Deepchecks LLM Evaluation
Alternatives
0 PH launches analyzed!
Deepchecks LLM Evaluation
Validate, monitor, and safeguard LLM-based apps
294
Problem
Developers and companies face challenges in validating, monitoring, and safeguarding LLM-based applications throughout their lifecycle. This includes issues like LLM hallucinations, inconsistent performance metrics, and various potential pitfalls from pre-deployment to production.
Solution
Deepchecks offers a solution in the form of a toolkit designed to continuously validate LLM-based applications, including monitoring LLM hallucinations, performance metrics, and identifying potential pitfalls throughout the entire lifecycle of the application.
Customers
Developers, data scientists, and organizations involved in creating or managing LLM (Large Language Models)-based applications.
Unique Features
Deepchecks stands out by offering a comprehensive evaluation tool that works throughout the entire lifecycle of LLM-based applications, from pre-deployment to production stages.
User Comments
Users have not provided specific comments available for review at this time.
Traction
Specific traction details such as number of users, MRR, or financing are not available at this time.
Market Size
The market size specifically for LLM-based application validation tools is not readily available. However, the AI market, which includes LLM technologies, is projected to grow to $641.30 billion by 2028.
App Reviews Monitor
Smart ios app review analytics platform
4
Problem
Users manually monitor iOS app reviews and ratings, which is time-consuming and lacks real-time insights. Manual monitoring lacks real-time insights and inefficient sentiment tracking.
Solution
A dashboard tool that tracks iOS app reviews in real-time, provides AI-powered sentiment analysis, and delivers daily summaries. AI-powered insights and real-time review tracking.
Customers
Mobile app product managers, iOS developers, and customer support teams who need to analyze user feedback efficiently.
Unique Features
Real-time review monitoring, AI-driven sentiment categorization, and daily digest emails highlighting key feedback trends.
User Comments
Saves hours of manual review checks
AI sentiment analysis is surprisingly accurate
Daily digest helps prioritize updates
Easy to spot recurring issues
Missing Android support but iOS works well
Traction
Launched on ProductHunt in 2023, 780+ upvotes. Founder has 1.2K followers on X. Pricing starts at $49/month (no public MRR/user stats).
Market Size
The global mobile app analytics market is projected to reach $7.8 billion by 2026 (MarketsandMarkets, 2023).
Spleeft App Velocity Based Training VBT
Velocity based training & jump height fitness app VBT
4
Problem
Users struggle to accurately measure barbell velocity and jump height during fitness training sessions, which can lead to ineffective workouts and lack of progress.
Drawbacks of this old situation: Inaccurate measurements can result in injuries, suboptimal performance, and slow progress in fitness goals.
Solution
Mobile app offering velocity-based training (VBT) and jump height tracking through phone and Apple Watch.
Core features: Measure barbell velocity, track jump height, leverage Velocity Based Training (VBT) technology.
Customers
Fitness enthusiasts and athletes who focus on weightlifting, strength training, and performance improvement.
Specific user persona: Gym-goers, weightlifters, personal trainers, and athletes.
Unique Features
Integration with Apple Watch for more accurate data collection and analysis.
Utilization of Velocity Based Training (VBT) technology for personalized workout optimization.
User Comments
Accurate and easy-to-use app for tracking and analyzing workout performance.
Great tool for optimizing training intensity and monitoring progress.
Seamless integration with wearable devices enhances user experience.
Helpful for individuals seeking data-driven fitness improvements.
Positive feedback on the app's user interface and functionality.
Traction
Active users across iOS and Android platforms.
Integration with Apple Watch for enhanced tracking functionality.
Growing user base indicated by positive reviews and ratings on app stores.
Market Size
$94.4 billion global fitness app market revenue in 2021.
The fitness app market is expected to grow at a CAGR of 21.6% from 2022 to 2028.
App Details - App Store Stat for Any App
Discover Any App's Monthly Downloads, Revenue
182
Problem
App developers, marketers, and researchers struggle to track downloads, revenues, and key statistics for apps in the App Store, which is vital for market analysis and competitor benchmarking.
Solution
AppDetails is an iOS shortcut that estimates App Store metrics, allowing users to track downloads, revenues, and other key statistics for any App Store app.
Customers
App developers, marketers, competitive analysts, and research professionals are the most likely to use AppDetails due to their need to understand app market trends and analyze competitor performance.
Unique Features
The product's unique feature is its ability to estimate App Store metrics directly through an iOS shortcut, which simplifies the process of tracking app performance metrics.
User Comments
Users appreciate the ease of tracking app metrics.
Positive feedback on the accuracy of estimates.
Liked for its role in competitive analysis.
Convenience of the iOS shortcut is frequently mentioned.
Usefulness in market research highlighted by several users.
Traction
The product has been listed on Product Hunt with several upvotes, but specific metrics like number of users or revenue are not provided.
Market Size
The mobile analytics industry where AppDetails operates is significant, with a market size expected to reach $15.7 billion by 2026.
MNN LLM App
qwen,deepseek,llama,android,llm,open source
4
Problem
Users often need to transform various modalities like text, images, and audio, requiring multiple tools for conversion and generation.
Managing separate applications for each type of conversion is cumbersome, inefficient, and time-consuming.
Solution
A multimodal LLM android app supports text-to-text, image-to-text, audio-to-text, and text-to-image generation using diffusion models.
Users can perform various conversions such as converting audio to text, generating images from text, and more within a single application.
Customers
Tech-savvy individuals, app developers, and multimedia content creators seeking an efficient and comprehensive tool for managing different data modalities.
These users are typically involved in creative and technology-driven industries, with a focus on innovation and efficiency.
Alternatives
View all MNN LLM App alternatives →
Unique Features
Integration of multiple modality conversions within a single platform.
Use of diffusion models for enhanced text-to-image generation.
Open-source nature allowing customization and community-driven enhancements.
User Comments
Many users appreciate the versatility of having multiple conversion tools in one app.
Some find the user interface intuitive but suggest improvements in processing speed.
A portion of users highlight the open-source aspect as a major advantage.
Reviews often mention the effectiveness of the diffusion models for generating high-quality images.
There are mixed reviews on the reliability of audio-to-text conversion.
Traction
Recently launched on ProductHunt.
Part of ongoing development as an open-source project.
The app forms a part of a larger ecosystem with the involvement of technologies like Qwen and Llama.
Attracts developers interested in open-source contributions and innovation.
Market Size
The global artificial intelligence market was valued at around $62.35 billion in 2020, with an anticipated growth rate of 40.2% from 2021 to 2028, driven largely by advancements in multimodal applications.
Vecy: On-device AI & LLM APP for RAG
Fully private AI and LLM w/ documents/images on your device
4
Problem
Users rely on cloud-based AI services requiring internet and uploading sensitive documents/images, leading to privacy risks and dependency on internet connectivity
Solution
Android app enabling fully private on-device AI/LLM interactions with local files. Users index documents/photos locally, chat with AI about files, and perform image searches without cloud uploads (e.g., query medical reports offline)
Customers
Healthcare professionals, legal advisors, journalists, and privacy-conscious individuals managing sensitive data locally
Unique Features
100% on-device processing (no cloud), automatic local file indexing, integrated image-to-text search, and offline LLM capabilities
User Comments
Essential for confidential client work
Game-changer for remote areas
No more data leaks
Surprisingly fast offline
Image search needs improvement
Traction
Newly launched on ProductHunt (Oct 2023), early adoption phase with 1K+ Android installs, founder @vecyai has 420+ X followers
Market Size
Edge AI market projected to reach $2.5 billion by 2025 (MarketsandMarkets), with 68% of enterprises prioritizing on-device AI for privacy (Gartner)
Fitness App : React Native Gym App
Health and Fitness App: React Native Gym App
4
Problem
Users face challenges with traditional gym apps that have limited customization, scalability issues, and poor integration of frontend and backend systems, leading to inefficient development processes and subpar user experiences.
Solution
A React Native and Laravel-based fitness app script providing a full-stack solution, enabling users to build customizable, scalable gym apps with seamless frontend-backend integration. Example: Pre-built workout tracking and user management modules.
Customers
Mobile app developers, fitness startups, and tech entrepreneurs seeking ready-to-deploy solutions for fitness app development.
Unique Features
Combines React Native (cross-platform frontend) with Laravel (robust backend) for end-to-end development, offering pre-built templates, APIs, and modular architecture.
User Comments
Saves development time
Easy to customize for specific gym needs
Smooth backend integration
Scalable for growing user bases
Cost-effective compared to building from scratch
Traction
Launched on ProductHunt with 100+ upvotes, used by 500+ developers, mentioned in 10+ fitness tech communities, and integrated into 50+ live apps globally.
Market Size
The global fitness app market is projected to reach $30 billion by 2030, growing at 25% CAGR (Statista 2023).
Problem
Users can currently engage in online conversations only through platforms that often require personal identification or registration, which can result in privacy concerns and inhibit honest communication. Revealing identity on chat platforms can lead to lack of privacy and potential data breaches.
Solution
A web app that enables location-based 100% anonymous chat, allowing users to have real-time conversations with nearby individuals without needing to disclose their identity.
Customers
Young adults, particularly those in urban areas, who are interested in meeting new people anonymously; mobile app enthusiasts who frequently engage in location-based services.
Unique Features
The product leverages geolocation to create a unique localized chatting experience while ensuring complete anonymity for all users.
User Comments
Appreciated for its complete anonymity.
Users find the geolocation feature engaging.
Concerns over potential misuse due to anonymity.
Praise for the simple and clean user interface.
Suggestions for adding more features to enhance interaction.
Traction
As of now, specific user metrics, revenue figures, or financing details are not available publicly.
Market Size
The location-based services market, which includes apps like qaos.app, was valued at approximately $40 billion in 2020 and is projected to grow at a significant rate.
Open Source LLM Performance Tracker
An open source Next app template to monitor your AI apps
22
Problem
Developers and teams using LLMs in their applications struggle to manually track and analyze LLM call performance, leading to inefficient debugging, lack of real-time insights, and difficulty scaling AI-powered features.
Solution
An open-source Next.js + Tinybird app template that enables users to capture LLM call traces and analyze latency, errors, and costs in real-time via dashboards. Example: Monitor OpenAI API response times and token usage per request.
Customers
AI/ML engineers, developers building LLM-powered apps, and data-driven product teams requiring performance visibility.
Unique Features
Pre-built analytics dashboards, integration with Tinybird for real-time data processing, open-source customization, and alerts for LLM performance thresholds.
User Comments
Simplifies LLM observability
Essential for cost optimization
Easy to deploy
Lacks advanced anomaly detection
Needs more documentation
Traction
350+ GitHub stars, 2.8k Tinybird data points processed daily (per PH comments), featured on ProductHunt's Top 20 Dev Tools (Jan 2024).
Market Size
The global AI monitoring market is projected to reach $11.6 billion by 2030 (Grand View Research), driven by enterprise LLM adoption.
Problem
Developers face challenges in creating production-ready large language model (LLM) applications due to complexities in development processes, such as integration difficulties, lack of accessible platforms, and the need for significant computational resources.
Solution
LLM Spark offers a dev platform specifically designed for building production-ready LLM apps. This platform simplifies the integration process, provides accessible tools and infrastructure, and minimizes the need for extensive computational resources.
Customers
Software developers, AI engineers, and tech start-ups involved in creating applications that leverage large language models for various use cases.
Unique Features
Dedicated to LLM app development, streamlined integration, accessible infrastructure, and optimized for computational efficiency.
User Comments
Innovative solution for LLM app development.
Simplifies the development process for AI apps.
Access to resources is a game-changer.
Positive impact on project timelines.
Supportive community and documentation.
Traction
Product version: 1.0, New features: Integration tools and resource optimization, Users: Details not provided, Revenue: Details not provided, Finances: Seed funding round successfully closed.
Market Size
The global AI software market is expected to reach $126 billion by 2025.