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TashIT

Find losses, recover revenue, keep assets running

Power, gas and water utilities and mining operators run large networks on incomplete data. We turn meter, SCADA, billing and field data into a ranked list of where losses happen and which assets need attention.
Discuss your operationRecommended solutions
Where we would start
Utility Loss & Revenue Assurance
Typical pilot length
10–16 weeks
How we engage
Paid diagnostic, then a paid pilot

Operating context

What is changing for utilities and energy operators in 2026

Utilities are under pressure from both sides. Regulators set loss and unaccounted-for-gas targets and increasingly link allowed tariffs or margins to them, while customers facing high bills look for ways to pay less, legally or otherwise.

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Advanced metering programmes and new bulk meters produce far more data than billing teams can review, and rooftop solar is changing load profiles and revenue in many networks. In Pakistan, the privatisation of distribution companies and regulator-set loss benchmarks put loss reduction at the centre of every tariff discussion. In the GCC, utilities are investing in smart metering and non-revenue water programmes. Mining and generation operators face the same availability question for haul fleets, turbines and pumps.

Regulatory points are general information, not legal advice. Rules change, so check the current position with your advisers.

Challenges

Common challenges for utilities and energy operators

These are the problems that cost the most and that data, software and automation can measurably reduce.

  • Technical and commercial losses

    Energy, gas or water enters the network and never reaches a paid bill. Separating technical loss from theft, meter faults and billing errors means balancing supply against consumption at every level of the network.

  • Meter data without action

    Smart and bulk meters generate interval readings, events and tamper flags, but teams lack the tools to rank which feeders, stations or customers to inspect first.

  • Low recovery and billing disputes

    Estimated bills, wrong tariffs and slow dispute handling reduce collections and erode customer trust.

  • Asset availability

    Transformers, compressors, pumps, turbines and mining fleets fail without warning, and maintenance budgets are spread evenly instead of by risk.

  • Data spread across systems

    SCADA, GIS, billing, customer service and field crews each keep separate records, so a single loss investigation needs four exports and a spreadsheet.

Use cases

Where AI and automation pay back for utilities and energy operators

Applications we can design and build for this sector. Each can start as a contained pilot covering a single feeder group, supply zone or asset class.
Scope a pilot with us
  1. Feeder, district and pressure-zone balance analytics that quantify loss at each level
  2. Theft and meter-fault scoring that ranks customers and sites for inspection
  3. Billing anomaly detection for wrong tariffs, stuck meters and repeated estimates
  4. Field inspection apps that record findings and feed results back into the model
  5. Condition monitoring and failure prediction for transformers, pumps, compressors and haul trucks
  6. Pumping and compression energy optimisation for water and gas networks
  7. Private AI assistants that answer staff questions from procedures, tariffs and network records

Recommended solutions

Where we would start

Solutions for utilities and energy operators with a defined scope, data requirements and pilot plan. Each page explains how it works and how success is measured.

Relevant services

Capabilities behind the work

The disciplines we combine for this sector, from data integration and AI to the software your teams use every day.

FAQ

Questions about a first project

Answers for utilities and energy operators weighing up a first pilot.

How we engage

  1. Step 1: Paid diagnosticTypically 1–3 weeks

  2. Step 2: Paid pilotFixed scope, measures agreed in writing

  3. Step 3: Rollout or managed serviceScoped after the pilot

How our engagement models work
What is a good first AI or automation project for utilities and energy operators?

We would suggest starting with 10-20 feeders or one supply zone. It runs as a fixed-scope paid pilot, after a short paid diagnostic, with a baseline and success measures agreed in writing before it starts, so you decide on rollout with evidence in hand.

How long does a pilot take?

Typically 10–16 weeks, after a paid diagnostic of 1–3 weeks. Length depends mainly on access to meter, billing and network data, and how quickly field teams can verify the top-ranked cases. The pilot ends in a clear go or no-go decision against the measures agreed at the start.

What data do you need to get started?

We usually ask for supply or bulk meter readings for the pilot area; customer master and 24–36 months of billing and consumption history; network topology linking customers to feeders, stations or zones; past inspection and theft case records. During the paid diagnostic we review what you already have and say plainly where gaps need to be closed.

Which solutions would you start with?

We would usually start from Utility Loss & Revenue Assurance, Predictive Maintenance & Fleet Intelligence, Energy Monitoring & Dispatch Optimisation or Enterprise AI Agents & Private AI. Each has a defined scope, data requirements and pilot plan, set out on its own page.

Do you work outside Pakistan?

Yes. TashIT is headquartered in Pakistan, our first market, and works with clients internationally, including in the GCC. Regulatory points on these pages are general information, not legal advice.

Related industries

Sectors with similar problems

These industries share several of the same solutions, so the same building blocks and methods carry across.

Start with one measurable pilot

Tell us which site, network or process you want to improve and the number you want to move. We will reply with a scoped first step, the data we would need and an honest view of the likely value.

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