Inerra
Dubai · United Kingdom · Working across the GCC

Your plant already knows. Nobody upstairs can see it.

The number that tells you how the operation is really performing may be sitting in a holding register, buried inside a reporting model or fragmented across an enterprise data estate. Inerra connects the source, builds the platform and turns the data into something the business can use, from the terminal block to the lakehouse and the AI built on top of it.

Book a call See the architectures
50+ MWConnected generation
50%Faster source onboarding
PLC → cloudOne platform, both ends
Live AIIn our own products
Plant overview · Site 01 Live
On-site generation501.0kWGrid import 0.0 kW
Availability96.4%Generation fleet, 30-day
Energy intensity0.38kWh/tTarget 0.35 · 8.6% above
CHP1_ENG_T0033_LOAD412.6 kW
SOL_INV_01_PAC88.4 kW
GEN_PS0600_STATUSAvailable

Where we work

  • CHP & generation
  • Solar PV
  • Automotive manufacturing
  • Heat networks
  • Building services
  • Enterprise data estates

What we do

Three practices. One team that covers all of it.

Most industrial data projects stall in the gap between the people who understand the panel and the people who understand the platform. There is no gap here. One team owns the register map and the lakehouse, and has done for twenty-five years.

OT integration

Getting data out of equipment that was never built to share it, without putting the process at risk. Register maps, polling logic, panel modifications and commissioning.

  • TIA Portal SCL
  • Modbus TCP/RTU
  • PROFINET
  • Panel design
  • Commissioning

Energy monitoring

Metering strategy through to reporting for CHP, solar and building systems. Fifteen years of it, on plant that has to keep running while you measure it.

  • CHP & generation
  • Solar PV
  • Heat metering
  • BMS
  • M&V reporting

Azure and data engineering

Enterprise data platforms built with the same ownership and engineering depth as the systems that feed them. Data mesh architecture, governed data products, and the platform engineering underneath them.

  • Data mesh
  • Microsoft Fabric
  • Databricks
  • Azure IoT Hub
  • Entra ID

Applied AI

From reliable data to applied AI

AI becomes useful when the data behind it is reliable, understood and connected to a real decision. We build the foundations first, then apply AI where it can improve operations, reduce manual work or identify problems earlier.

  • Detect abnormal equipment behaviour
  • Identify patterns associated with emerging equipment problems
  • Extract information from technical documents
  • Ask questions across operational and enterprise data

What you get

What changes when the data works

The practical improvements the business sees once its operational and enterprise data can be trusted.

  • Operations sees problems sooner
  • Reporting stops depending on manual spreadsheets
  • New sites and sources become easier to onboard
  • Energy use can be compared against production
  • IT gains a secure and governable platform
  • AI use cases can move beyond demonstrations

Sample architectures

Four patterns, four sides of the business.

Pure data engineering, enterprise architecture, industrial IoT and applied AI. Drawn with the components that are actually in them. Open any one for the full case.

Data platform

Medallion lakehouse on Microsoft Fabric

A charge point operator growing fast, with a Power BI import model breaking under the weight of it: large files, slow refreshes, and one person who understood how it held together. We replaced it with a full medallion lakehouse on Fabric and owned every architectural and cost decision. It later absorbed a full CPMS migration with no structural rework, because the separation of concerns was right first time.

  • Microsoft Fabric
  • OneLake
  • Delta Lake
  • PySpark
  • Azure Functions
  • Power BI

Sources

CPMS
OCPP messagesCharger telemetry
Billing and CRM

Ingest

Fabric Data PipelinesBatch sources
Azure FunctionsReal-time OCPP

Bronze

OneLake / DeltaRaw, append only

Silver

PySpark notebooksDedup, nested struct coercion
Delta MERGE upserts

Gold and use

Star schema
Power BI
Fault alerts to engineers

Delivered: real-time OCPP ingestion for proactive charger fault detection, cutting engineer response time to critical errors. Client named on request.

Read the case study →
Data platform

Secure enclave inside an enterprise data mesh

The sensitive and secret data domain of a global energy supermajor's data mesh, holding PII, sensitive and classified data at organisational scale. SOX and GDPR were designed into the architecture rather than bolted on afterwards, and the controls sit at the boundary, so a team that needs the data does not have to stand up a platform of its own to hold it.

  • Azure
  • Data mesh
  • Data tokenisation
  • Custom RBAC
  • Private Link
  • Key management
  • Azure DevOps

Restricted sources

Sensitive domain data
Classified data
PII

Boundary

Private LinkNo public path in
Data tokenisation
Access approval

Enclave

Isolated storageCustomer-managed keys
Governed compute
Custom RBAC

Published

Governed data product
Full audit trail

Consumers

Approved teams only
SOX and GDPR in the design · risk register kept to audit standard · roadmap owned across multiple quarters

Delivered: led the security engineering team on the design and build. Every stage approved by a Security Architectural Review Board of more than ten members at VP and SVP level. Client named on request.

Read the case study →
IoT architecture

Distributed generation platform, one site to 50 MW

A multi-tenant platform for renewable and industrial generation across some of the UK's largest manufacturers, built so a new site or a new generation technology could be onboarded without major development. The commercial model carried no CAPEX, so cloud cost per site had to keep falling as the portfolio grew.

  • Azure IoT Hub
  • IoT Edge
  • Stream Analytics
  • Azure Data Explorer
  • Azure Digital Twins
  • SignalR

Plant

CHP engines
Solar inverters
PLCsPlant control
MetersModbus TCP/RTU

Edge

Edge modulesGeneration against site demand, export margin, grid events

Ingest

Azure IoT Hub

Process and store

Stream Analytics
Azure Digital TwinsSite and asset model
Azure Data ExplorerTime series telemetry

Use

SignalR dashboardsReal-time
Grid balancing

Delivered: grew from a single CHP site to over 50 MW of live generation, with cloud cost per site trending down as the portfolio grew.

Read the case study →
Applied AI

AI-assisted property inspection

The architecture behind Tamaneena, our own product. An inspector walks a unit and photographs the defects, and the platform turns the images, the room and defect context and the notes into a contractor-ready snagging report. A person signs off, and every step leaves an audit history. Practical AI on a governed platform, not a demo.

  • Image analysis
  • Defect classification
  • Description generation
  • Human review
  • Audit history

Inputs

Site photographs
Room and defect context
Inspection notes

AI processing

Image analysis
Defect classification
Description generation
Severity and trade suggestion

Application

Human reviewA person signs off
Contractor-ready report
Audit history

Delivered: live as Tamaneena in the UAE, proof that we build AI applications that reach production.

Explore all architectures →

How we work

Start with the problem. Build what proves the answer.

Some projects begin with a PLC or meter. Others begin with an unreliable report, a fragmented data estate or a cloud platform that no longer scales. We start by understanding the problem, the systems involved and what a successful outcome looks like.

01

Understand the real problem

We review the systems, data sources, architecture and processes already in place. That might mean tracing data from plant equipment, assessing a Fabric environment, investigating a failing reporting process or finding out why an existing platform has become difficult to scale.

You receive: a clear view of the problem, the practical options and the best place to begin.

02

Prove the right approach

We design and build a focused first outcome using real data and real operating conditions. That could mean connecting one asset, rebuilding one reporting flow, creating a governed lakehouse domain or automating a critical business process.

You receive: a working solution that proves the approach and reduces the risk of wider investment.

03

Build it for production

Once the approach is proven, we make it reliable, secure and repeatable. We add the testing, monitoring, deployment processes, documentation and governance needed for day-to-day operation and future growth.

You receive: a production-ready platform built to scale.

04

Make the capability yours

Your team receives the source code, infrastructure definitions, data models and documentation needed to understand and extend what has been built. We can continue to support and develop the platform, but the knowledge and control stay with you.

Bring us the problem, wherever it begins. A register map. A failing report. A fragmented lakehouse. A manual process. An architecture that no longer scales.

Products

We operate the software we build.

Tamaneena, Equipy and Factory Doctor run on the same engineering principles we put behind client work. Building and operating our own products keeps our decisions grounded in security, reliability, cost and the realities of production support.

Tamaneena

Live · UAE

AI property snagging for the UAE. Walk the unit, photograph the defect, and leave with a contractor-ready snag report instead of a spreadsheet nobody reads.

ProvesApplied AI, document generation and workflow

Snag list · Unit 1204
Kitchen · cabinet door misaligned Open
Master bath · grout crack Open
Living · paint blemish, north wall Fixed
Visit tamaneena.ae →

Equipy

Asset tracking

Asset tracking and hire management for people who own kit that moves. GPS and BLE tags on the equipment, with hire contracts and utilisation on the same screen.

ProvesIoT, location data, multi-tenancy and operational software

Assets · last seen
Generator 60 kVA · GEN-014 On hire
Telehandler · TLH-002 On hire
Compressor · CMP-021 Yard · 6 days
Visit equipy.io →

Factory Doctor

Live · UK & UAE

A virtual consultant for manufacturing sites. It asks the right questions for your equipment, scores the site across eleven areas from energy to maintenance, and hands back a prioritised plan, then re-scores as the team acts on it.

ProvesApplied AI, industrial diagnostics and multi-tenant SaaS

Site score · 49 / 100
Compressed air leak repairs +4 pts
Submeter the three biggest loads +3 pts
Condition monitoring on CNC cells +5 pts
Visit factory.doctor →

Who you would be working with

Inerra is led by an engineer who has worked every layer this business touches, from PLC code on the panel to the data mesh in the cloud.

Twenty-five years in software, more than a decade of it in the cloud. The path runs the wrong way round for this industry: software first, then cloud architecture and big data engineering on Azure and Microsoft Fabric, and only then into OT and IT integration, PLC programming and industrial automation. That is why Inerra can own the register map and the lakehouse in one team, rather than handing off in the middle where most projects break.

The recent work sits at both ends. On the plant side, polling fleets of engines, meters and inverters onto one tag model and into Azure. On the enterprise side, leading the security engineering for the sensitive data domain of a global energy supermajor’s data mesh, where every stage was signed off by a review board at VP and SVP level.

Alongside the consultancy, Inerra ships its own software, Tamaneena and Equipy, on the same Azure platform it puts behind client work. The industrial thinking is also written down: the principal is the author of The Modern Factory Handbook and the creator of the Factory Doctor diagnostic.

Selected work

Selected work across plant and platform.

Plant

CHP fleet
Modbus polling across a mixed fleet of engines, heat meters, gateways, boilers and standby generation, normalised into one tag model.
One view of the fleet
Automotive plant
Distributed I/O design and wiring instructions for a UK vehicle manufacturing site, issued to the installing contractor.
Installed first time
Solar & BMS estate
Inverter polling written in SCL and proven against an emulator before commissioning. Integration panel with watchdog and automatic reset.
No truck roll for a hung link

Platform

Charge point operator
Medallion lakehouse on Microsoft Fabric replacing a failing Power BI import model, with real-time OCPP ingestion for proactive fault detection.
CPMS migration absorbed
UK insurance
Standardised ingestion on Databricks with a governance layer on Unity Catalog, taken on as architect mid-engagement.
Onboarding time halved
Energy supermajor
Security engineering for the sensitive data domain of an Azure data mesh: tokenisation, custom RBAC and Private Link, signed off by a VP and SVP review board.
Signed off at board level

Start here

Not sure where to begin?

Send us a register map, architecture diagram, sample report or a brief description of the problem. We will help you work out what is practical, where the value is and what the first step should be.

Talk to us about your project Book a call
Email hello@inerra.ae
Phone +971 44 465 248
Regions UAE · GCC · UK
Base Dubai & United Kingdom
Typical start A focused assessment or first use case