System Silos
14 systems. Zero joins.
Billing lives in Oracle. SCADA in a proprietary historian. Meter reads in flat files. GIS in a spatial DB. Each system answers one question. None answer cross-system questions.
Sector
Power & Distribution
Grid data unified. Losses recovered.
QWRY connects SCADA, billing, metering, GIS, and consumer databases into one queryable warehouse, without replacing any of them. AT&C loss analytics, tamper detection, and demand forecasting become questions you can ask in plain English.
SCADA & Billing Unified
AT&C Loss Analytics
Tamper Detection
On-Prem Ready
01The Problem
The data exists. The correlation doesn't.
A DISCOM runs dozens of data systems across billing, metering, SCADA, GIS, and consumer databases, none of them joined. Cross-system questions that should take minutes take weeks.
AT&C Losses
Loss identification takes weeks.
Correlating energy injected with energy billed requires joining SCADA with billing with consumer records. Without QWRY, this is a manual exercise repeated every quarter.
Tamper Detection
Tampering is visible. Suspects aren't.
Anomalous consumption patterns exist in the data. Matching them to consumer accounts, transformer zones, and field inspection history requires cross-database joins that don't exist today.
Demand Forecasting
Forecasts without full context.
Demand models built on billing data alone miss SCADA load curves, seasonal patterns, and infrastructure constraints that sit in separate systems.
02Use Cases
Questions your teams ask every day.
Each of these queries joins SCADA, billing, metering, and GIS data, with verified SQL behind every answer, inside your perimeter.
Use Case 01
AT&C Loss Attribution
Join energy injected (SCADA) with energy billed (billing DB) by feeder, transformer, and zone. Surface the feeders and divisions where technical and commercial losses exceed thresholds.
SCADABilling DBGIS
Use Case 02
Tamper Candidate Surfacing
Cross-reference anomalous consumption patterns with meter read sequences and transformer load data. Rank tampering candidates by confidence score and zone, before field teams are dispatched.
Meter ReadsBillingSCADA
Use Case 03
Demand Forecasting
Combine SCADA load curves with billing history, weather data, and infrastructure records. Generate feeder-level forecasts that account for the full system context.
SCADABillingGIS
Use Case 04
Outage Root Cause
Join outage events with maintenance records, asset age, and load history. Identify the assets and zones at highest risk before the next failure, not after it.
SCADAMaintenance DBGIS
Use Case 05
Revenue Recovery Tracking
Track disconnection, reconnection, and regularisation actions against identified loss clusters. Measure the revenue impact of enforcement campaigns in real time.
BillingField RecordsFinance
Use Case 06
Regulatory Reporting
Generate AT&C loss statements, energy audit reports, and compliance submissions directly from the unified warehouse. Every figure traces to its source query.
All SourcesAudit Trail
03Capabilities
Built for the data complexity of grid operations.
Connectivity
Reads legacy systems without replacement
Oracle billing, proprietary SCADA historians, flat-file meter exports, GIS databases. QWRY connects to what is already running, with no system replacement and no migration project.
Verification
Every loss figure has a source query
AT&C percentages, tamper candidate counts, revenue figures; every number in the warehouse traces to the SQL that produced it. Admissible in regulatory submissions.
Sovereignty
Data never leaves your perimeter
On-premise deployment with your own PostgreSQL warehouse. SCADA and consumer data stays inside your infrastructure. QWRY orchestrates; you own everything.
Workspace
Plain English for non-technical teams
Revenue officers, field supervisors, and regulatory teams query the warehouse in plain English. The platform generates SQL, verifies the answer, and returns a result anyone can act on.
Use cases, deep-dives & field notes.
Customer playbooks and technical deep-dives from QWRY deployments in power & distribution.
Use Case
SCADA
Billing DB
GIS
qwry
How a state DISCOM unified 14 billing & SCADA systems in 42 days, recovering ₹118 Cr in AT&C losses.
Inside the integration playbook: relationship discovery across legacy Oracle, MariaDB, and flat-file billing exports, and how cross-source joins surfaced 23,000 tampering candidates in the first month.
Read the case study
Technical
JOIN scada ON billing.meter_id
→ 94% match · conf 0.97
→ 94% match · conf 0.97
Why cross-source relationship discovery is a data graph problem, not an LLM problem.
Under the hood of qwry's sampling engine: how we score column overlap, detect cardinality, and turn it into a confidence-ranked relationship graph across heterogeneous grid data sources.
Read the deep-dive
Blog
"
AT&C loss recovery: what the data already knows.
Why billing data and SCADA telemetry together contain enough signal to flag revenue leakage, and why most DISCOMs never see it because the two datasets never talk to each other.
Read the postReady to recover
what the data already shows?
A direct technical conversation with the founding team. No sales deck. Tell us about your systems and we'll map out what becomes possible when they behave like one.
Email goes directly to the founding team. First response within one business day.