Logically forecasts narrative risk for government and enterprise with a conversational AI agent on Databricks

Overview

Threat intelligence company Logically built a conversational AI agent using Databricks Agent Bricks Custom Agents, AI Search, Delta Lake and LangGraph to make narrative-risk intelligence accessible to non-technical users, processing over 10 million social media messages daily and going from concept to production-ready agent in under two weeks.

The challenge

Analysts became bottlenecks managing requests from non-technical teams; the platform needed to process more than 10 million social media messages a day but its Elasticsearch-based solution was expensive, slow and difficult to scale, and ingestion, storage, retrieval and AI execution lived in separate environments requiring fragile manual connectors.

The solution

Logically adopted the Databricks Data + AI Platform, using Lakeflow Jobs to automate ETL orchestration, Delta Lake as the foundation with materialized views for instant insights, Agent Bricks Custom Agents for multi-step reasoning agentic AI, AI Search for semantic search, Google Gemini for reasoning, LangGraph to manage agent reasoning loops and tool orchestration, MLflow for the ML lifecycle, Model Serving via AI Gateway for inference, and Unity Catalog for fine-grained governance.

Reported business value

Logically expanded its narrative-intelligence platform from technical OSINT analysts to non-technical users such as policy advisors and communications teams, built the initial AI agent in under two weeks (down from at least one and a half months) and completed full production integration in about a month, while reducing the agent's query latency with pre-computed materialized views.