Oregon State Bar tests AI-driven online referral tool for high-volume Legal Referral Service
January 30, 2026 | Legal Services Corporation, Independent Federal Agency, Executive, Federal
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The Oregon State Bar is testing an AI-enhanced online referral tool intended to help the statewide Legal Referral Service (LRS) match callers to attorneys more efficiently, Karen Farkas told a Jan. 30 panel.
Farkas, representing the LRS, described a high-volume service with about five full-time staff who take calls via RingCentral and enter issues into a custom database called BearShark. The pilot lets people submit issues in plain language and lets a conversational AI propose follow-up questions that mimic a live assistant. If the AI identifies multiple legal issues, the system will match to one or more attorneys who cover the listed subjects.
The LRS also runs a modest-means sliding-scale panel with an online financial-eligibility step. Farkas said the project is roughly two-thirds to three-quarters complete after live testing with staff and partner submissions; the team plans a soft launch to partners for bug fixes followed by a broader rollout aimed at encouraging more online submissions and preserving human staff for complex cases.
Design priorities include minimizing user overwhelm, preserving clear off-ramps to call-center staff, and ensuring accuracy when users enter lengthy or multitopic issues. Farkas said the tool includes front-end disclaimers and examples to help people understand what facts to include, and that staff will review AI-suggested matches before case referrals are finalized.
The Oregon pilot uses AI for triage and matching rather than as a substitute for human review; next phases include training the tool for specialty panels (licensed paralegals, unbundled legal help) and broader rollout planning.
Farkas, representing the LRS, described a high-volume service with about five full-time staff who take calls via RingCentral and enter issues into a custom database called BearShark. The pilot lets people submit issues in plain language and lets a conversational AI propose follow-up questions that mimic a live assistant. If the AI identifies multiple legal issues, the system will match to one or more attorneys who cover the listed subjects.
The LRS also runs a modest-means sliding-scale panel with an online financial-eligibility step. Farkas said the project is roughly two-thirds to three-quarters complete after live testing with staff and partner submissions; the team plans a soft launch to partners for bug fixes followed by a broader rollout aimed at encouraging more online submissions and preserving human staff for complex cases.
Design priorities include minimizing user overwhelm, preserving clear off-ramps to call-center staff, and ensuring accuracy when users enter lengthy or multitopic issues. Farkas said the tool includes front-end disclaimers and examples to help people understand what facts to include, and that staff will review AI-suggested matches before case referrals are finalized.
The Oregon pilot uses AI for triage and matching rather than as a substitute for human review; next phases include training the tool for specialty panels (licensed paralegals, unbundled legal help) and broader rollout planning.
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