EnergyConversational AI

Italgas replaces its contact center IVR with a conversational AI agent built on Databricks

ItalgasAI Gateway · MLflow · Unity Catalog +1

At Europe's largest gas distributor, the customer contact center handled approximately 120,000 calls per month using a traditional IVR system, with 22,000 calls dropped during navigation and 10,000 calls resolved through automation. The IVR was replaced with a conversational AI agent built on Databricks, which interacts with callers in natural language, gathers contextual information and routes users to the correct resolution path. The session abstract reports a 50% reduction in call drops during navigation and a 44% increase in automated resolution.

Overview

At Europe's largest gas distributor, the customer contact center handled approximately 120,000 calls per month using a traditional IVR system, with 22,000 calls dropped during navigation and 10,000 calls resolved through automation. The IVR was replaced with a conversational AI agent built on Databricks, which interacts with callers in natural language, gathers contextual information and routes users to the correct resolution path. The session abstract reports a 50% reduction in call drops during navigation and a 44% increase in automated resolution.

This entry has 11 published fields tied to exact passages in an immutable source capture.

Inspect the highlighted source

The challenge

At Europe's largest gas distributor, the customer contact center handled approximately 120,000 calls per month using a traditional IVR system, which resulted in 22,000 calls dropped during navigation and only 10,000 calls resolved through automation.

The solution

The IVR was replaced with a conversational AI agent built on Databricks. The AI Gateway provides the backbone for real-time agent serving while MLFlow tracks performance, data is securely accessed from Unity Catalog, and the tools are served via MCP through a Databricks app. The agent interacts with callers in natural language, gathers contextual information, and routes users to the correct resolution path.

Conversational AIAgentic AI

Reported business value

According to the session abstract, the solution reduced call drops during navigation by 50% and increased automated resolution by 44%.

Sources

Open any source and check the claim yourself — that is the point of the register.

This record was researched and written with AI assistance, and its claims were checked against the sources above. (EU AI Act art. 50 transparency notice.)

Related entries

Other energy entries in the register.

All entries
EnergyNatural Language ProcessingPublic Cloud

Building a clean energy future with natural language analytics

Williams, a large-scale natural gas infrastructure operator, deployed Databricks AI/BI Genie to give commercial, regulatory, accounting and technical staff natural-language, self-serve access to analytics. The team flattened 27 disparate tables into SQL models that Genie Spaces reason over, encoding internal acronyms and business logic into Genie's instructions, powered by Databricks Unity Catalog. A data request that previously took an analyst five days now completes in seconds with validated accuracy, and the weekly backlog of data requests dropped from up to ten to one or two, freeing analysts for predictive modeling and enterprise projects.

96/100HighPrimary source
WilliamsDatabricks AI/BI Genie · Databricks Unity Catalog
EnergyPredictive AnalyticsPublic Cloud

Plenitude builds machine learning models on Databricks to forecast energy demand and renewable production

Eni-owned energy company Plenitude, which serves 10 million households and businesses across Europe, uses statistical models and machine learning on the Databricks Data + AI Platform to forecast customer energy consumption at hourly and daily granularity, forecast wind and solar generation from its renewable asset portfolio, and run customer segmentation and propensity models across 60 implemented use cases.

100/100HighPrimary source
PlenitudeDatabricks Data + AI Platform · Delta Lake · Unity Catalog +2
EnergyPredictive AnalyticsUnknown

Shell delivers innovative energy solutions with data and AI on Databricks

Shell built its Shell.ai platform on Databricks to unify data, analytics, and AI workloads for its 600-member mathematics, computational and data science team, running over 100 AI applications including an inventory prediction model running 10,000+ simulations across spare parts and facilities, and an AI-powered recommendation engine for its loyalty program.

92/100HighPrimary source
ShellDatabricks Data + AI Platform · Delta Lake
EnergyPredictive AnalyticsPublic Cloud

Using data to power-fuel the transition to a carbon-neutral world

Helen, Helsinki's energy utility, built a centralized data and AI platform on Databricks to power forecasting and optimization models for its district heating system serving about 90% of Helsinki's population, processing real-time streaming sensor and IoT data to optimize distributed energy resources and EV charging placement as part of a plan to cut carbon emissions over 80% by decommissioning coal plants.

96/100HighPrimary source
Helen· FinlandDatabricks Data + AI Platform · Delta Lake · Spark Declarative Pipelines +3

Was this helpful?

Your feedback helps us improve our use case database