Customer Service Automation · Enterprise Knowledge Search
Locala helps brands and agencies efficiently plan, activate and measure campaigns personalized to the local consumer. Before leveraging Databricks, Locala’s data team of five faced significant challenges in developing, training and deploying machine learning models.
Reported impact
Reported outcomes include 1 person To develop a GenAI virtual assistant using Databricks; “We used the Llama 2 model for pretraining and fine-tuning due to its cost-effectiveness..
Locala built its Databricks implementation around Agent Bricks, Databricks Data + AI Platform, Unity Catalog, Databricks Model Serving. Locala helps brands and agencies efficiently plan, activate and measure campaigns personalized to the local consumer. Before leveraging Databricks, Locala’s data team of five faced significant challenges in developing, training and deploying machine learning models. 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. Databricks Model Serving hosts production model endpoints or LLM interfaces used by applications and business users.
Source data is ingested into databricks, curated in shared lakehouse tables, processed with Databricks compute and orchestration services, and served through analytics, semantic search, or model endpoints for downstream users and applications. It connects with Airflow.
1 person To develop a GenAI virtual assistant using Databricks
One of the significant benefits Locala experienced with Databricks was the ease of managing the entire ML lifecycle. They utilized MLflow for version control, experimentation tracking and model storage, greatly simplifying their workflows.
One of their key advancements is the creation of a virtual assistant, dubbed Insights AI, that’s designed to enhance the insights and planning process. This feature allows users to input natural language prompts and receive explanations of
To build the virtual assistant, Camper knew he needed a comprehensive data management platform that could streamline the machine learning (ML) lifecycle and securely access Locala-related data in real time. “As you can imagine, being able
With Databricks robust AI/ML lifecycle management capabilities , Camper could swiftly develop a virtual assistant. “We used the Llama 2 model for pretraining and fine-tuning due to its cost-effectiveness.
“We used the Llama 2 model for pretraining and fine-tuning due to its cost-effectiveness.
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The page’s JSON-LD lists legalName "Ask Locala Inc", numberOfEmployees value 200, and a location "Locala Paris" with addressCountry "FR".
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