Energy & Utilities practice
We harness frontier models to build agentic workflows for the utility, delivered by forward-deployed engineers on a context and trust layer we bring to every engagement.
Domains
Customer service agent, high-bill alerts, collections and assistance matching, outage communications. All on Customer 360 and shared MCP tools.
In productionDispatch copilot, outage ETR prediction, relay-settings review, wildfire risk, and a grid digital twin for what-if and switching studies.
Shared foundationField safety briefings, transformer and asset health, DER interconnection queues. Program targeting for DR, efficiency, and rate plans from AMI data.
RoadmapLegal review and contract management with the clause cited, regulatory filings, and analytics agents that answer questions over the lakehouse in plain language.
Shared foundationThe fleet
Generation & transmission
Operations & field
Customer
Corporate
Every agent is built for the utility it runs in. What stays constant is the context layer it reads from and the certification evidence it ships with.
What we bring
Resolved CIS, MDM/AMI, OMS, payments, and contact center, governed and lineaged.
Unity CatalogDeflection of top call drivers, a CSR copilot, and QA scoring on 100% of interactions.
Voice · chat · digitalService, meter & billing, outages, collections, and contracts, all reading the same context.
One tool layer, many agentsEvery agent cataloged, scored, human-calibrated, and certified before it talks to a customer.
Audit-ready evidenceThe platform
Customer operations · five value streams
Intent analytics on every transcript, a real-time CSR copilot, and QA on 100% of interactions.
Furthest alongPredict the high bill before it lands. Explain it from interval data and tariff, not a guess.
Risk · mediumPremise-level ETR, storm-mode self-service, medical-needs customers notified first.
Risk · lowPropensity-to-pay, assistance matching, compliant arrangements. A human approves.
Risk · highObligations, renewals, and rate terms extracted from PDFs with the clause cited.
Risk · low to highNorth star
Cost-to-serve
Calls per customer, AHT, containment.
CSAT / J.D. Power
Proactive, personalized bills and outage comms.
Bad debt & DSO
Early intervention instead of blanket dunning.
PUC compliance
100% interaction scoring, certified agents.
Trust in AI
Agent certification as standing evidence.
Sequencing
H1 · months 0–6
H2 · months 6–15
H3 · months 15–24
Delivery
Agentic workflows fail in the gap between the spec and the floor. So we close the gap: our engineers sit with the people who will use the agent, build on your governed data from the first week, and certify as they go.
Weeks 0–2
Shadow the floor, pick one call driver or one outage pattern, stand up the context layer on your data, write the rubric.
Weeks 3–8
Ship a working agent to a pilot group, iterate daily on real interactions, score every change against the rubric.
Weeks 9–12
Produce the certification evidence, go live under a human-approval gate, and pair your team onto the next agent.
“Real artists ship.” Steve Jobs, to the Macintosh team, 1983
Partner
Technology partner
Databricks is the data, ML, and agent plane for the practice. Unity Catalog governs Customer 360, Vector Search powers the Digital Brain, and the agents, their context, and their serving all stay inside the workspace.
The Agent Context Platform runs on Lakebase. Entity profiles live as Postgres JSONB with pgvector, rebuilt from the gold layer by schedule and change feed.
Postgres · pgvector · changefeedWhere the agents are built and tuned. Digital Brain retrieval agents and the CSR copilot are composed, evaluated against the certification rubric, and iterated here.
Model Serving · MLflow evalsThe MCP tool layer and the copilot UI ship as Apps, so explain_bill and get_outage_status run next to the data with Unity Catalog permissions intact.
MCP tools · CSR copilotDeployment
AWS
Amazon Bedrock
Agents served through Bedrock with Guardrails, inside the utility's VPC. Landing zones, IAM, and PrivateLink to the lakehouse.
Microsoft Azure
Azure AI Foundry
Foundry agents and model catalog, Entra ID for every tool call, and a direct path from Dynamics and Teams into the CSR copilot.
Google Cloud
Gemini on Vertex AI
Gemini models on Vertex AI for long-context contract and transcript work, with Cloud SQL and BigQuery federated into Unity Catalog.
We work with utility operations, data, and compliance teams on Databricks across AWS, Azure, and Google Cloud. Bring a call driver, a bad-debt number, or a PUC question.