AI-Powered Visibility and Optimisation for Legal Client Onboarding
We built an AI workflow that summarises case communications onto the Salesforce record, increasing fee-earner visibility and reducing manual overhead and escalation.
We built an AI workflow that summarises case communications onto the Salesforce record, increasing fee-earner visibility and reducing manual overhead and escalation.
Taylor Rose is a UK-leading legal conveyancing firm, with more than 1,000 fee-earning consultants. As keen adopters of AI and modern tools, they wanted to embed automation into their workflows to optimise a selection of both manual and repeatable processes.
As an existing partner, ThirdEye delivered a discovery and prioritisation exercise to understand where AI would deliver real value to the business. This identified two key areas where AI could support the client onboarding process that’s delivered through a self-service portal. The two areas of opportunity were a client-facing agent to sit on the website for self-serve support, and agentic automation for drafting heavy case documentation.
Digging into this, together we identified a specific visibility gap in onboarding where large volumes of communication between team members and the client happens before the fee earner is ever looped in. This meant they didn’t have the full picture and were spending valuable time looking for information and working the answer out from there.
This created two costs. Clients experienced friction and delay getting answers, whilst internal staff spent time repeatedly resolving similar issues manually, often just to reconstruct information that already existed somewhere in an email trail.
Both identified opportunities had genuine merit, but the prioritisation exercise pointed to something more fundamental. Lack of onboarding visibility was the biggest driver of pain, and it was better addressed directly, rather than patched with an agent that could only help once cases had already been raised.
ThirdEye built a background AI workflow that retrieves the relevant email communications for a case and generates a summary of everything that has been exchanged, placing it directly on the Salesforce record for the fee earner to see.
This closes the visibility gap without requiring any change to licensing or access levels. Fee earners now have a single point of reference for the full communication history of a case, rather than having to ask a colleague and wait, or search through documentation themselves.
This is deliberately not a customer facing chatbot or an autonomous agent. It's an AI-powered summarisation workflow running quietly in the background, aimed at stopping cases from needing escalation in the first place, rather than making escalated cases faster to resolve.
Taylor Rose expects to see the volume of onboarding related cases fall week on week as the summary becomes the fee earner's first port of call, though it will take a longer observation window to isolate that effect. Once there is a meaningful run of data, the plan is to track cases raised on this subject against the period before the fix went live.
x3
new AI opportunities identified and added to roadmap
x2
operational pain points identified and fixed with automation
x1
AI-enhanced client onboarding journey with full fee-earner visibility
The most interesting part of this story isn't the workflow itself, it's the decision behind it. ThirdEye didn't treat "we want AI" as a brief to build an agent. The process started with identifying the actual root cause of Taylor Rose's problem, and only then asking whether AI, and which form of it, was the right answer. In this case, the answer was a simpler and more targeted solution than either of the two agentic concepts on the table, and it addresses the underlying cause rather than the symptom.
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