Keep the firm. Change how the work gets done.
Moving to a new operating model is hard. Galley is designed so firms don’t have to transform everything at once.
Law firms already have profitable services, established teams, client relationships and billing models that work today. Replacing all of that in a wholesale transformation would be expensive, disruptive and risky.
We think there is a more practical path.
Galley is designed to help small and medium law firms migrate existing services into an AI-native operating model one service at a time. Firms can experiment with new ways of delivering work while their existing business continues to operate around them.
The aim is not to kill the golden goose while building the next one. It is to create a controlled path from one operating model to another, proving the economics and the quality of each service before expanding further.
From matter to work
When a new matter arrives, Galley identifies the type of work and applies the appropriate playbook.
It breaks the service into individual tasks and assigns each one to the right kind of worker: a lawyer, an AI model or agent, or conventional software and business rules.
This allows the way work is produced to change underneath the firm without requiring the entire organisation to change with it at once.
Know how every piece of work was produced.
Galley provides a common control and measurement layer across the service.
Rather than presenting reviewers with an AI-generated answer and asking them to trust it, Galley is designed to preserve the evidence behind the work. Facts, decisions and clauses can be traced back to their source, whether that’s the firm’s knowledge base, the client’s instructions or an authorised change made by a solicitor during the matter.
That gives the reviewing solicitor the information they need to understand what was produced, how it was produced and what it was based on before approving the work.
Your firm’s knowledge stays yours.
Your playbooks, business rules, precedents and quality standards remain part of your firm’s operating model rather than being locked into a particular AI provider.
As your firm learns, those rules can be updated. As models and tools improve, the technology doing the work can change without requiring you to redesign the service around it.
The result is an operating model that can evolve progressively: service by service, matter by matter, with the firm able to measure what works before deciding what to change next.