QuaerisAI connects your AMI, SCADA, GIS, and OMS systems through a single natural language interface — giving every team member instant answers, without expensive data warehouse overhauls or IT backlogs.
Co-ops and utilities run lean IT teams against a sprawling stack of vendor systems. The infrastructure is in place — the last mile, getting governed answers to operations, field, and member-services teams, is where the bottleneck lives.
AMI, SCADA, OMS, GIS, billing CIS, and document repositories each live in their own silo from a different vendor. Answering a single question means toggling between three systems, and joining the data takes a project nobody has time for.
Co-ops run with small IT teams and limited budgets while data sits scattered across multiple vendor systems. A traditional data-warehouse project demands a year-plus and headcount the organisation simply does not have.
During an outage, control-room and field teams piece together alarm timelines, recent maintenance logs, and impacted member counts by toggling between vendor systems — losing time when every minute of response matters.
Operations and engineering wait on weekly reports or an IT ticket to answer questions about grid, meter, and customer data. By the time the report arrives, the moment to act has often already passed.
Reliability metrics are under continuous scrutiny, but the patterns behind outages stay buried across OMS, AMI, GIS, and weather data — making it hard to target right-of-way investment or proactive replacement before problems recur.
Four capabilities built around how utilities actually operate — from querying systems in place to reducing reliability metrics, all without a warehouse build.
QuaerisAI connects to AMI, SCADA, OMS, GIS, billing, and document systems as data sources and lets staff ask plain-English questions across all of them — no central data warehouse, no months-long ETL project, no IT ticket.
QuaerisAI learns each system's schema and business definitions automatically through the Smart Semantic Layer, then joins data across them at query time. A single question pulls blink counts from the OMS and work orders from the asset and GIS systems and produces one answer.
By combining OMS, AMI, GIS, and weather data, teams spot the patterns behind outages before they recur and assemble a unified incident snapshot in seconds — cross-referencing blink counts with vegetation work-order history and detecting transformers operating above rated capacity.
QuaerisAI runs inside the utility's own VPC or on-prem environment, routes every query through a governed semantic layer that blocks arbitrary table access, and lets you bring your own model. Customer data stays inside the utility's controlled environment.
Agentic analytics can be deployed safely on critical infrastructure when it runs inside the utility's own environment, uses a governed semantic layer, and produces a full audit trail. QuaerisAI is architected around exactly these properties — the controls NERC CIP, SOC 2, HIPAA, and EU AI Act assessors actually evaluate.
Runs inside the utility's own VPC or on-prem environment. Customer data stays in your controlled environment.
A governed semantic layer blocks arbitrary table access and prevents free-form SQL.
A prompt-level audit log records who asked what, which model answered, and which steps the agent executed.
BYOM: the AI model is your choice across OpenAI, Anthropic, Google, Meta, or a private/on-prem model.
QuaerisAI transformed how our operations team accesses data. Instead of waiting for weekly reports, our engineers get answers in seconds, with full traceability back to the source. We've cut incident response time dramatically.
QuaerisAI works with your existing AMI, SCADA, GIS, OMS, and billing systems — no data movement, no warehouse build, full governance built in.
