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Shazam’s Presence in Our Lives Since 1999

October 28, 2026

Shazam's acoustic fingerprinting algorithm in action, showing sound waves being processed into a unique digital signature for music recognition.

Shazam is one of the oldest and most established services in the mobile technology world. The technology behind the app predates even smartphones.

Company Establishment (1999)

Shazam Entertainment Limited was founded in London to develop music recognition algorithms.

First SMS Service (2002)

It started its service in the UK with the number “2580“. Users would dial the number, hold the phone up to the music playing, the call would automatically end after 30 seconds, and the artist and name of the song would be sent as an SMS.

Mobile App Launch (2008)

The modern mobile application we know today was released as one of the first apps available in the Apple App Store when it first opened.

Acquisition by Apple (2017)

The application was acquired by Apple for approximately 400 million dollars, integrating it more closely with their operating systems.

How did its initial services work?

Shazam‘s initial service in 2002 operated using the phone call and SMS infrastructure of standard mobile phones, prior to smartphones. At the core of the system was the “acoustic fingerprinting” algorithm developed by co-founder Avery Wang.
The process worked in these steps:
1. Calling: When a user heard music on the radio or in a venue, they would dial the short number (2580) assigned to the system in the UK and hold the phone’s microphone towards the music.
2. Audio Transmission: The sound captured by the phone’s microphone was transmitted directly to Shazam‘s servers, similar to a phone call, over the cellular network.
3. Acoustic Mapping: The server would extract a spectrogram (frequency and time map) from the incoming low-quality and noisy audio recording. The algorithm identified the most prominent peak points within the sound, creating a mathematical fingerprint of the music.
4. Database Matching: This generated fingerprint was compared with recordings in Shazam‘s own music database, which had been pre-scanned and mapped on their servers.
5. SMS Notification: After approximately 30 seconds of listening, the system would automatically terminate the call, and if a match was found, it would send the song’s name and artist to the user as a short message (SMS). Initially, this service was charged per successful SMS sent.

Is the system artificial intelligence?

The original technology forming the basis of Shazam is not artificial intelligence (machine learning or deep learning) in today’s sense. This system is a purely deterministic Digital Signal Processing (DSP) and database matching algorithm.
For a system to be considered artificial intelligence in the modern sense, it is generally expected to learn from big data, make generalizations, and make predictions (predictive modeling) about new situations it encounters. Shazam‘s core technology, however, does not “learn” or make predictions; instead, it operates with strict mathematical rules:
1. Fourier Transform: Converts sound waves from a smartphone or microphone into a spectrogram (frequency and time map).
2. Constellation Map: Marks the highest energy points (characteristic peaks of the sound) in the spectrogram.
3. Hashing and Search: Converts these points into cryptographic “hash” codes, searching for an exact match in a massive pre-indexed database (hash table) on the servers.
This structure is more akin to a search engine that finds a specific code within a massive data dictionary in milliseconds, rather than an artificial intelligence model attempting to “understand” a sound or image.
Today, within the Shazam application under Apple, machine learning (ML) models are actively used to clean up background noise (wind, crowd hum) recorded by the microphone or to suggest new music of similar genres to users. However, the main engine that identifies the song’s identity is fundamentally still this classic and mathematical structure established in 2002.