To grow in the AI era, boutique LSPs are called to scale under permanent time pressure. There is rarely spare capacity to redesign operations, because the same small team is also delivering projects, handling clients, and keeping the business running. Traditionally, we rely on SaaS platforms that promise order, but with trade-offs: dependency, limited configurability, and incremental pricing that can penalise growth. In this session, I will share practical lessons from our work at Rhyme&Reason Language Services and RIMA Language_Tech_Culture, where we have created a lightweight workflow-orchestration layer using AI agents to connect and standardise operational steps. I will walk through what has worked (and what has not) when automating routine tasks - intake and quoting, file routing and versioning, hand-offs, and QA checkpoints - while keeping human judgement and accountability in place. A key theme is sustainability for small teams: automation that can be understood, maintained, and easily adjusted without becoming a second job. I will also share a simple decision framework for what to automate first (and what to leave manual) so that small teams can prioritise the changes that actually help. We will also look at where AI can meaningfully support boutique companies in specialist niches, by reducing coordination overhead, speeding up structured drafting and triage, and improving consistency, without outsourcing judgement to the tools.