Redefine strength training records with AI. Lütieji kicks off its angel round of financing.
An Overlooked Structural Opportunity
The daily records of strength trainers have long been in an awkward vacuum.
In the past decade, innovation in the fitness industry has concentrated on two ends: "content" and "tools". On the content side, online course platforms such as Keep and Daily Yoga have emerged. On the tool side, a large number of physical data tracking devices have appeared. However, all these solutions fail when it comes to the niche group of strength trainers.
They train 3 - 5 times a week, strictly follow a split training routine, and pay attention to weight, sets, state of exhaustion, and progressive overload. Their training needs to be seriously recorded, but the available tools are extremely scarce. General fitness apps aim for comprehensiveness, and the recording function is buried deep. Notepads and Excel cannot handle the complex structure of training data. No tool can transform training records from "dead data" into insights that can be interpreted and used to guide future training.
The emergence of AI makes this problem solvable. Training records are naturally structured text data - movements, weights, sets, feelings, and physical states. These dimensions are exactly what AI is best at handling. However, most of the "AI fitness" products on the market currently focus on visual AI scenarios such as motion detection and posture recognition, overlooking a more fundamental but core - demand - oriented direction: using AI to understand training records and generate judgments and suggestions from the data.
Lu Tie Ji was born out of this signal.
From "Recording Tool" to "AI Partner"
Lu Tie Ji is an AI application dedicated to strength training records, developed and operated by Jining Xiaofu Changliu Technology Information Consulting Co., Ltd. It doesn't pursue all - encompassing functions but focuses on one thing: ensuring that every training session is fully recorded, truly understood, and noticed.
"The current AI field is booming, but what really enters the lives of ordinary people still seems to be the question - and - answer form represented by Doubao and Yuanbao," said founder Tan Peiqi. "Many manufacturers are actively exploring the implementation of AI applications, but they are prone to falling into the misunderstanding of using AI for the sake of using it."
Lu Tie Ji has chosen a different path. It uses training records as an entry point to achieve deep integration of AI. When users habitually open Lu Tie Ji to record a set of training during their daily workouts, the AI is ready: from timing between sets, to post - training review and analysis, to dynamic adjustment of the next training plan. It's not an independent "AI chat window" but a companion and source of insights that permeates every training session.
The product logic consists of only four steps: record → accumulate → analyze → suggest. During training, it times between sets, synchronizes data to the cloud. The AI identifies training patterns and points out bottlenecks based on real historical data, and dynamically adjusts the next training plan. Diet management and physical data tracking serve this closed - loop system. They are not independent functional modules but complementary context to make the records more complete and AI analysis more evidence - based.
Differentiating Anchors: AI as a Fundamental Capability, Not a Function Button
Different from general AI fitness products, Lu Tie Ji has three differentiating anchors in its underlying logic.
First, AI is not a function but a fundamental capability that runs through the entire training process. Plan formulation, training recording, exhaustion notes, post - training review, and diet management - AI is not just a button but ensures that every link fits together naturally. Users don't need to input text or perform additional operations, and the AI works in the gaps between recording and analysis.
Second, the product's tone is defined by "real training scenarios" rather than imagination. The team has established a dedicated corpus and a high - frequency movement data structure for the fitness population. The AI provides not general health advice but actionable training insights based on users' real historical data. The product has won Xiaomi's "Golden Rice Award" and is applying for Apple's "Daily Selection" certification.
Third, it focuses on user asset accumulation rather than one - time use. Most competing products are single - machine tools sold through a one - time purchase. Lu Tie Ji is based on a subscription model to support continuous AI services and data accumulation. Once users' training history is structured into personal profiles, the migration cost is much higher than just exporting a few numbers.
Founding Team: Both Developers and Core Users
The team consists of two founders with a rare combination of capabilities: 10 years of development experience and years of systematic fitness practice.
Tan Peiqi serves as the founder, CEO, and product manager. With 10 years of client - side development experience, he has witnessed the technical architecture and full - link delivery of many products. He has 8 years of systematic fitness practice and maintains a split training routine 4 - 5 times a week. The product design, interaction logic, and function prioritization all stem from his real pain points when recording in the gym. "He doesn't just 'think for users'; he is a core user himself," an early investor commented.
Co - founder Luo Sixiang serves as the CTO, responsible for the server - side and AI data. With 10 years of server - side development experience, he is good at high - concurrency architecture and data processing. The dedicated fitness movement dataset and vector database he led to build for Lu Tie Ji are not just shell - based applications of general large models but high - quality vertical corpora accumulated based on real training scenarios, which evolve AI analysis from "correct but useless words" to "actionable training insights".
Core Barriers: Triple Moats of Interaction, Scenarios, and Data
Lu Tie Ji's barriers are built on three dimensions.
Interaction is a barrier. The product avoids function stacking. All interactions are based on real training habits, minimizing the learning cost. Competitors can copy the function list but find it difficult to replicate the smooth and intuitive interaction experience. "Minimizing the friction for users to record while collecting the most in - depth structured data makes this design itself a moat for data quality," Tan Peiqi explained.
Scenario bundling. Lu Tie Ji's strategic cooperation with offline gyms is the core way to make users "dependent". Scanning the code to enter the gym, renewing membership cards in the app, booking personal trainers online, and automatic push of training evaluations from the coach's end - this is not just a simple traffic cooperation but creates a high migration cost. Once users leave, they lose not only the recording software but also the non - transferable personal growth data accumulated through long - term interaction with coaches.
Data assets. The team has established a dedicated corpus and a high - quality movement dataset for the fitness population, which are truly scarce resources in the AI era. The subscription model provides stable income for long - term investment in AI capability building. As users' real training records accumulate, the thickness and value of data assets will continue to grow, feeding back into model iteration and forming a positive cycle of "more data → more accurate AI → better experience → more users".
Business Model: C - end Subscription as the Foundation, Bilateral Network as the Growth Engine
Lu Tie Ji's business model is advanced in stages.
In the first stage, C - end membership subscription is the foundation to solidify the user base.
In the second stage, a coach - student bilateral service will be launched soon. Students can book one - on - one courses with certified personal trainers in the app and automatically receive training evaluations written by coaches after class. Coaches can manage students, record training feedback, and build their personal teaching reputation through the coach - side tool. Courses are charged by the hour, and the platform takes a service commission. Once the bilateral relationship is established, the migration cost is extremely high, which is fully in line with the core barriers of "scenario bundling + data assets".
In the long run, paid fitness content, corporate health plans, brand co - branding and ecological monetization, gym traffic diversion, and SaaS management will be the natural results of endogenous growth.
Financing Progress and Future Plans
In this round of financing, 1.2 million RMB was raised by giving up 15% of the shares. The use of funds is clear: 40% will be invested in product R & D and AI capability building, 30% in strengthening the core team (backend/data engineers, user growth managers), 20% in precise customer acquisition and paid conversion, and 10% in infrastructure and legal affairs construction.
Since Lu Tie Ji was launched two years ago, the current data of organic user growth shows that there are more than 4,000 monthly active users, among which 1,219 users record more than 4 days a month. The next - day retention rate of newly acquired organic users is about 23%. The core goal of the team in the next 6 months is to increase the number of premium members to over 1,200 and make the paid model truly work.
"Lu Tie Ji has verified the rigid demand of strength trainers for recording tools. Our core task in the next 6 months is no longer to verify 'whether users need to record' but to make the key leap from a'recording tool' to an 'AI partner' based on the established demand," Tan Peiqi said.
Starting from a single training record to becoming an AI fitness partner that everyone depends on - Lu Tie Ji is proving that the best perseverance comes from seeing every bit of your progress and being seen by someone who truly understands you.
About Lu Tie Ji
Lu Tie Ji is an AI application dedicated to strength training records, developed and operated by Jining Xiaofu Changliu Technology Information Consulting Co., Ltd. The product has covered iOS, Android, HarmonyOS, watchOS, and mainstream domestic wearable devices and has received industry recognition such as Xiaomi's "Golden Rice Award".