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AudioLock

AI for your business

Turn AI capability into dependable operational tools.

We help you choose and implement the approach that fits your operation — connected enterprise AI, bespoke applications or private AI — with model evaluation and validation built into delivery.

Enterprise AI connected to your business

Give your team powerful AI with the context of your business.

We help music businesses connect their existing internal systems and external services with enterprise AI platforms such as ChatGPT, Claude and Gemini. By bringing approved business data and knowledge into these tools, staff can work with AI that draws on your catalogue, processes and priorities.

We configure supported connectors and develop custom integrations through APIs, enabling staff to retrieve relevant information and carry out supported workflow actions. Connections are designed around the information each role needs and the permissions your business requires.

Less time spent searching, copying information and explaining the same context creates more capacity for valuable work. We test responses against approved sources and design data handling and access controls around your requirements, helping your team adopt AI confidently.

Three approaches

How the approaches compare

Enterprise platforms run externally; a fully self-hosted model runs within infrastructure you control. Many businesses combine them.

01

Connected enterprise AI

AI for your team

What it is
Enterprise AI platforms such as ChatGPT, Claude and Gemini, connected to approved business data and services.
Where processing happens
On the external enterprise platform you choose.
Suited to
Finding answers across documents, summarising release and operational information, preparing reports and drafting informed responses.
What we design
Supported connectors, custom API integrations, business-specific instructions, workspace configuration and staff guidance.

02

Bespoke AI applications

Tools and automated workflows

What it is
AI applications and automated workflows built around your operation, from metadata review to reporting.
Where processing happens
Selected per workflow: external model APIs, private models, or a combination.
Suited to
Repeatable operational tasks where quality, throughput and cost per result need to be measured.
What we design
Model benchmarking, evaluation and validation built into delivery, with optional multi-model architecture.

03

Private AI

Fully self-hosted

What it is
Suitable large language models deployed on infrastructure you control: your own servers or dedicated private environments.
Where processing happens
Within your infrastructure; sensitive prompts, documents and outputs need not be sent to an external AI API.
Suited to
Sensitive information with specific confidentiality and data sovereignty requirements.
What we design
Retrieval, storage, access, encryption, logging, retention and backups, plus hardware capacity, resilience and support.

AI model benchmarking

The right model is a measured decision.

We benchmark candidate models against your actual requirements, using representative tasks and test data approved for each environment, and compare how they perform in the workflow you need to run.

  1. 01

    Output quality

    Accuracy, consistency and the ability to handle difficult cases.

  2. 02

    Performance

    Response times, throughput and behaviour under expected demand.

  3. 03

    Cost efficiency

    The cost of delivering an acceptable result, including hosting or API usage, validation, retries and ongoing operation.

  4. 04

    Deployment fit

    Compatibility with your infrastructure, integration needs and data handling requirements.

Model- and provider-agnostic

Our approach is model- and provider-agnostic, allowing us to combine models and services where that improves the solution.

We design to reduce unnecessary dependence on a single provider, giving your business greater flexibility as capabilities and costs evolve. Changing provider still involves evaluation and adjustment; the architecture is designed to keep that work contained.

Private AI deployment

Your AI capability. Your infrastructure. Your control.

We architect and deploy suitable large language models on infrastructure you control, including your own servers and dedicated private environments. A fully self-hosted solution can process sensitive prompts, documents and outputs without sending them to an external AI API.

We design the supporting system as carefully as the model itself: document retrieval, storage, access, encryption, logging, retention and backups. Data flows and operational access are defined around your confidentiality and data sovereignty requirements.

We assess hardware capacity, utilisation, resilience and support alongside model performance to establish the full operating cost of the deployment.

Frequently asked questions

Discuss your next technology challenge

Tell us about the workflow, system or idea you want to improve. We will discuss your requirements and recommend an appropriate starting point.

Discuss your requirementsenquiries@audiolock.net