An evidence-based AI assessment for a science-first product
Audicin’s product is validated by neuroscientists and medical doctors, so any AI added to it had to meet the same bar. Moterra delivered a Rapid AI Assessment that gave leadership a model choice backed by numbers, a scoped path to production, and confidence that AI would enhance the science rather than compromise it.
The situation
Audicin builds scientifically-engineered music combining binaural beats, spatial sound and neuroscience-backed audio design to help the nervous system relax, focus and recover. Every track is validated by an in-house team of neuroscientists, medical doctors, audio engineers and music composers - a standard any added AI layer would also have to meet.
What they needed
As the product and user base grew, Audicin’s team wanted to explore how generative AI could take personalisation from broad categories to something genuinely individual, without compromising the scientific integrity that defines the product. Four questions had to be answered before anything got built.
What Moterra delivered
A Rapid AI Assessment scoped to Audicin’s context, combining stakeholder work with hands-on measurement rather than desk research.
Throughout the engagement, Audicin had access to Moterra Business AI Suite as a working sandbox, used to prototype and validate personalisation use cases against real content and data.
The outcome
Audicin’s leadership got what mattered most: a model choice backed by numbers, a scoped path to production, and confidence that AI would enhance the science rather than compromise it.
A product built on peer-reviewed method deserves the same rigour in its tooling. Benchmarking three models on Audicin’s own tasks cost a fraction of building on the wrong one and finding out in production.
Frequently asked questions
What problem did Audicin need to solve?
Audicin builds scientifically-engineered music combining binaural beats, spatial sound and neuroscience-backed audio design to help the nervous system relax, focus and recover. Every track is validated by an in-house team of neuroscientists, medical doctors, audio engineers and music composers - a standard any added AI layer would also have to meet.
What did Moterra deploy for Audicin?
A Rapid AI Assessment scoped to Audicin’s context, combining stakeholder work with hands-on measurement rather than desk research.
What results did Audicin see?
Audicin’s leadership got what mattered most: a model choice backed by numbers, a scoped path to production, and confidence that AI would enhance the science rather than compromise it.
Where does the deployment run?
Inside the client’s own cloud tenant, in the region they choose. The deployment is Private Claude Cowork by Moterra, with admin, MDM and governance handled by Moterra AI Bridge. Moterra builds in AWS and Azure, operates as a data processor under a DPA covering UK and EU GDPR, and the stack is ISO 27001 and ISO 42001 certified across the AWS and Anthropic layers.
How long does a deployment like this take?
Standard deployment is typically live within one to two weeks, covering environment and region setup, the identity path from your SSO, managed configuration through your MDM, and the connector allowlist.
Read the deployment behind this story: Private Claude Cowork by Moterra for the environment itself, and Moterra AI Bridge for the admin, MDM, plugin and agent layer around it.
Moterra is a private AI deployment company and a Select Services Partner in the Claude Partner Network. We help businesses deploy Claude inside their own AWS or Azure environment, connect it to the tools they already use, and keep it secure and governed, so everyday processes get faster.
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