and generates relevant notifications when transits affect a user's chart.
  • Full birth chart engine -- houses, aspects, dignities, retrogrades. Not just sun signs.

Key insight: Co-Star's DAU/MAU ratio is among the highest in the lifestyle app category. The reason is push notifications tied to real planetary transits. Users open the app because the notification feels personally relevant, not because of generic "check your horoscope" reminders.

Co-Star monetizes through Co-Star+, a premium subscription offering hyper-personalized notifications, extended compatibility reports, and detailed transit breakdowns. The freemium model works because the free tier is genuinely useful, creating trust that converts to paid subscriptions.

The takeaway: you need an astrology engine accurate enough for real birth charts, an AI layer that generates personalized content, and a notification system tied to planetary transits. Building all of this from scratch is expensive. Using Vedika API, you get all three through a single integration.

2. The Opportunity: Build Your Own Version

Co-Star proved the market. But it has not saturated it. There are clear gaps a new app can exploit:

$4.2B

Projected astrology app market by 2028. Co-Star holds a fraction of this. Room for competitors is massive.

30M+

Co-Star downloads. Proves demand. But millions of users in India, Southeast Asia, and Latin America are underserved.

90%

Cost reduction using Vedika API vs. building from scratch. Ship in weeks, not months.

Market Gaps You Can Target

  • Vedic astrology focus. Co-Star is Western astrology only. Over 1 billion people in India and the diaspora use Vedic (Jyotish) astrology. No major app serves this market with AI-powered personalization.
  • Multi-language support. Co-Star is English-only. Vedika API supports 30 languages including Hindi, Tamil, Telugu, Bengali, Spanish, Arabic, and more. Build for 5 billion potential users instead of 1 billion.
  • Conversational AI. Co-Star delivers static daily horoscopes. Users cannot ask follow-up questions. With Vedika AI, you can build a full chatbot that answers questions like "When is the best time to start my business?" using their actual birth chart.
  • Matrimonial compatibility. Kundali matching for marriage is a massive market in India with no serious app-first player. Vedika API's matching endpoint handles Ashtakoot, Manglik detection, and doshas.

The recommended tech stack for building your Co-Star alternative:

// Recommended Tech Stack
const techStack = {
  mobile:     'React Native (Expo) or Flutter',
  backend:    'Node.js + Express',
  astrology:  'Vedika API (vedika.io)',
  database:   'Firebase Firestore',
  auth:       'Firebase Authentication',
  push:       'Firebase Cloud Messaging (FCM)',
  analytics:  'Mixpanel or Amplitude',
  payments:   'RevenueCat (iOS/Android subscriptions)',
  hosting:    'Google Cloud Run or Vercel'
};

3. Core Features You Need (and How Vedika API Handles Each)

Every feature that makes Co-Star compelling maps directly to a Vedika API endpoint. Here is the feature-to-API mapping:

Personalized Daily Horoscopes

What Co-Star Does

Generates AI-powered daily readings based on the user's complete birth chart and current planetary transits. Not generic sun-sign content.

Vedika API Solution

V2 Prediction API -- generates personalized daily, weekly, and monthly predictions using the user's birth data and current transits.

GET /v2/astrology/prediction/daily

Birth Chart Generation

What Co-Star Does

Calculates the user's complete natal chart -- planets, houses, aspects, dignities, and retrogrades -- using NASA JPL data.

Vedika API Solution

Birth Chart API -- Swiss Ephemeris (astronomical-grade) accuracy. Returns all 9 planets, 12 houses, ascendant, nakshatras, and more. Both Vedic and Western.

GET /v2/astrology/birth-chart

AI-Powered Insights

What Co-Star Does

Uses AI to interpret chart data and generate natural language readings. Users get "your day at a glance" summaries across categories (self, romance, work, etc.).

Vedika API Solution

Vedika AI Chat -- multi-agent AI swarm that answers any astrology question using the user's birth chart. Supports real-time streaming and 30 languages.

POST /api/vedika/chat

Compatibility Matching

What Co-Star Does

Synastry comparison between two charts. Users add friends and see compatibility scores across different life areas. Key viral growth driver.

Vedika API Solution

Matching API -- Ashtakoot matching (Vedic), synastry analysis (Western), Manglik detection, and doshas. Returns scores and detailed breakdowns.

GET /v2/astrology/matching

Push Notifications (Transit Tracking)

What Co-Star Does

Monitors planetary transits in real-time. When a planet moves into a house that affects the user's chart, it sends a push notification. This is Co-Star's biggest retention lever.

Vedika API Solution

Transit Tracking + Prediction API -- query current transits and generate AI-powered content. Combine with Firebase Cloud Messaging for push delivery.

GET /v2/astrology/transits

4. Step-by-Step: Build a Co-Star Clone with React Native

The following code examples form a working foundation. Each screen connects to Vedika API for real astrology data and AI predictions. Copy these into your Expo project and modify the UI to match your brand.

1 React Native Project Setup

Initialize an Expo project and install all required dependencies. The Vedika JavaScript SDK handles API authentication, request formatting, and response parsing.

# Create Expo project
npx create-expo-app CoStarClone --template blank-typescript
cd CoStarClone

# Install dependencies
npm install vedika                    # Vedika API SDK
npm install @react-navigation/native  # Navigation
npm install @react-navigation/bottom-tabs
npm install firebase                  # Auth + Firestore + FCM
npm install react-native-svg          # Birth chart rendering
npm install @expo/vector-icons        # Icons
npm install expo-notifications        # Push notifications
npm install react-native-reanimated   # Animations
Vedika api/vedikaClient.ts -- API Configuration
// api/vedikaClient.ts
import { VedikaClient } from 'vedika';

// Initialize once, reuse everywhere
const vedika = new VedikaClient(
  process.env.EXPO_PUBLIC_VEDIKA_API_KEY  // vk_live_xxxxx
);

export default vedika;

// Types for your app
export interface BirthData {
  datetime: string;    // ISO 8601: "1995-06-15T14:30:00"
  latitude: number;    // e.g., 19.0760
  longitude: number;   // e.g., 72.8777
  timezone: string;    // UTC offset: "+05:30"
}

export interface UserProfile {
  uid: string;
  name: string;
  birthData: BirthData;
  fcmToken?: string;
  createdAt: Date;
}

2 Daily Horoscope Screen

This is the screen users see every morning. It fetches a personalized daily prediction using the user's birth data and current planetary transits. The Co-Star-style layout splits content into categories: self, romance, work, and general.

Vedika screens/DailyHoroscopeScreen.tsx
// screens/DailyHoroscopeScreen.tsx
import React, { useEffect, useState } from 'react';
import {
  View, Text, ScrollView, StyleSheet,
  ActivityIndicator, RefreshControl
} from 'react-native';
import vedika from '../api/vedikaClient';
import { useAuth } from '../hooks/useAuth';

interface DailyReading {
  general: string;
  love: string;
  career: string;
  selfGrowth: string;
  luckyNumber: number;
  mood: string;
}

export default function DailyHoroscopeScreen() {
  const { user } = useAuth();
  const [reading, setReading] = useState<DailyReading | null>(null);
  const [loading, setLoading] = useState(true);
  const [refreshing, setRefreshing] = useState(false);

  const fetchDailyReading = async () => {
    try {
      // Vedika AI generates personalized predictions
      // based on the user's actual birth chart + transits
      const response = await vedika.chat.ask({
        question: 'Give me my daily horoscope for today. ' +
          'Break it into: general overview, love, career, ' +
          'and personal growth. Include lucky number and mood.',
        birthData: user.birthData,
        language: 'en'
      });

      // Parse AI response into structured sections
      const parsed = parseDailyReading(response.answer);
      setReading(parsed);
    } catch (error) {
      console.error('Failed to fetch daily reading:', error);
    } finally {
      setLoading(false);
      setRefreshing(false);
    }
  };

  useEffect(() => {
    fetchDailyReading();
  }, []);

  if (loading) {
    return (
      <View style={styles.loadingContainer}>
        <ActivityIndicator size="large" color="#6366f1" />
        <Text style={styles.loadingText}>
          Reading the stars...
        </Text>
      </View>
    );
  }

  return (
    <ScrollView
      style={styles.container}
      refreshControl={
        <RefreshControl
          refreshing={refreshing}
          onRefresh={() => {
            setRefreshing(true);
            fetchDailyReading();
          }}
        />
      }
    >
      <Text style={styles.date}>
        {new Date().toLocaleDateString('en-US', {
          weekday: 'long', month: 'long', day: 'numeric'
        })}
      </Text>

      <Text style={styles.title}>Your Day</Text>

      {/* Category Cards -- Co-Star Style */}
      <CategoryCard
        icon="sun" title="General"
        content={reading?.general}
      />
      <CategoryCard
        icon="heart" title="Romance"
        content={reading?.love}
      />
      <CategoryCard
        icon="briefcase" title="Career"
        content={reading?.career}
      />
      <CategoryCard
        icon="user" title="Self"
        content={reading?.selfGrowth}
      />

      {/* Mood + Lucky Number */}
      <View style={styles.quickStats}>
        <View style={styles.statBox}>
          <Text style={styles.statLabel}>Mood</Text>
          <Text style={styles.statValue}>
            {reading?.mood}
          </Text>
        </View>
        <View style={styles.statBox}>
          <Text style={styles.statLabel}>Lucky Number</Text>
          <Text style={styles.statValue}>
            {reading?.luckyNumber}
          </Text>
        </View>
      </View>
    </ScrollView>
  );
}

// Co-Star-inspired minimal styling
const styles = StyleSheet.create({
  container: {
    flex: 1,
    backgroundColor: '#000',
    padding: 20
  },
  date: {
    color: '#666',
    fontSize: 14,
    marginTop: 60
  },
  title: {
    color: '#fff',
    fontSize: 32,
    fontWeight: '700',
    marginTop: 8,
    marginBottom: 24
  },
  loadingContainer: {
    flex: 1,
    justifyContent: 'center',
    alignItems: 'center',
    backgroundColor: '#000'
  },
  loadingText: {
    color: '#666',
    marginTop: 12
  },
  quickStats: {
    flexDirection: 'row',
    gap: 12,
    marginTop: 16,
    marginBottom: 40
  },
  statBox: {
    flex: 1,
    backgroundColor: '#111',
    padding: 16,
    borderRadius: 12
  },
  statLabel: {
    color: '#666',
    fontSize: 12,
    textTransform: 'uppercase'
  },
  statValue: {
    color: '#fff',
    fontSize: 18,
    fontWeight: '600',
    marginTop: 4
  }
});

3 Birth Chart Visualization

The birth chart screen fetches complete planetary data from Vedika API and renders it using react-native-svg. This component draws a wheel chart with planet glyphs positioned by degree.

Vedika screens/BirthChartScreen.tsx
// screens/BirthChartScreen.tsx
import React, { useEffect, useState } from 'react';
import {
  View, Text, ScrollView, StyleSheet,
  ActivityIndicator
} from 'react-native';
import Svg, { Circle, Line, Text as SvgText } from 'react-native-svg';
import vedika from '../api/vedikaClient';
import { useAuth } from '../hooks/useAuth';

// Planet glyphs for chart rendering
const PLANET_GLYPHS: Record<string, string> = {
  sun: '\u2609', moon: '\u263D', mars: '\u2642',
  mercury: '\u263F', jupiter: '\u2643', venus: '\u2640',
  saturn: '\u2644', rahu: '\u260A', ketu: '\u260B'
};

interface PlanetData {
  sign: string;
  house: number;
  degree: number;
  isRetrograde: boolean;
  dignity?: string;
}

export default function BirthChartScreen() {
  const { user } = useAuth();
  const [chart, setChart] = useState<any>(null);
  const [loading, setLoading] = useState(true);

  useEffect(() => {
    async function fetchChart() {
      try {
        const result = await vedika.vedic.birthChart({
          datetime: user.birthData.datetime,
          latitude: user.birthData.latitude,
          longitude: user.birthData.longitude,
          timezone: user.birthData.timezone
        });
        setChart(result);
      } catch (err) {
        console.error('Birth chart fetch failed:', err);
      } finally {
        setLoading(false);
      }
    }
    fetchChart();
  }, []);

  if (loading) {
    return (
      <View style={styles.center}>
        <ActivityIndicator size="large" color="#6366f1" />
      </View>
    );
  }

  return (
    <ScrollView style={styles.container}>
      <Text style={styles.title}>Your Birth Chart</Text>

      {/* Ascendant */}
      <View style={styles.ascendantBox}>
        <Text style={styles.ascLabel}>Ascendant</Text>
        <Text style={styles.ascValue}>
          {chart.ascendant.sign} {chart.ascendant.degree.toFixed(1)}
        </Text>
      </View>

      {/* SVG Wheel Chart */}
      <View style={styles.chartContainer}>
        <Svg height="320" width="320" viewBox="0 0 320 320">
          {/* Outer ring */}
          <Circle cx="160" cy="160" r="150"
            stroke="#333" strokeWidth="1" fill="none" />
          {/* Inner ring */}
          <Circle cx="160" cy="160" r="100"
            stroke="#222" strokeWidth="1" fill="none" />

          {/* House dividers (12 lines) */}
          {Array.from({ length: 12 }).map((_, i) => {
            const angle = (i * 30 - 90) * (Math.PI / 180);
            return (
              <Line key={i}
                x1={160 + 100 * Math.cos(angle)}
                y1={160 + 100 * Math.sin(angle)}
                x2={160 + 150 * Math.cos(angle)}
                y2={160 + 150 * Math.sin(angle)}
                stroke="#333" strokeWidth="1"
              />
            );
          })}

          {/* Planet positions */}
          {chart.planets &&
            Object.entries(chart.planets).map(
              ([name, data]: [string, any]) => {
                const totalDeg = (data.house - 1) * 30
                  + data.degree;
                const angle = (totalDeg - 90) * (Math.PI / 180);
                const r = 125;
                return (
                  <SvgText key={name}
                    x={160 + r * Math.cos(angle)}
                    y={160 + r * Math.sin(angle)}
                    fill={data.isRetrograde ? '#ef4444' : '#fff'}
                    fontSize="14" textAnchor="middle"
                  >
                    {PLANET_GLYPHS[name] || name[0].toUpperCase()}
                  </SvgText>
                );
            })}
        </Svg>
      </View>

      {/* Planet Details List */}
      <Text style={styles.sectionTitle}>Planetary Positions</Text>
      {chart.planets &&
        Object.entries(chart.planets).map(
          ([name, data]: [string, any]) => (
          <View key={name} style={styles.planetRow}>
            <Text style={styles.planetGlyph}>
              {PLANET_GLYPHS[name]}
            </Text>
            <View style={styles.planetInfo}>
              <Text style={styles.planetName}>
                {name.charAt(0).toUpperCase() + name.slice(1)}
                {data.isRetrograde ? ' (R)' : ''}
              </Text>
              <Text style={styles.planetDetail}>
                {data.sign} {data.degree.toFixed(1)} | House {data.house}
                {data.dignity ? ` | ${data.dignity}` : ''}
              </Text>
            </View>
          </View>
        ))}
    </ScrollView>
  );
}

const styles = StyleSheet.create({
  container: { flex: 1, backgroundColor: '#000', padding: 20 },
  center: {
    flex: 1, justifyContent: 'center',
    alignItems: 'center', backgroundColor: '#000'
  },
  title: {
    color: '#fff', fontSize: 28,
    fontWeight: '700', marginTop: 60, marginBottom: 16
  },
  ascendantBox: {
    backgroundColor: '#111', padding: 16,
    borderRadius: 12, marginBottom: 20
  },
  ascLabel: {
    color: '#666', fontSize: 12, textTransform: 'uppercase'
  },
  ascValue: {
    color: '#fff', fontSize: 22, fontWeight: '600', marginTop: 4
  },
  chartContainer: { alignItems: 'center', marginBottom: 24 },
  sectionTitle: {
    color: '#fff', fontSize: 20,
    fontWeight: '600', marginBottom: 16
  },
  planetRow: {
    flexDirection: 'row', alignItems: 'center',
    backgroundColor: '#111', padding: 14,
    borderRadius: 10, marginBottom: 8
  },
  planetGlyph: { color: '#fff', fontSize: 24, width: 40 },
  planetInfo: { flex: 1 },
  planetName: { color: '#fff', fontSize: 16, fontWeight: '600' },
  planetDetail: { color: '#888', fontSize: 13, marginTop: 2 }
});

4 AI Chat Interface

This is the feature that goes beyond Co-Star. Instead of static daily readings, users can ask follow-up questions and get AI-powered answers grounded in their actual birth chart data. Vedika AI streams responses in real-time for a modern chat experience.

Vedika screens/AIChatScreen.tsx
// screens/AIChatScreen.tsx
import React, { useState, useRef } from 'react';
import {
  View, Text, TextInput, TouchableOpacity,
  FlatList, StyleSheet, KeyboardAvoidingView,
  Platform
} from 'react-native';
import vedika from '../api/vedikaClient';
import { useAuth } from '../hooks/useAuth';

interface Message {
  id: string;
  role: 'user' | 'assistant';
  content: string;
  timestamp: Date;
}

export default function AIChatScreen() {
  const { user } = useAuth();
  const [messages, setMessages] = useState<Message[]>([
    {
      id: '0',
      role: 'assistant',
      content: 'Ask me anything about your birth chart, ' +
        'career, relationships, or upcoming transits.',
      timestamp: new Date()
    }
  ]);
  const [input, setInput] = useState('');
  const [isTyping, setIsTyping] = useState(false);
  const flatListRef = useRef<FlatList>(null);

  const sendMessage = async () => {
    if (!input.trim() || isTyping) return;

    const userMessage: Message = {
      id: Date.now().toString(),
      role: 'user',
      content: input.trim(),
      timestamp: new Date()
    };

    setMessages(prev => [...prev, userMessage]);
    setInput('');
    setIsTyping(true);

    try {
      // Send question to Vedika AI with birth data
      const response = await vedika.chat.ask({
        question: userMessage.content,
        birthData: {
          datetime: user.birthData.datetime,
          latitude: user.birthData.latitude,
          longitude: user.birthData.longitude,
          timezone: user.birthData.timezone
        },
        language: 'en'
      });

      const aiMessage: Message = {
        id: (Date.now() + 1).toString(),
        role: 'assistant',
        content: response.answer,
        timestamp: new Date()
      };

      setMessages(prev => [...prev, aiMessage]);
    } catch (error) {
      const errorMsg: Message = {
        id: (Date.now() + 1).toString(),
        role: 'assistant',
        content: 'Unable to read the stars right now. ' +
          'Please try again.',
        timestamp: new Date()
      };
      setMessages(prev => [...prev, errorMsg]);
    } finally {
      setIsTyping(false);
    }
  };

  const renderMessage = ({ item }: { item: Message }) => (
    <View style={[
      styles.messageBubble,
      item.role === 'user'
        ? styles.userBubble
        : styles.aiBubble
    ]}>
      <Text style={[
        styles.messageText,
        item.role === 'user'
          ? styles.userText
          : styles.aiText
      ]}>
        {item.content}
      </Text>
    </View>
  );

  // Suggested questions for first-time users
  const suggestions = [
    'What does my birth chart say about my career?',
    'When is a good time to start a business?',
    'Tell me about my current Mahadasha period',
    'Am I going through Sade Sati?'
  ];

  return (
    <KeyboardAvoidingView
      style={styles.container}
      behavior={Platform.OS === 'ios' ? 'padding' : undefined}
      keyboardVerticalOffset={90}
    >
      <FlatList
        ref={flatListRef}
        data={messages}
        renderItem={renderMessage}
        keyExtractor={item => item.id}
        contentContainerStyle={styles.messageList}
        onContentSizeChange={() =>
          flatListRef.current?.scrollToEnd()
        }
        ListHeaderComponent={
          messages.length <= 1 ? (
            <View style={styles.suggestionsBox}>
              <Text style={styles.suggestLabel}>
                Try asking:
              </Text>
              {suggestions.map((q, i) => (
                <TouchableOpacity key={i}
                  style={styles.suggestChip}
                  onPress={() => {
                    setInput(q);
                  }}
                >
                  <Text style={styles.suggestText}>{q}</Text>
                </TouchableOpacity>
              ))}
            </View>
          ) : null
        }
      />

      {isTyping && (
        <View style={styles.typingIndicator}>
          <Text style={styles.typingText}>
            Analyzing your chart...
          </Text>
        </View>
      )}

      <View style={styles.inputContainer}>
        <TextInput
          style={styles.input}
          value={input}
          onChangeText={setInput}
          placeholder="Ask about your chart..."
          placeholderTextColor="#666"
          multiline
          maxLength={500}
        />
        <TouchableOpacity
          style={[
            styles.sendButton,
            (!input.trim() || isTyping)
              && styles.sendDisabled
          ]}
          onPress={sendMessage}
          disabled={!input.trim() || isTyping}
        >
          <Text style={styles.sendIcon}>↑</Text>
        </TouchableOpacity>
      </View>
    </KeyboardAvoidingView>
  );
}

const styles = StyleSheet.create({
  container: { flex: 1, backgroundColor: '#000' },
  messageList: { padding: 16, paddingBottom: 8 },
  messageBubble: {
    maxWidth: '80%', padding: 14,
    borderRadius: 16, marginBottom: 10
  },
  userBubble: {
    alignSelf: 'flex-end',
    backgroundColor: '#6366f1',
    borderBottomRightRadius: 4
  },
  aiBubble: {
    alignSelf: 'flex-start',
    backgroundColor: '#1a1a1a',
    borderBottomLeftRadius: 4
  },
  messageText: { fontSize: 15, lineHeight: 22 },
  userText: { color: '#fff' },
  aiText: { color: '#e5e5e5' },
  typingIndicator: { paddingHorizontal: 20, paddingBottom: 8 },
  typingText: { color: '#666', fontSize: 13, fontStyle: 'italic' },
  inputContainer: {
    flexDirection: 'row', alignItems: 'flex-end',
    padding: 12, borderTopWidth: 1, borderTopColor: '#222',
    backgroundColor: '#000'
  },
  input: {
    flex: 1, backgroundColor: '#111',
    color: '#fff', padding: 12, borderRadius: 20,
    fontSize: 15, maxHeight: 100, marginRight: 8
  },
  sendButton: {
    backgroundColor: '#6366f1', width: 40,
    height: 40, borderRadius: 20,
    justifyContent: 'center', alignItems: 'center'
  },
  sendDisabled: { backgroundColor: '#333' },
  sendIcon: { color: '#fff', fontSize: 20, fontWeight: '700' },
  suggestionsBox: { marginBottom: 16 },
  suggestLabel: {
    color: '#666', fontSize: 13,
    marginBottom: 8, textTransform: 'uppercase'
  },
  suggestChip: {
    backgroundColor: '#111', paddingHorizontal: 14,
    paddingVertical: 10, borderRadius: 20,
    marginBottom: 8, borderWidth: 1, borderColor: '#333'
  },
  suggestText: { color: '#ccc', fontSize: 14 }
});

5 Push Notification System (Backend)

This Node.js backend service runs daily via a cron job. For each user, it fetches the current transits affecting their chart from Vedika API, generates a short personalized notification using Vedika AI, and sends it via Firebase Cloud Messaging. This is the retention engine that keeps users coming back.

Vedika backend/notifications/dailyPush.ts
// backend/notifications/dailyPush.ts
import { VedikaClient } from 'vedika';
import * as admin from 'firebase-admin';

const vedika = new VedikaClient(process.env.VEDIKA_API_KEY!);
const db = admin.firestore();

/**
 * Runs daily at 7:00 AM via Cloud Scheduler.
 * Fetches personalized transit-based content for each user
 * and sends a push notification via FCM.
 */
export async function sendDailyNotifications() {
  // Get all users with FCM tokens
  const usersSnapshot = await db.collection('users')
    .where('fcmToken', '!=', null)
    .get();

  console.log(
    `Sending notifications to ${usersSnapshot.size} users`
  );

  const batchSize = 50;
  const users = usersSnapshot.docs;

  for (let i = 0; i < users.length; i += batchSize) {
    const batch = users.slice(i, i + batchSize);

    await Promise.allSettled(
      batch.map(async (userDoc) => {
        const userData = userDoc.data();
        try {
          // Generate personalized notification content
          // using Vedika AI + user's birth chart
          const response = await vedika.chat.ask({
            question:
              'Give me a one-sentence insight for today ' +
              'based on current planetary transits affecting ' +
              'my chart. Keep it under 100 characters, punchy ' +
              'and actionable. No greetings.',
            birthData: {
              datetime: userData.birthData.datetime,
              latitude: userData.birthData.latitude,
              longitude: userData.birthData.longitude,
              timezone: userData.birthData.timezone
            },
            language: userData.preferredLanguage || 'en'
          });

          // Send via FCM
          await admin.messaging().send({
            token: userData.fcmToken,
            notification: {
              title: 'Your stars today',
              body: response.answer.slice(0, 178)
            },
            data: {
              type: 'daily_horoscope',
              screen: 'DailyHoroscope'
            },
            android: {
              priority: 'high',
              notification: {
                channelId: 'daily_horoscope'
              }
            },
            apns: {
              payload: {
                aps: {
                  sound: 'default',
                  badge: 1
                }
              }
            }
          });

          console.log(`Sent to ${userDoc.id}`);
        } catch (err) {
          console.error(
            `Failed for ${userDoc.id}:`, err
          );
        }
      })
    );

    // Rate limit: pause between batches
    if (i + batchSize < users.length) {
      await new Promise(r => setTimeout(r, 1000));
    }
  }
}

// Cloud Scheduler entry point
// Schedule: "0 7 * * *" (7 AM daily)
export default sendDailyNotifications;
Pro tip: Use Promise.allSettled instead of Promise.all so one failed notification does not block the rest of the batch. Vedika API's 30-language support means you can send notifications in each user's preferred language.

5. Monetization Strategy

Co-Star uses a freemium model. The free tier drives downloads and daily engagement; the premium tier (Co-Star+) converts engaged users to subscribers. Here is how to replicate this model:

Freemium Tier Structure

Feature Free Tier Premium ($4.99/mo) Pro ($19.99/mo)
Daily horoscope
Birth chart
AI chat questions 3/day Unlimited Unlimited
Compatibility 1 match 5 matches Unlimited
Transit notifications
Dasha predictions
Yearly forecast
Multi-language English only 5 languages 30 languages

Revenue Math

With 100,000 free users and a 5% conversion rate at $9.99/month average: $49,950/month recurring revenue. Vedika API cost at Business plan: $120/month.

In-App Purchases

Detailed reports (career analysis, marriage timing, Varshaphal) as one-time purchases: $2.99-$9.99 each. High margin, low churn risk.

Advertising

Native ads between horoscope sections. Spiritual products, wellness brands, and meditation apps pay premium CPMs for astrology audiences.

RevenueCat tip: Use RevenueCat to manage iOS and Android subscriptions. It handles receipt validation, cross-platform entitlements, and analytics. Integrates with Firebase in 10 lines of code.

6. Cost Comparison: Build from Scratch vs. Vedika API

This is the math that makes the decision straightforward. Building Co-Star's core features from scratch versus using Vedika API:

Component Build from Scratch With Vedika API
Ephemeris engine (planetary calculations) $15,000 - $30,000 $0 (included)
AI prediction model (training + inference) $20,000 - $50,000 $0 (included)
Birth chart API $5,000 - $10,000 $0 (included)
Compatibility / matching engine $5,000 - $15,000 $0 (included)
Multi-language support (30 languages) $10,000 - $25,000 $0 (included)
Mobile app (React Native) $5,000 - $15,000 $5,000 - $15,000
Backend infrastructure $3,000 - $8,000 $500 - $1,000
Ongoing server costs (monthly) $500 - $2,000/mo $12 - $120/mo
Total Initial Cost $50,000 - $150,000 $5,000 - $15,000
Timeline 6 - 12 months 4 - 8 weeks

Bottom Line

Using Vedika API saves $45,000 - $135,000 in upfront development costs and 4 - 10 months in development time. The API handles the hardest parts: accurate astronomical calculations, AI model training and inference, and multi-language content generation. You focus on what matters -- the user experience, branding, and growth.

Frequently Asked Questions

How much does it cost to build an astrology app like Co-Star?

Building from scratch costs $50,000-$150,000 and takes 6-12 months. Using Vedika API, you can build a Co-Star alternative for $5,000-$15,000 in 4-8 weeks. The API handles birth chart calculations, AI predictions, daily horoscopes, and compatibility matching, which are the most expensive components to develop independently.

What tech stack does Co-Star use?

Co-Star uses React Native for mobile, a custom backend with AI integration, and NASA JPL ephemeris data for astronomical calculations. To build a similar app, you need React Native or Flutter for the frontend, Node.js or Python for the backend, an astrology API like Vedika for calculations and AI, and Firebase or Supabase for auth and data storage.

Can I build a Co-Star clone as a solo developer?

Yes. With Vedika API handling all astrology calculations, AI predictions, and birth chart generation, a solo developer can build a functional Co-Star alternative in 4-8 weeks. The API provides 120+ calculations, AI chatbot, daily horoscopes, and compatibility matching through simple REST endpoints and official SDKs for JavaScript (npm install vedika) and Python (pip install vedika).

How do astrology apps like Co-Star make money?

Astrology apps typically monetize through freemium subscriptions ($4.99-$19.99/month for premium features like unlimited AI chat, transit notifications, and detailed reports), in-app purchases for one-time readings ($2.99-$9.99), and native advertising from wellness and spiritual brands. Co-Star specifically uses Co-Star+ premium subscription for advanced features like hyper-personalized transit notifications.

What API should I use to build an astrology app?

Vedika API is the best choice for building modern astrology apps in 2026. It provides AI-powered predictions with Vedika AI, Swiss Ephemeris accuracy (astronomical-grade, 0.01 degree precision), 300+ Vedic and Western calculations, birth chart generation, compatibility matching, daily horoscopes, real-time streaming, and support for 30 languages. Plans start at $12/month with official JavaScript and Python SDKs.

How long does it take to build an astrology app like Co-Star?

Building from scratch with a team of 3-5 developers takes 6-12 months. Using Vedika API, a single developer or small team can build a functional MVP in 4-8 weeks. The API eliminates the need to build your own ephemeris calculations, AI model training, prediction engine, and multi-language content generation -- the four components that consume the most development time.

Start Building Your Astrology App Today

The astrology app market is $4.2 billion and growing. Co-Star proved the demand. Vedika API gives you the technology. What you build with it is up to you. Get your API key in seconds and start shipping.

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