Ready to improve your music discovery workflows? Try Similarity Search in Cyanite.

Thematic is a creative community built for discovery, collaboration, and growth. Co-founded by Michelle Phan, a pioneering creator who helped define how influencers build and monetize audiences online, Thematic was optimized for the creative experience from the start and is now trusted by over 1 million creators.

When a creator features a Thematic song in their video, they create a promotional moment for that artist. The artist can track exactly which videos by which creators used their music and how many new fans they gained as a result.

Every interaction feeds back into the recommendation engine, creating a virtuous loop of value between creators and artists. It’s a collaborative ecosystem where both sides of the creative equation create, connect, and grow together.

Thematic’s goal was to turn music discovery into a win for all by giving creators better options. However, in practice, their growing catalog meant creators had to navigate an overwhelming amount of choice in a space already defined by decision fatigue. As Thematic continued to scale, so did the pressure to make discovery smarter.

When finding the right track becomes a problem

Before building anything new, the team listened carefully. One-on-one interviews, surveys, support ticket analysis, and community feedback all pointed to the same problem. Finding the right song was taking too long.

The size of the catalog wasn’t the issue. It was the mismatch between how creators think and how search tools work.

Tags and genres are a poor way to describe music. “Creators don’t fall in love with a song because it’s ‘indie folk with a male vocalist at 120 BPM,’” explains Audrey. “They connect with it because of how it sounds, how it makes them feel, and the emotional resonance of the lyrics.”

Traditional keyword search asks users to “translate a feeling into a music tag formula,” as Audrey puts it. Most creators know what they want when they hear it. Forcing people into a keyword search box creates a time-consuming cycle: sampling track after track, exploring a genre only to find it missed the mark, then starting over.

But Thematic serves both creators and artists, so improving discovery efficiency would have a double impact: saving creators time finding the perfect-fit song, while driving higher placement opportunities for artists.

“Think about the difference between flipping through cable channels versus opening a feed that already knows what you like,” says Audrey. “The channel count doesn’t matter. What matters is whether the right thing surfaces at the right moment.”

To address this, Thematic launched a rebuilt platform alongside a complete rebrand. The product had grown significantly since its initial launch, and the visual identity needed to catch up.

The rebuild focused on two areas: 

• A personalized For You experience based on each creator’s usage history and music taste, updated tagging infrastructure to improve search and filtering accuracy, and the ability to find sonically similar songs to any track, whether on Thematic or Spotify.
• Deepening the creator community through a points leaderboard, upgraded creator and artist profiles, and better visibility into the value exchange happening on the platform.

At the center of the smarter discovery experience was Cyanite.

The decision to incorporate AI-based audio analysis came down to one thing: saving creators time.

“We treat AI as a great workflow improvement tool for creators,” says Audrey.
“Its ability to analyze large datasets and surface the most relevant information can be genuinely time-saving, especially when trying to identify songs that have a similar sound, not just similar music attributes and tags.”

Sound-based search has removed the need to translate intent into search terms. Instead of asking creators to describe what they’re looking for, it lets them start from a reference track and find cleared, licensed music on Thematic that matches that sonic profile. What used to take hours can now happen in seconds.

From there, creators can quickly build a full set of songs that fit their overall aesthetic by exploring complementary recommendations. What used to be a slow, trial-and-error process becomes fast, flexible, and far more creatively aligned.

Why Cyanite?

When evaluating solutions, Thematic made their decision based on capability and practicality.

Beyond features, the path to implementation mattered too: “Product-switching a core backend component can often be painful, but the ease of transition was seamless.”

How Cyanite fits into Thematic’s workflow

Cyanite is integrated across several touchpoints, allowing Thematic users to move fluidly between different discovery pathways depending on how they work.

Auto-Tagging

Auto-Tagging is the foundation of everything. It provides the baseline context for every song in Thematic’s database and powers the filtering, matching, and personalization that follows. For artists who haven’t provided their own descriptions, Cyanite also generates auto-descriptions, ensuring no track enters the catalog without proper context.

This is important for emerging artists. “Discoverability can often be a visibility problem dressed up as a quality problem,” says Audrey. “A great song that isn’t tagged correctly, or that gets added to a platform when the algorithm isn’t paying attention, can sit undiscovered for months.” Accurate, consistent tagging prevents that gap from opening up.

Similarity Search

Thematic’s Similarity Search lets creators find music that matches a reference track’s sonic and emotional profile. For any song, one click surfaces a playlist of sonically similar tracks. It also works for any external song via Spotify URL: entering a link returns a curated shortlist of cleared music that matches the sound.

The feature directly addresses the feedback creators gave Thematic in their research. No more guessing at genre labels or struggling to articulate the vibe they’re after. The reference track does the talking.

Advanced Search

Advanced Search powers part of Thematic’s For You page by recommending songs based on what a specific creator has already downloaded and used.

“Advanced Search might be my favorite” says Audrey, “as it’s a hyper-personalized way for us to provide perfect-fit song recommendations for our users, contextualized to songs they already like to use. It’s not just, ‘Here are songs in this genre.’ It’s ‘Here are the songs most likely to work for you, based on everything we know about how you create.’”

Cyanite’s multi-track similarity underpins this. Rather than building a recommendation from a single song, Thematic builds a rich, dynamic music profile for each creator from their full history. The result is recommendations that feel more accurate than single-song matching can achieve on its own.

The new Thematic homepage is the clearest expression of what this infrastructure makes possible.

Every module is personalized. Depending on a creator’s behavior and preferences, they might see new drops from artists and creators they follow, song suggestions based on their download history and content niche, editorial playlists matched to trending formats, and exclusive creator perks and rewards.

One of the modules is powered directly by Cyanite’s Advanced Search. Others are shaped by the music tags Auto-Tagging produces. Together, they create a feed designed to surface the right song before the creator even has to go looking for it.

The impact of integrating Cyanite

Since integrating Cyanite, Thematic has seen consistent, meaningful changes in how creators search and make decisions:

• Nearly 9% decrease in the number of plays before a creator downloads a song
• Nearly 15% increase in creators downloading songs directly from the For You home page, without using search or filters at all

Creators are reaching confident decisions faster, spending less of their energy on searching and editing and more on actually creating.

The second signal is the one that excites Thematic most. “We’re getting the right song in front of the right creator before they even have to go looking for it,” says Audrey. “That’s the goal: discovery that feels effortless.”

For artists, the impact is equally direct. Better matching means more placements, more exposure, and more new fans. AI-powered similarity matching means a song’s sonic profile does the work that metadata alone can’t. As Audrey puts it, “The right creator finds the right artist not because they searched for them, but because the system recognized the match.”

Rethinking where music fits in the creative process

Beyond the metrics, Thematic sees a larger shift ahead. Music has traditionally been the last step in a creator’s process. They tend to hunt for the perfect fit after the rough cut is done and the overall vibe is already set. AI-powered discovery has the potential to flip that entirely.

When Thematic decided to invest in AI-powered discovery, removing friction was the priority: for creators looking for the perfect track, and for artists waiting to be found. Cyanite made both possible at once.

Improve your catalog’s discoverability with Cyanite. Sign up to get started.

Ready to improve your music discovery workflows? Try Similarity Search in Cyanite.

Melodie is a music licensing platform that provides pre-cleared music for film, TV, advertising, and content creation. All artists and tracks on the platform are carefully curated and hand-selected for quality, originality, and emotional resonance. Ethics are at the core of Melodie’s company philosophy. It operates under a 50/50 revenue and royalty split, meaning Melodie doesn’t earn money on downloads until the artist does.

To make it easier to discover artists at scale, Melodie continues to refine how users navigate its catalog. AI helps users explore more quickly—but it doesn’t replace the human element behind editorial curation.

The rising tension between depth and speed

As Melodie’s catalog grew, a familiar tradeoff emerged: depth versus speed.

Despite thoughtful editorial tagging, the reality was that users often struggled to translate nuanced creative briefs into static keywords. “Describing music is inherently subjective; what sounds ‘uplifting’ to one person might sound ‘intense’ to another. As the saying goes, talking about music is like dancing about architecture,” explains Evan.

By relying solely on tags, users often found themselves in an experimental searching-listening-refining-repeating loop—a time-consuming effort that most editors and producers simply don’t have the bandwidth for.

Melodie recognized this problem early on and set out to improve the user experience in their library. As Evan puts it, “bridging the gap between ‘hearing it in your head’ and ‘finding it on the screen’ is the holy grail of music licensing.”

AI as an enabler, not a generator

Human curation is central to how Melodie operates. Tracks are not scraped or auto-generated. Over time, it became clear that tags on their own couldn’t support the kind of discovery users needed, so AI was added to help surface music intuitively and improve navigation.

Cyanite aligned naturally with that philosophy.

Rather than positioning AI as a substitute for curation, Cyanite’s AI search treats sound as data that can be understood, compared, and explored. What clicked for Melodie in their search for AI music analysis software was Cyanite’s approach: “The technology felt musical rather than just mathematical. The analysis is intuitive and forgiving, respecting the nuances of the tracks,” says Evan.

Thanks to this shared understanding, Cyanite became part of Melodie’s day-to-day music discovery process.

How Cyanite fits into Melodie’s workflow

Today, Melodie users move fluidly between different music discovery pathways depending on their working process.

Sound-based Similarity Search

Users can use Cyanite’s Similarity Search to analyze a reference song and instantly explore tracks with a comparable emotional arc, energy, and sonic character. The reference can come from Spotify, YouTube, or a temporary edit.

This closes the gap between intuition and results in seconds.

Prompt-based Free Text Search

Some users prefer to express what they are looking for in their own words. Prompt-based search allows them to describe mood, pacing, or instrumentation, even with spelling errors or mixed languages. Evan believes natural language search has done for music libraries what Google did for information in the late 90s: democratized access.

Editorial filters and contextual metadata

Even though AI excels at recognizing patterns in sound, only people can understand context, intent, and cultural meaning. That’s where editorial curation shines, as it carries the cultural, social, and creative nuances that AI can’t infer on its own. Melodie’s is valued for its trust and consistent quality, so they couldn’t rely exclusively on AI. Especially since, as Evan puts it, their users trust their taste, ethics, and artists.

To harmonize AI and editorial nuances, users combine Cyanite’s sound- or prompt-based results with Melodie’s tagging system, which brings in the contextual metadata layer AI can’t deliver. 

This hybrid approach means discovery can become exploration: fast, confident, and grounded in human context. “Cyanite helps users get to the right neighborhood quickly, but our human-tagged keyword taxonomy ensures the house is built correctly. By combining the two, we ensure that efficiency never comes at the cost of the ‘soul’ of the library,” explains Evan. 

Read more: Why AI labels and contextual metadata matter in music licensing 

Spotlighting original Australian music through contextual metadata

One of Melodie’s most impactful filters is the “Australian Artists” tag. As a proudly Australian brand, spotlighting local artists is a core value for Melodie.

For Australian broadcasters, brands, agencies, and government bodies, supporting the local creative economy is often a conscious mandate. Melodie’s stance is simple: it should be frictionless for Australian clients to support local talent, if they want to do so.

A typical search might look like this:

1. A client starts with a reference track that has a cinematic, atmospheric build.
2. They use Similarity Search to generate a shortlist of tracks with the same emotional profile.
3. Instead of scanning all international options, they apply the “Show Australian Artists only” filter (currently available for Australian-based users only).
4. They further refine by mood, instrumentation, tempo, or key.
5. Within seconds, they are listening to a track that fits both the creative brief and their mandate to support local artists.

By making artist origin visible and searchable, Melodie ensures Australian music is infinitely discoverable—not buried beneath descriptors.

This approach extends to Melodie’s broader ethical framework, including the First Nations Composer Fund—part of their Indigenous Engagement Strategy. Melodie contributes a minimum of $25,000 annually to support Aboriginal and Torres Strait Islander artists in development and accessing music licensing opportunities.

Evan describes how Melodie approaches contextual and cultural metadata with care: “We only introduce tags when they serve a clear purpose for the user and the artist. Crucially, tags are optional pathways, not restrictive labels. They exist to empower choice—like finding tracks created by an Australian artist—not to define an artist by a single attribute. By working closely with our stakeholders, we ensure that our metadata adds value and visibility without diminishing the complexity of the artistry.”

From discovery to deployment: a National Geographic campaign

This workflow has already been translated into real campaigns.

Melodie collaborated with National Geographic on their film Meanwhile in Australia. The brief called for a sound that felt unmistakably Australian, authentic to the country’s northern “Top End” region.

Using Melodie’s combined AI and editorial search, the team discovered “Moonlit Campfires” by Australian composer James Collins, which ended up making it into the film’s trailer. The track matched the film’s emotional tone, instrumentation, and cultural context while ensuring that licensing revenue flowed directly back into the local creative community. A clear example of how sound-based discovery and contextual filters work together and why that combination matters.

The impact of integrating Cyanite

Since integrating Cyanite, Melodie has seen consistent, meaningful changes in how users search and make decisions:

• Search sessions are shorter.
• Playlists and shortlists are stronger.
• Users reach confident decisions faster. 
• Usage of contextual filters continues to grow.

Evan explains that the addition of Cyanite’s AI search has given Melodie users greater flexibility in how they search, and confidence that “they’re not just finding a track—they’re finding the right track.” For Melodie, that’s the real value: striking the balance between speed and confidence. 

Melodie’s own team also runs countless searches for clients daily. AI-powered discovery saves them significant time while helping them maintain the high editorial standards users expect from them. 

But beyond day-to-day efficiency, the impact of this approach has also been recognized externally. The platform’s search experience has earned multiple industry awards, including 2024 Product of the Year at NAB Show in Las Vegas, celebrating technical excellence and reinforcing user trust. And, as Evan puts it, satisfaction with Cyanite is not unfounded: “We continue to receive great feedback from users too. Based on that feedback, as well as our own experience with Cyanite’s technology, we continue to refine our platform.”

When Melodie decided to amplify their music library with AI, their goal wasn’t to automate creativity. It was to remove friction. With their users top of mind, their intention was to help people find extraordinary, human-made music in seconds, while ensuring that every download pays a real artist.

Striking this balance with Cyanite’s technology has allowed Melodie to grow without diluting what makes their catalog special.

The Problem

The sync licensing industry faces a fundamental information asymmetry problem. With hundreds of production music libraries operating globally, producers struggle to identify which companies are actively placing their style of music. Jesse Josefsson, veteran of 10,000+ sync placements, identified this gap as a core market inefficiency.

Key Challenges:

• • Producers pitching to inappropriate libraries for years without results
• • Manual research taking days or weeks per opportunity
• • Inaccurate tagging solutions create more problems than they solve
• • Industry professionals “flying blind” when making strategic decisions

The Solution

“One of the members said it was so accurate, it was almost spooky because it got things and it labeled things that even they wouldn’t have probably thought of themselves.” – Jesse Josefsson

After evaluating multiple auto-tagging solutions, SyncMyMusic selected Cyanite based on accuracy standards and industry reputation. The platform architecture combines TV placement data with AI-powered music metadata analysis to deliver targeted recommendations.

Why Cyanite:

• • Industry-leading accuracy in genre and mood classification
  • Partnership credibility through SourceAudio integration
  • Responsive customer support with sub-2-hour response times
  • Seamless API integration capabilities

The Implementation

I’m what they would probably call a “vibe coder”. I don’t have coding skills, but if I can do this, you can do this. – Jesse Josefsson

Jesse built the entire SyncMatch platform using AI tutoring (ChatGPT/Grok) and automation tools (make.com) without traditional coding experience. The implementation took 2.5 months from concept to MVP, demonstrating how modern no-code approaches can deliver enterprise-grade solutions.

Technical Innovation:

• No-code integration using make.com automation modules
• Al-assisted development reducing technical barriers
• Scalable architecture supporting thousands of tracks
• Real-time processing with 5-minute turnaround times

The Impact

“I’ve already had multiple members on my app successfully partner with production music libraries as a result of the accurate tags they’ve gotten from Cyanite. One being partnered with Extreme Music.“
– Jesse Josefsson

Within months of launch, SyncMatch users achieved concrete career milestones, including partnerships with industry-leading publishers. The platform transforms weeks of manual research into minutes of data-driven insights.

Measurable Results:

• Multiple successful library partnerships, including Extreme Music (Hans Zimmer’s publisher)
• Research time reduced from weeks to minutes
• Thousands of tracks processed with industry-standard accuracy
• Career-changing outcomes for music producers in the sync licensing space

Industry Validation:

“We‘re partnering with basically the sync licensing industry’s leader auto tagging model. SourceAudio has partnered with them, so you know that whatever tags are getting applied to your tracks are the industry standards right now.“
– Jesse Josefsson

Interested in learning more about how Cyanite’s API can power your music technology platform? Get in touch with our team to explore what’s possible when accuracy meets innovation.