The client, a legal marketing and case acquisition firm supporting mass-tort and personal injury practices, was experiencing increasing operational strain in its call center. As campaign activity expanded and lead volumes grew, intake agents were spending more time handling repetitive qualification and follow-up conversations with potential claimants.
The firm had already deployed an initial chatbot, known as MEL, on campaign landing pages to answer basic questions and help prequalify potential claimants. While this improved digital intake on the web, SMS engagement remained largely transactional, and the team needed more conversational SMS for legal intake to handle nuanced, back-and-forth dialogues at scale. Many SMS interactions still required live agent involvement, which limited the organization’s ability to scale intake without adding operational burden.
The existing SMS workflow lacked the conversational intelligence needed to interpret natural language responses, manage multi-step qualification paths, and respond flexibly to ambiguous claimant input. Instead of guiding users through a dynamic intake experience, the process relied heavily on structured prompts, manual review, and agent-led follow-up.
This created several challenges:
- Intake agents were spending valuable time on repetitive conversations.
- Lead qualification outcomes varied across channels and campaigns.
- SMS engagement could not easily adapt to free-form claimant responses.
- Campaign-specific qualification criteria and legal content were spread across multiple repositories.
- The firm needed stronger governance to keep chatbot and SMS responses aligned with evolving case requirements.
- Scaling across multiple tort campaigns required a more consistent and automated intake framework.
To improve efficiency, the organization needed a conversational, AI-assisted engagement model that could automate claimant intake across SMS and web channels while supporting compliance, knowledge consistency, and operational control.