Customer Service Automation · Enterprise Knowledge Search
Crisis Text Line offers text-based mental health support and crisis intervention in English and Spanish. With over 1.3 million conversations supported in the past year alone, the organization leverages advanced data and AI technologies to deliver high-quality training for crisis counselors.
Reported impact
Reported outcomes include 1.3 million Crisis intervention conversations; 100,000 Volunteers trained globally; Crisis Text Line is a nonprofit organization dedicated to providing free, 24/7, confidential, text-based mental health support and crisis intervention..
Crisis Text Line built its Databricks implementation around Agent Bricks, Databricks Data + AI Platform, Unity Catalog, MLflow. Crisis Text Line offers text-based mental health support and crisis intervention in English and Spanish. With over 1.3 million conversations supported in the past year alone, the organization leverages advanced data and AI technologies to deliver high-quality training for crisis counselors. Agent Bricks provides the agentic and generative AI runtime used to build domain-specific applications. Databricks Data + AI Platform provides the shared lakehouse environment for ingestion, engineering, analytics, and AI workflows in this deployment. Unity Catalog applies centralized governance, lineage, auditing, and access control across shared data assets. MLflow tracks model experiments and repeatable machine learning workflows.
Source data is ingested into databricks, curated in shared lakehouse tables, processed with Databricks compute and orchestration services, and exposed to downstream analytics and users.
1.3 million Crisis intervention conversations
100,000 Volunteers trained globally
As CTO Matthew Vanderzee noted, “We think about how we take all of the learnings from the knowledge we’re gaining around mental health and crisis response, and see how we can use that to support more people while influencing public policy a
Principal Product Manager Kristi Lui explained, “At the time, our data landscape was very siloed in terms of record reporting. A lot of business rules and context remained inconsistent or lost in data silos.
“Being able to manage access at the table and column level for all these different data profiles has been vital for our teams to move quickly, but with the proper oversight,” Lui said.
“Without that single source of truth, it was difficult to build a cohesive data culture across the organization,” Lui highlighted. The siloed nature of the infrastructure led to duplicated efforts across teams.
Review how this reference was scored and trace each normalized claim back to its documented source.
Scoring methodology
Customer Reference Value measures usefulness as a customer reference. Evidence Confidence measures the quality and traceability of available evidence, not independent verification.
Traceability
Field coverage shows which facts each source supports. Dates are shown only when documented by the source.
The 2024 Form 990 states: "Total number of individuals employed in calendar year 2024 (Part V, line 2a)" and reports 261, which maps to Mid-market under the 250-999 rule.
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