AI-Driven Music App to Help Indie Musician Artists Scale
Timeline: 6 Months| Country: United Kingdom
Project Brief
A UK-based music-tech startup approached us to build a comprehensive, AI-powered SaaS and mobile platform aimed at helping emerging musicians scale their careers independently. Their target users included solo artists, singer-songwriters, producers, and music influencers who often lack structured career planning, mentorship access, and marketing strategy support. These artists typically juggle content creation, distribution, fan engagement, and personal brand building without adequate guidance or digital tools.
To address this gap, we were tasked with designing a scalable platform that combines artist-specific strategy building, automated task execution, personalized recommendations, and mentorship connectivity into one unified experience. This new product needed to function as a digital accelerator—equipping independent artists with tools traditionally available only to label-backed professionals. The platform also needed to harness AI and LLM (Large Language Model) technologies to provide career coaching, automate workflows, and support real-time insights into growth opportunities.
Client's Need
- The client sought to create a first-of-its-kind platform that would serve as a digital accelerator for independent musicians, empowering them to grow their careers without needing a label or agency. Their vision was to bridge the gap between emerging artists and professional career support, by providing a system that offers structure, guidance, and actionable insights—all in one place.
- They needed a fully new SaaS and mobile platform that could work across global markets and adapt to individual artist journeys. It had to support goal planning, mentorship access, AI-based strategy guidance, content and task automation, and career progress tracking. At the heart of the product was an expectation to embed AI and LLM technologies to personalize the experience for every user—so that no two artists received the same roadmap.
- The platform also had to feel approachable and intuitive to creatives who may not be tech-savvy. It was critical that the system worked seamlessly across desktop and mobile, offered on-demand coaching via AI chat, and included a human mentoring marketplace for deeper engagement. All these tools needed to function cohesively so that an artist could log in daily and get exactly what to focus on, how to do it, and track their growth over time—without needing outside consultants or label funding.
Technologies
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React Native
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NodeJS
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FirebaseDB
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MySQL
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Challenges
- Musicians often need tailored advice based on their level, goals, and brand. Crafting a unique strategy for every user required intelligent user segmentation and adaptive content delivery.
- Platforms often fail to engage users after onboarding. Keeping musicians involved in continuous learning, mentorship, and community conversations required dynamic engagement strategies.
- Tracking weekly and long-term goals for every user, including feedback, completions, and nudges, required automated context generation and workflow cycling using LLM prompts.
- Extracting meaningful insights from TikTok, Instagram, and YouTube to provide actionable feedback required building a real-time AI social media audit feature.
- Delivering helpful and sensitive responses to open-ended mental health inputs was a challenge, demanding context-aware NLP models with soft prompt engineering.
- Managing and integrating live mentor sessions, masterclasses, cohort programs, and community tribes in a seamless UX experience presented technical and structural challenges.
Solution By Kanhsoft
- We implemented a scoring-based user segmentation model and used large language models to generate customized yearly and weekly strategies based on questionnaire input and user progress.
- Designed a multi-step onboarding process using conditional logic: waitlist registration, interview scheduling, payment capture post-approval, and personalized dashboards post-activation.
- Introduced a recurring task loop system where LLMs analyze past actions, feedback, and goal progress weekly to generate the next set of tasks and suggest nudges or praise.
- Connected social APIs to analyze user content and engagement, then surfaced actionable tips via AI chatbots—improving reach and follower growth through practical suggestions.
- Built structured masterclass scheduling, mentor profile browsing, and 1-on-1 session booking with video call integration—supporting deeper artistic growth.
- Added a simple, free-text mental health check-in system powered by AI. It interprets responses and returns practical, compassionate mental health tips directly in-app.
Key Features
- Automatically generated action plans and creative development paths using LLM logic based on user segmentation, scoring, and archetype identification.
- Weekly analysis by LLMs tracks user feedback and progress, then auto-generates new task lists, creating a continuous improvement loop with personalized nudges.
- Musicians can join interest-based groups to post content, collaborate, and grow peer networks with AI-powered recommendations for groups to join.
- Artists can join scheduled masterclasses led by industry pros, receive reminders, and rewatch sessions, building skills over time.
- AI-driven insight tool connected to major platforms (e.g., TikTok, Instagram) to provide performance tips and optimize content strategy.
- A conditional user flow that includes profile setup, segmentation, waitlist approval, interview scheduling via Calendly, and activation upon approval.
- Chatbot provides 24/7 guidance for branding, social media growth, gig opportunities, and monetization strategies tailored to each artist’s level.
- Free-text input from users enables AI to detect emotional well-being concerns and respond with simple mental health tips—building trust and empathy.
- Personalized mentor matching, session booking, and live video consultations to help users refine their strategy with expert feedback.
- Secret levels assigned to each user that guide content exposure and strategy depth—making development progressive and customized.
- Weekly reports and context-aware nudges based on user activity, task completions, and progress to help maintain long-term platform engagement.
- The LLM is continuously improved through user feedback, common artist challenges, and strategic data, making the recommendations more relevant over time.