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The growing demand for personalized health tracking, especially among women, has paved the way for AI to revolutionize menstrual and fertility monitoring. Traditional methods often rely on rough estimates, but AI-powered ovulation trackers now offer up to 98% accuracy, far surpassing the 76% accuracy of calendar-based methods.
AI is proving to be a game-changer for ovulation tracking:
- It provides three times more accuracy than traditional tracking methods (according to an NIH study).
- It detects cycle irregularities up to five days faster than manual logging.
- It can reduce the time it takes to conceive by up to 30% for couples trying to get pregnant.
Take Clue, for example; this app leverages machine learning to:
- Predict menstrual cycles up to six months in advance with 90% precision.
- Link symptoms, such as cramps or acne, to hormonal shifts.
- Detect early signs of conditions like PCOS, alerting users before doctors can identify them in 22% of cases.
By analyzing vast amounts of user data, AI enables these trackers to predict cycles, identify irregularities, and offer personalized health insights, making ovulation tracking more accurate and accessible than ever before.
In this blog, we will explore the key steps to develop an AI app like Clue, drawing on our experience in the femtech space, where we have worked for over a decade. We specialize in building AI-driven apps that provide personalized health insights for women at every stage of life. This deep expertise makes IdeaUsher the perfect partner to guide you through the development process. Let’s dive in!
Overview of the Clue App
Clue is a femtech app designed to track menstrual cycles and ovulation, helping users manage and understand their reproductive health. With millions of users worldwide, Clue is available for iOS, Android, and watchOS devices.
How It Works
- Cycle Tracking: Users log details such as period days, symptoms, moods, and other cycle-related data. The app uses this information to predict future periods, PMS, and ovulation windows.
- Personalized Insights: Clue analyzes the logged data to offer personalized insights into menstrual patterns, fertility, and overall health. It tracks over 100 different experiences, such as pain, cravings, and energy levels, providing a comprehensive picture of reproductive health.
- Reminders & Alerts: Clue sends timely reminders for upcoming periods, ovulation, birth control, and other health-related events, helping users stay on top of their reproductive health.
- Privacy: Clue prioritizes user privacy, adhering to strict privacy laws like GDPR. The app does not sell or share user data, ensuring confidentiality.
- Customization: Users have the flexibility to tailor the app to track what matters most to them, whether that’s periods, symptoms, medications, or even pregnancy.
- Health Integration: For iOS users, Clue can sync with Apple Health, providing a more integrated view of overall health.
A Perfect Time to Invest in Developing an AI Ovulation Tracker
According to PersistenceMarketResearch, the fertility tracking apps market is experiencing rapid growth, expected to rise from US$81.39 billion in 2024 to US$206.34 billion by 2031, with a CAGR of 14.2%. This surge is driven by increasing infertility rates, delayed motherhood, greater awareness of reproductive health, and advancements in fertility tracking technologies.
Source: PersistenceMarketResearch
AI-powered ovulation trackers are leading the way, offering more personalized and accurate fertility insights. These devices combine advanced algorithms, temperature sensors, and hormone tracking to predict ovulation windows with higher precision than traditional methods.
Popular apps like Clue, Flo, Ovia, and Glow are incorporating AI to improve cycle and symptom tracking, helping users gain better insights into their fertility.
Wearables like the Ava Fertility Tracker, an FDA-cleared bracelet, also play a significant role by using various physiological signals and AI-driven analytics to pinpoint fertile days. Other innovative devices like the Mira Fertility Tracker, OvuSense, and Kegg are using hormone monitoring, body temperature sensors, and cervical fluid analysis, respectively, to offer even more personalized fertility tracking, all seamlessly syncing with mobile apps for real-time guidance.
Investing in an AI-powered ovulation tracker like Clue is a timely and profitable opportunity, especially with the growing focus on women’s health.
Apps like Flo and Ovia Health have set a high standard in the industry, showcasing the financial potential of this market. Flo has successfully reached over $200 million in annual revenue, largely through its freemium model and in-app purchases.
Similarly, Ovia Health, with its tailored fertility and pregnancy tracking tools, generated over $50 million in revenue in 2024. These examples highlight how investing in a well-designed, AI-driven app can lead to impressive financial returns.
Business Model of the Clue App
Clue is a leading science-based app focused on menstrual and reproductive health. Trusted by over 10 million active users and downloaded more than 100 million times globally, Clue is developed by Berlin-based BioWink GmbH. Available on iOS, Android, and watchOS, Clue’s business model is centered around accessibility and user privacy.
Subscription Model
Clue’s primary revenue comes from its paid subscription service, Clue Plus. As of May 2025, Clue has 1 million paid subscribers, more than doubling in just over a year. Clue Plus is priced at around one euro per month, offering users enhanced analysis, personalized predictions, and advanced cycle insights. This affordable, high-volume model ensures the app’s broad accessibility while maximizing global reach.
In-App Purchases
In addition to the subscription model, Clue offers in-app purchases. Users can access premium features like advanced tracking, deeper analytics, and additional content, enhancing their experience.
Free Tier
Clue offers a free version with core tracking and prediction features to attract a broad user base. This free tier helps retain users and convert a portion into paid subscribers over time.
Financial Performance
- Annual Revenue: Clue’s estimated annual revenue is around $22.8 million as of 2025, highlighting its significant growth in the digital health space.
- Revenue per Employee: With a workforce of 148 employees, Clue generates approximately $154,000 in revenue per employee annually.
- Growth: Clue’s paid subscriber base has doubled within a year, reaching 1 million by May 2025. However, the company reduced its employee count by 18% last year, signaling a focus on improving operational efficiency.
Funding and Investment
Clue has secured investment from notable backers, including Union Square Ventures, Mosaic Ventures, Groupe Arnault (LVMH), Brigitte Mohn (Bertelsmann), and entrepreneurs from Spotify, SoundCloud, and Dropbox.
While specific figures aren’t disclosed, Clue has attracted venture capital and strategic investments since its founding in 2012, aiding its growth and market expansion.
Key Stats
- User Base: Clue boasts over 10 million active users, with more than 100 million downloads globally.
- Paid Subscribers: The app has reached 1 million paid subscribers as of May 2025.
- App Store Performance: Clue maintains an impressive 4.8-star rating from over 2.5 million
Features We Add in an AI Ovulation Tracker Like Clue
After developing numerous femtech solutions, we’ve identified key features that users truly value. Through our experience, we’ve seen what resonates with users in ovulation and fertility tracking apps.
These are the features that have consistently been shown to improve user engagement and satisfaction. Here’s a look at the most popular features we’ve integrated into these apps:
1. Personalized Cycle Predictions
We’ve found that personalized cycle predictions are essential for users. By inputting their period dates and symptoms, the AI offers precise insights into future cycles, including ovulation and fertile windows. This feature helps users plan their fertility journey with confidence.
2. Fertility & Ovulation Tracking
Fertility and ovulation tracking are must-have features. Users can track key signs like cervical mucus and temperature, while the AI analyzes this data to predict ovulation days accurately. This makes it easier for users to time conception or track their cycle efficiently.
3. Symptom Logging & Pattern Recognition
Symptom logging has become a vital tool for understanding menstrual health. By tracking symptoms such as cramps, mood swings, or headaches, users can identify patterns over time. AI-powered insights help them manage their cycle more effectively and address any recurring issues.
4. Menstrual Health Insights
We’ve seen that menstrual health insights are one of the most appreciated features. By tracking period dates and flow, users gain deeper insights into their cycle length, regularity, and overall reproductive health. This allows them to make informed decisions about their well-being.
5. Pregnancy Mode
For users who become pregnant, pregnancy mode offers real-time updates on fetal development. This feature enables users to transition seamlessly from ovulation tracking to pregnancy tracking, providing ongoing support throughout their pregnancy journey.
6. Mood and Energy Level Tracking
Tracking mood and energy levels has proven to be very popular. This feature helps users understand how their emotions and energy fluctuate during their cycle. AI analyzes this data to offer insights, helping users manage mental and emotional health more effectively.
7. Customizable Tags and Notes
Customizable tags and notes allow users to track personal factors like “stress” or “exercise” that may affect their cycle. This level of customization has been a game-changer for users, providing a more personalized experience.
8. Advanced Cycle Analysis
Users love having access to detailed reports that break down their cycle length, ovulation timing, and fertility windows. The advanced analysis feature helps them better understand their cycle and identify any irregularities or trends that might need attention.
9. Integrations with Wearables
We’ve integrated wearable devices to sync health data like sleep patterns, heart rate, and body temperature. This integration offers a more comprehensive view of the user’s health, which helps in providing even more accurate predictions and insights.
10. Pregnancy Test and Early Detection Insights
By logging pregnancy test results, users can get AI-driven insights into their early pregnancy signs. This feature helps them assess their chances of being pregnant and gives them the information they need to move forward.
11. Notifications & Alerts
Timely notifications about upcoming periods, ovulation, and fertile windows are critical. Users appreciate this feature as it keeps them informed and on track with their cycle, ensuring they never miss important health milestones.
Development Steps for an AI Ovulation Tracker Like Clue
We specialize in developing AI-powered healthcare solutions, including advanced ovulation trackers. When working with clients to create a personalized AI ovulation tracker, we take a systematic approach to ensure the product is user-centric, secure, and scalable. Here’s how we develop an AI app like Clue,
1. Requirement Gathering & Research
We begin by understanding the core features needed for the AI ovulation tracker. This includes period tracking, ovulation prediction, and fertility insights. We focus on the target audience, whether they have regular cycles, are trying to conceive, or have health conditions like PCOS. We also conduct thorough market research to identify gaps and opportunities by analyzing competitors like Clue and Flo.
2. Feature Definition & AI Integration Scope
Next, we define the essential features that the app will offer, such as cycle tracking, symptom logging, and personalized health insights. We also establish how AI will be integrated, from fertility predictions to pattern recognition based on user data. This ensures that the AI provides truly personalized recommendations tailored to each user’s unique needs.
3. Technical Architecture & AI Model Design
We focus on building a strong backend infrastructure using reliable cloud hosting and databases to securely handle large datasets. The AI models are designed to predict cycles and provide insights using machine learning algorithms. At this stage, we also prioritize security and ensure that the app complies with privacy laws like GDPR to protect user data.
4. Frontend Development
Our frontend team develops a clean, responsive design that works seamlessly across all devices, including mobile phones and tablets. We prioritize ease of use, ensuring users can quickly input data and view their cycles. The UI is intuitive, and we focus on smooth navigation to minimize any friction during daily usage. Integration with APIs for real-time data tracking is also included.
5. Backend Development
The backend is designed with scalability in mind to ensure smooth performance, even during high traffic. We use databases like MongoDB or PostgreSQL to store user data, including cycle history and symptoms securely. When we develop an AI app like Clue, our team integrates AI models that process real-time data to generate personalized predictions while upholding strict data security and privacy compliance.
6. Data Collection & Analysis
We design user-friendly input fields to allow users to log their data easily, such as cycle dates, mood, and symptoms. This data is anonymized and used to train our AI models. By analyzing historical data, the AI learns to predict future cycles and detect patterns, improving its accuracy over time. This data-driven approach ensures personalized insights for each user.
7. UI/UX Design
We create an engaging user interface that encourages consistent data input. Clear visualizations of the menstrual cycle, ovulation windows, and health metrics are designed to help users easily understand their data. Personalization is key, as we provide tailored feedback and insights based on individual tracking.
8. AI Algorithm Development
We develop machine learning algorithms that predict ovulation windows based on the user’s cycle length and symptoms. The AI also analyzes other symptoms, like mood swings or cramps, and correlates them with fertility predictions. The goal is to provide personalized health tips, dietary suggestions, and lifestyle recommendations to improve overall well-being.
9. Development of Additional Functionalities
Beyond the core features, we incorporate additional functionalities, such as symptom tracking for conditions like PCOS and PMS. The app also sends reminders and notifications for key fertility events, like ovulation. We integrate support for wearable devices, allowing real-time tracking of heart rate, body temperature, and sleep patterns, providing a more holistic view of a user’s health.
10. Beta Testing & User Feedback
We release the app to a small group of beta testers to collect real-world feedback. The focus is on usability, functionality, and AI accuracy. We closely track user behavior to identify any friction points or missing features. Based on their input, we refine the app, ensuring it meets the needs of our client and provides a seamless user experience.
11. Integration with Third-Party APIs
To enhance the app’s functionality, we integrate third-party APIs that provide additional data, such as hormone levels and temperature sensors. We also consider adding medical advisory features, linking users to trusted healthcare resources or offering telemedicine options for consultations with experts.
12. Launch & Market the App
Before launch, we ensure the app is optimized for app store visibility through effective ASO. A targeted marketing campaign is created to reach a broad audience, using influencers, social media platforms, and partnerships with healthcare professionals. We also implement strategies for user acquisition, such as referral programs or freemium models.
Cost of Developing an AI Ovulation Tracker Like Clue
The cost required to develop an AI app like Clue depends on several factors, including the complexity of features, data integration, and regulatory requirements. Below, we break down the key cost components that influence the development of such an app.
Phase 1: Research, Planning & Discovery
| Task | Cost Range | Details |
| Market Research & Competitor Analysis | $500 – $2,000 | Analyze apps like Clue, Flo, Natural Cycles |
| Feature Prioritization & Scope Definition | $500 – $3,000 | Define MVP must-haves and phased features |
| Tech Stack Consultation | $500 – $2,000 | Decide on tools: Flutter, Firebase, TensorFlow, etc. |
| Legal & Compliance (Initial) | $500 – $3,000 | Address HIPAA, GDPR basics for user data handling |
| Wireframing & Flow Design | $500 – $2,000 | Low-fidelity mockups and navigation flow planning |
| Total for Phase 1 | $2,500 – $10,000 |
Phase 2: UI/UX Design
| Task | Cost Range | Details |
| User Research & Personas | $500 – $3,000 | Understand user behavior, define primary user types |
| Wireframing & Prototyping | $1,000 – $5,000 | Create clickable prototype for testing |
| Visual UI Design | $1,000 – $8,000 | High-fidelity screens for mobile platforms |
| Accessibility Compliance | $500 – $4,000 | Screen reader support, contrast compliance |
| Total for Phase 2 | $3,000 – $20,000 |
Phase 3: Backend Development & API Integration
| Task | Cost Range | Details |
| Database Design | $1,000 – $5,000 | Cycle history, user preferences, secure storage |
| API Development | $2,000 – $10,000 | Create backend logic and connect services |
| User Authentication | $1,000 – $5,000 | Secure login, user data isolation |
| Cloud Hosting Setup | $1,000 – $8,000 | AWS/GCP with HIPAA-compliant storage |
| Data Security & Encryption | $1,000 – $7,000 | At-rest and in-transit data encryption |
| Total for Phase 3 | $6,000 – $35,000 |
Phase 4: Feature Development (Including AI/ML)
| Feature | Cost Range | Details |
| Basic Cycle Tracking | $1,500 – $5,000 | Log periods, symptoms, moods |
| Simple AI Ovulation Prediction | $2,000 – $10,000 | Rule-based or ML-based fertile window prediction |
| User Profiles & Personalization | $1,000 – $4,000 | Preferences, cycle lengths, fertility goals |
| Notifications & Reminders | $500 – $2,000 | Customizable fertility and health alerts |
| Basic Data Visualization | $1,000 – $5,000 | Graphs, trends, heatmaps |
| Advanced AI Features (Optional) | $5,000 – $20,000 | Wearable data, deep learning, real-time personalization |
| Total for Phase 4 | $7,000 – $40,000 |
Phase 5: Testing & QA
| Task | Cost Range | Details |
| Functional Testing | $500 – $3,000 | Test core app logic |
| UI/UX Testing | $500 – $3,000 | Accessibility and design behavior validation |
| Performance Testing | $500 – $3,000 | Speed, crashes, load handling |
| Security Testing | $1,000 – $5,000 | Vulnerability scanning, data leaks |
| AI Model Validation | $1,000 – $5,000 | Accuracy, false positives/negatives |
| Total for Phase 5 | $3,500 – $15,000 |
Phase 6: Deployment & Launch
| Task | Cost Range | Details |
| App Store Submission | $500 – $3,000 | Publish on iOS/Android |
| Backend Deployment | $500 – $5,000 | Final cloud integration |
| Initial Marketing & ASO | $500 – $2,000 | App Store Optimization and soft launch |
| Total for Phase 6 | $1,500 – $10,000 |
Phase 7: Post-Launch Maintenance (Annual Cost)
| Task | Annual Cost | Details |
| Bug Fixes & Updates | $1,000 – $5,000 | Maintain compatibility with OS updates |
| AI Model Retraining | $2,000 – $10,000 | Enhance prediction accuracy with new data |
| Security & Compliance | $1,000 – $5,000 | Regular audits and encryption maintenance |
| Minor Feature Updates | $1,000 – $5,000 | Based on user feedback |
| Total Annual Cost | $5,000 – $20,000+ |
Total Estimated Cost: $10,000 – $100,000+
Please note that this is just an estimate, and the final estimated cost to develop an AI app like Clue can vary based on the specific features and customizations. The total estimated cost generally ranges from $10,000 to $100,000+, depending on the app’s scope and additional requirements.
Factors Affecting the Cost of Developing an AI Pregnancy app like Ovia Health
Developing an AI ovulation tracker comes with both common app development costs and unique factors that drive up the budget. The sensitivity of health data, complexity of biological predictions, and integration with specialized hardware all play a significant role.
Rule-Based vs. Machine Learning vs. Deep Learning
A basic AI model might use simple rules based on average cycle lengths. But moving to machine learning or deep learning increases both the technical requirements and costs. More advanced apps like Clue and Flo rely on machine learning to make more personalized predictions, which significantly raises the development cost.
Data Acquisition and Labeling
To ensure the AI delivers accurate predictions, it requires high-quality, labeled data. Collecting and labeling menstrual cycle data, especially for irregular cycles, is a resource-intensive task. This process is critical to the app’s functionality and adds considerable costs, as it involves confirming key data points like ovulation dates.
Model Training and Retraining
Training AI models is a resource-heavy task, requiring cloud computing and GPU instances. Additionally, ovulation tracker apps need to continually retrain their models with new user data. This ongoing need for updates to improve prediction accuracy adds extra costs throughout the life of the app.
Bias Detection and Mitigation
Biological data can be prone to biases, such as gaps in data for irregular cycles or certain ethnicities. To ensure fairness and accuracy, it’s necessary to detect and mitigate these biases. This requires specialized efforts, which is a unique and often costly challenge for health-related AI applications.
Core AI Technologies Used for Ovulation Tracking
Ovulation tracking has advanced beyond traditional methods, relying on AI and machine learning to provide more accurate predictions and personalized insights. Here’s a breakdown of the key technologies shaping the future of fertility forecasting.
Machine Learning Models for Period Prediction: LSTM vs. ARIMA
LSTM or Long Short-Term Memory Networks
LSTMs excel at capturing irregular cycle patterns, especially for users with conditions like PCOS. By retaining long-term context, they deliver accurate predictions, achieving 92-96% accuracy when trained with at least six months of user data. However, developing LSTM models requires a GPU-accelerated setup, making the cost roughly $15,000-$30,000.
ARIMA or AutoRegressive Integrated Moving Average
ARIMA is effective for predicting regular, 28-day cycles, but falls short for those with more irregular patterns. It’s less adaptive to lifestyle factors, such as stress or travel, which can affect ovulation. With a development cost of $5,000-$10,000, it’s a budget-friendly option for users with predictable cycles.
Pro Tip: Combining ARIMA for baseline predictions and LSTM for anomaly detection is a cost-effective hybrid solution, reducing development expenses by 40% while maintaining high accuracy.
How Neural Networks Improve Fertility Forecast Accuracy?
Traditional period trackers rely on simplistic averages, but neural networks offer significant advancements in prediction accuracy.
- Multimodal Data Fusion: Neural networks process multiple data types, such as basal body temperature, cervical mucus, and mood logs, simultaneously reducing false ovulation alerts by 28%.
- Adaptive Learning: Using self-correcting models like CycleNet, the system adjusts based on user-reported errors, improving over time.
- Edge AI Capabilities: With on-device models like TensorFlow Lite, neural networks provide real-time insights without relying on the cloud, ensuring greater privacy and no personal health information leaving the user’s phone.
The Role of Time-Series Analysis in Cycle Tracking Apps
Tracking menstrual cycles is a complex time-series problem due to their irregular and noisy nature. Top apps use several advanced techniques to make sense of this data:
| Technique | Purpose | Estimated Cost |
| DTW (Dynamic Time Warping) | Aligns irregular cycle data for meaningful comparison | $8,000 – $12,000 |
| Prophet (by Meta) | Handles missing data and predicts cycles | $3,000 – $7,000 |
| Spectral Analysis | Identifies hidden periodic patterns in long-term data | $15,000+ |
Blood Test Correlation
By integrating wearable data (like Oura Ring temperature readings and blood glucose levels) with time-series clustering, we increased prediction confidence intervals by 41% and boosted user retention by 33%.
Always visualize a “confidence score” for users, it helps them understand and accept the inherent uncertainties in predictions.
Conclusion
An AI ovulation tracker, like Clue, offers users personalized insights that help them better understand their fertility cycles, empowering them to make informed health decisions. The importance of such a tool lies in its ability to offer accurate predictions and support throughout the journey to conception. If you’re looking to develop an AI app like Clue that truly benefits your users, get in touch with us for a free consultation. Let’s discuss how we can bring your vision to life and create something that stands out in the market.
Looking to Develop an AI Ovulation Tracker Like Clue?
At Idea Usher, we specialize in bringing your AI ovulation tracker to life, offering precise fertility predictions, an intuitive user experience, and HIPAA-compliant security, ensuring your app is as reliable and empowering as Clue.
Why Choose Us?
- 500,000+ Hours of Expertise – Our ex-MAANG/FAANG developers build reliable, scalable AI solutions tailored to your needs.
- End-to-End Development – From AI model training to FDA-compliant deployment, we handle every step.
- Proven Track Record – Explore our latest projects to see our success in action.
Ready to disrupt femtech and launch a next-gen ovulation tracker? Let’s turn your vision into a market-ready app.
Get a free consultation today. Contact us now to get started.
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FAQs
A1: To develop an AI ovulation tracker app, you need to create a solution that accurately tracks menstrual cycles and predicts ovulation windows. Focus on integrating AI to analyze user data and offer personalized fertility insights. The app should be intuitive, easy to navigate, and secure, ensuring user privacy. Collaborating with healthcare professionals to validate predictions and ensuring compliance with regulations, such as HIPAA, will help build trust and accuracy.
A2: An AI ovulation tracker app should include features such as cycle tracking, ovulation prediction, and a fertility window calculator. It can also allow users to log symptoms, moods, and other health data to personalize recommendations. Adding features like reminders for fertility-related tasks, educational resources, and integration with fitness trackers for data on temperature and physical activity can further enhance its value.
A3: The cost of developing an AI ovulation tracker app depends on the complexity of the features you want to include. A basic app focused on cycle tracking and ovulation prediction will be less expensive to build than one that integrates advanced AI insights or wearable device data. Additional costs may arise from ongoing maintenance, updates, and ensuring the app complies with privacy regulations.
A4: AI ovulation tracker apps often make money through subscription models, where users pay for premium features like advanced fertility predictions, personalized advice, or access to expert consultations. In-app purchases, such as fertility products or services, can also contribute to revenue. Some apps may partner with healthcare providers or fertility clinics to offer additional services or products through affiliate marketing or sponsorships.
