UK's First SME Infrastructure AI Platform · TRL-7 Prototype Ready

Predictive Intelligence
for the Grid of Today.
Reliability for Tomorrow.

GridOps Intelligence transforms fragmented industrial telemetry into unified, actionable reliability scores detecting failure precursors up to 14 days in advance with sub-500ms Edge-AI processing. Purpose-built for UK SME utility providers, renewable energy operators, and local councils.

LIVE MONITORING
GridOps Asset
Criticality Dashboard
GRID HEALTH
98%
OPTIMAL
⚡
Assets Monitored (Live)
5,000+
🔍
Failures Predicted (This Month)
147
🛡️
Outage Risk Level
LOW
📡
Telemetry Events / Hour
25,000
🏭
Energy Flow (Total Output)
12.4 GW
✅
NIS 2018 Compliance
99.9% UP
£2.8B
UK Industrial AI & Predictive Maintenance Market by 2028
Market Research 2024
30,000+
UK localized infrastructure sites lacking predictive oversight
GridOps Analysis 2025
£2M/hr
Maximum cost of unplanned downtime in industrial sectors
Industry Reports 2024
NIS 2018
UK regulatory mandate driving SME infrastructure compliance
UK Government 2018
Our Platform

Three Engines. One Intelligent Infrastructure AI Platform.

GridOps Intelligence combines real-time Edge-AI processing, multiaxial vectorization, and federated learning into a unified platform that transforms fragmented industrial telemetry from a reactive guessing game into a proactive, compliance-ready reliability standard.

Predictive Drift Detection
Engine 01

Predictive Drift Detection Matrix

Identifies micro-variances in thermal, vibration, and electrical data that precede major failures by up to 14 days well before traditional alarm systems trigger.

GridOps uses a proprietary algorithmic matrix that distinguishes between operational "noise" and genuine failure precursors across substations, wind turbines, solar inverters, and water pumping stations. Each asset learns its own operational baseline, preventing nuisance alarms.
Federated Failure Repository
Engine 02

Federated Failure Repository

Overcomes the SME "small data" barrier by enabling industry-wide failure signatures through a privacy-preserving federated learning framework zero raw data sharing.

Every GridOps deployment strengthens the collective intelligence repository with anonymized failure precursors. SME operators benefit from national-scale predictive accuracy while their commercially sensitive operational data remains fully encrypted and sovereign.
Zero-Overhaul SCADA Bridge
Engine 03

Zero-Overhaul SCADA Bridge

Structures data directly from legacy Modbus and DNP3 protocols without requiring expensive hardware replacements the only platform designed for the UK's aging assets.

UK SMEs can unlock Tier-1 predictive intelligence from their existing SCADA infrastructure within weeks. No rip-and-replace. No proprietary sensors. No middleware overhaul. The IIoT Bridge extracts and structures legacy industrial data, feeding it directly into the AI reliability engine.
Our Mission

Transforming Reactive Infrastructure Management into AI-Powered Predictive Reliability

GridOps Intelligence was founded on a clear premise: the thousands of UK SMEs managing localized substations, renewable energy sites, and industrial assets are trapped in a cycle of reactive maintenance. This reliance on "fix-it-when-it-breaks" strategies leads to unplanned outages, excessive operational costs, and systemic risks to the UK's localized energy resilience.

With unplanned downtime in industrial sectors costing between £35,000 and £2 million per hour, GridOps delivers the UK's first AI-powered predictive operations platform specifically designed for SME infrastructure providers combining multiaxial vectorization, behavioral drift detection, and privacy-preserving federated learning.

Built by infrastructure operations professionals with deep experience in mission-critical energy environments, GridOps Intelligence democratizes enterprise-grade reliability making it accessible, affordable, and compliant for every UK SME operator.

Multiaxial Asset Criticality Vectorization
Behavioral Drift Detection Matrix
Federated Failure Repository
Zero-Overhaul SCADA Bridge
Offline-First Edge-AI Inference
Automated NIS 2018 Compliance
UK Net Zero 2050 Aligned
UK GDPR · ISO 27001 Ready
Founder & CEO

Muhammad Shujaat Shabbir

MSc Digital Marketing · University of Chester · BSc (Hons) Information Technology · Microsoft Azure Administrator · Network Security Specialist · Former HUBC (Pakistan's Largest IPP)

Muhammad brings over 6 years of experience in mission-critical IT infrastructure, enterprise operations, and energy sector stability. His tenure at The Hub Power Company (HUBC), Pakistan's largest Independent Power Producer, provides GridOps with an authentic foundation in operational reliability and large-scale infrastructure management.

His expertise bridges high-performance systems engineering and strategic product growth ensuring GridOps Intelligence is built on a foundation of real-world operational reality, not just theoretical data science. He personally reviews and signs off on all critical security and compliance documentation, ensuring technical accountability remains a core pillar of operations.

Growing the Team · Phase 2

Strategic UK Hires

Evidence-Based Recruitment Plan

GridOps Intelligence is building its core team through a phased, revenue-linked strategy: an OT Security Engineer to refine the zero-trust monitoring framework; an Infrastructure Data Analyst to oversee the federated failure repository; and Implementation Specialists to lead field deployments and SME client onboarding.

All hires are UK-based, aligned with the UK's National AI Strategy and NIS 2018 mandates. By Year 5, the platform targets 38 high-skilled UK jobs across industrial AI, OT cybersecurity, and global commercial functions.

The Platform

Every Layer of GridOps Intelligence's Asset Reliability Engine

GridOps Intelligence is a cloud-native SaaS platform built on a modular architecture real-time Edge-AI dashboards, legacy SCADA bridge integration, proprietary vectorization logic, and UK GDPR-compliant infrastructure designed to serve UK infrastructure SMEs without requiring internal data science teams.

Multiaxial Asset Criticality Vectorization
Module 01

Multiaxial Asset Criticality Vectorization

Deep learning models that analyze real-time signals from meters, sensors, and SCADA logs evaluating each asset based on systemic impact, not just simple threshold breaches.

Calculates a "Dynamic Criticality Score" considering load variations, environmental stress, and grid position updating in real-time so operators prioritize high-risk components before cascading failures occur. Unlike generic IoT dashboards, this is asset-context-aware intelligence.
Behavioral Drift Detection Matrix
Module 02

Asset Behavioural Drift Detection Matrix

Identifies early-stage degradation through micro-variance accumulation analysis distinguishing between operational "noise" and genuine failure precursors with 94% accuracy.

Trained on UK-specific infrastructure asset profiles. Provides algorithmic identification of thermal, vibration, and electrical drifts that correlate with emerging failure signatures delivering a 14-day early-warning window unavailable to static alarm systems.
Micro-Failure Event Correlation Synthesizer
Module 03

Micro-Failure Event Correlation Synthesizer

Aggregates low-severity anomalies into composite failure signatures, providing a 14-day early-warning window for planned interventions across all asset classes.

Correlates disparate telemetry signals (thermal, vibration, and electrical) into a single unified failure prediction event. Traditional monitoring misses the "quiet inefficiencies" GridOps makes them visible, auditable, and actionable before they escalate.
Edge-First Offline Monitoring
Module 04

Edge-First Offline Monitoring Layer

Processes critical telemetry locally on NVIDIA Jetson modules ensuring 24/7 oversight for remote wind farms, rural substations, and low-connectivity industrial sites.

Sustains 95% of predictive functionality during complete network dropouts. Once reconnected, the cloud-integrated engine synchronizes data to update global reliability models. Localized processing also minimizes the data attack surface, enhancing cyber-physical security.
Privacy-Preserving Federated Learning
Module 05

Privacy-Preserving Federated Learning

Enables SMEs to benefit from industry-wide failure signatures through a federated repository without ever sharing raw, commercially sensitive operational data.

Creates a "Collective Resilience Moat" where every new asset deployment strengthens predictive accuracy for all users in the network. Fully aligned with UK GDPR and OT security standards. The only SME-focused tool solving the "small data" problem through encoded, privacy-first learning cycles.
Automated NIS 2018 Compliance Reporting
Module 06

Automated NIS 2018 Compliance & Reporting

Automatically generates the audit trails and resilience reports required by Ofgem and UK regulators transforming compliance from an administrative burden into an operational advantage.

Maintains an immutable audit trail of maintenance actions and efficiency gains. Maps asset performance against UK energy standards and Net Zero compliance requirements in real-time making SMEs "audit-ready" without dedicated compliance teams or additional administrative overhead.
Market Analysis

A £214M UK Infrastructure AI Market. 30,000+ Sites. A Clear Reliability Gap.

The UK presents a structurally underserved market for intelligent infrastructure reliability management. With over 30,000 UK localized energy and industrial sites managed by SMEs that lack enterprise-grade predictive oversight, the demand for GridOps Intelligence's platform is both urgent and commercially validated.

£2.8B
UK industrial AI and predictive maintenance market projected by 2028 at 7.2% CAGR
UK Industry Data 2024
30K+
Active UK localized infrastructure sites in target sectors without predictive monitoring
GridOps Research 2025
£214M
Total Addressable Market across energy, utilities, facilities management and industrial sectors
GridOps Market Analysis
UK Infrastructure Failure Cost Impact
Cost contributors to unplanned downtime across UK SME infrastructure operators
Current Monitoring Methods The Reliability Gap
Where UK infrastructure SMEs currently fail to predict asset failures
GridOps Intelligence vs Competitors Capability Comparison
How GridOps' predictive reliability platform compares to existing industrial AI tools
UK & Global Predictive Maintenance Market Growth
Market size trajectory and projected UK SME adoption rate 2022–2030
£85M
Energy & Utilities TAM (8,500 sites)
£100M
Industrial Manufacturing TAM (20,000 plants)
7.2%
UK Industrial AI CAGR to 2028
145
Clients needed to exceed £1M ARR
GridOps Intelligence Platform Performance vs Industry Average
Comparing GridOps' predictive reliability capabilities against existing enterprise and SME monitoring tools
How It Works

From Fragmented Telemetry to Unified Reliability in Six Phases

GridOps Intelligence's predictive operations lifecycle moves UK infrastructure SMEs from reactive "fix-it-when-it-breaks" maintenance to proactive, data-driven reliability management protecting asset uptime, reducing grid costs, and ensuring permanent regulatory compliance.

Phase 01 · Connect

Connect & Ingest Legacy SCADA & Industrial Sensor Data

GridOps Intelligence connects directly to legacy SCADA systems, industrial IoT sensors, energy meters, and operational technology via a Zero-Overhaul software bridge. No hardware replacement. No middleware overhaul. The platform structures data from Modbus and DNP3 protocols instantly.

Apache Kafka and MQTT brokers automate the ingestion of high-frequency data from industrial sensors and legacy meters providing sub-300ms data pipeline latency across substations, renewable energy sites, and industrial facilities.

SCADA Bridge Setup Protocol-Agnostic APIs Real-Time Telemetry
Phase 01 – Connect
Phase 02 – Vectorize
Phase 02 · Vectorize

Build Each Asset's Unique Criticality Vector

The Multiaxial Asset Criticality Vectorization engine evaluates each asset based on its systemic impact calculating a "Criticality Score" that considers load variations, environmental stress, and grid position. Unlike generic threshold alerts, this is context-aware intelligence.

This Criticality Score is stored as the asset's permanent operational intelligence ensuring that failure patterns are recognized even through staff turnover or seasonal infrastructure changes, eliminating institutional "knowledge loss."

Criticality Scoring Asset Intelligence Systemic Impact Mapping
Phase 03 · Detect

Behavioral Drift Detection 14 Days Before Failure

The Asset Behavioural Drift Detection Matrix identifies "micro-variances" tiny anomalies in thermal, vibration, and electrical data that precede major failures. The system distinguishes genuine failure precursors from operational noise with 94% accuracy.

When a transformer begins subtle thermal drift or a wind turbine bearing shows irregular vibration patterns, GridOps detects the composite failure signature weeks before a catastrophic failure occurs providing a vital planned intervention window.

14-Day Early Warning Sub-500ms Alerts Drift Pattern Analysis
Phase 03 – Detect
Phase 04 – Edge AI
Phase 04 · Edge Process

Edge-AI Inference 24/7 Even Without Connectivity

The Edge-First architecture processes critical telemetry locally on NVIDIA Jetson Orin modules ensuring uninterrupted 24/7 monitoring for remote wind farms, rural substations, and industrial sites with limited or no network connectivity.

Unlike cloud-dependent competitors, GridOps sustains 95% of its predictive functionality during complete network dropouts. Localized processing also minimizes data attack surfaces providing built-in OT cybersecurity for infrastructure assets.

Offline-First AI 95% Uptime Offline OT Cyber Protection
Phase 05 · Act

Automated Maintenance Workflows & Prioritized Work Orders

GridOps automatically generates prioritized maintenance work orders based on failure probability and asset criticality scores. Front-line operators receive clear, actionable intelligence no data science team required. The right engineer is dispatched to the right asset at the right time.

Human-in-the-loop verification ensures high-risk criticality scores are reviewed by senior engineers before automated actions maintaining governance requirements for essential UK infrastructure services.

Auto Work Orders Criticality-Ranked Human-in-the-Loop
Phase 05 – Act
Phase 06 – Comply
Phase 06 · Comply

Automated NIS 2018 & Ofgem Compliance Reporting

GridOps closes the loop automatically generating immutable audit trails and resilience reports required by Ofgem and UK NIS 2018 regulators. Compliance becomes an operational advantage, not a manual administrative burden.

Every maintenance action, criticality score, and efficiency gain is logged, encrypted, and stored in a GDPR-compliant digital archive keeping SME operators "audit-ready" at all times without dedicated compliance staff.

NIS 2018 Automated Ofgem Audit-Ready Immutable Audit Trail
Pricing & Plans

Tier-1 Reliability at 10% of Enterprise CAPEX

GridOps Intelligence operates on a B2B SaaS and Edge-hardware model, offering tiered subscription access designed for SME budgets. No data science team required. No expensive hardware overhaul. Just affordable, always-on AI reliability.

SME Site
Basic Tier
£299/month
Per infrastructure site · Up to 50 assets
Monitoring for up to 50 active assets
Real-time behavioral drift alerts
Standard NIS 2018 compliance reporting
Legacy SCADA bridge (Modbus/DNP3)
Ideal for micro-grids & pumping stations
Email & portal support
Most Popular
Regional Operator
Professional Tier
£749/month
Per operator portfolio · Up to 250 assets
Monitoring for up to 250 active assets
Advanced criticality vectoring & scoring
API access for SCADA integration
Sector-specific reliability modules
Priority technical support
Federated learning repository access
Utility Provider
Enterprise Tier
Avg. £1,499/mo
Unlimited assets · Custom compliance mapping
Unlimited active asset monitoring
Full federated learning repository access
Custom Ofgem compliance mapping
24/7 mission-critical support
Edge-AI hardware kit included
Dedicated implementation specialist
Sector Add-Ons

Specialized Reliability Modules

⚡
Renewable Energy Module
£599/year
Optimized for solar inverters and wind turbine bearing monitoring
🏭
Electrical Substation Module
£499/year
Thermal and electrical drift signatures for transformers and switchgear
💧
Water Utility Module
£399/year
Pump cavitation detection and pressure-drift analysis for water networks
Edge-AI Hardware Kit

NVIDIA Jetson-Based Industrial Gateway

Pre-configured Edge-AI gateway for real-time monitoring in remote or low-connectivity sites. Includes 1-year software license, multi-protocol SCADA bridge, and ruggedized IP67-rated environmental housing.

NVIDIA Jetson Orin Modbus & DNP3 Ready 1-Year License Included
£3,800
Per unit + VAT
FAQ

Frequently
Asked
Questions

Everything UK infrastructure operators need to know about GridOps Intelligence's predictive reliability platform, deployment process, and compliance credentials.

Pilot Programme

Join Our Phase 1 Launch Cohort

GridOps Intelligence is actively recruiting regional energy contractors, local council infrastructure teams, and renewable energy operators for a 12-week proof-of-value pilot. Strategic framework agreements are already in discussion with localized utility contractors.

12-Week Paid Pilot UK Energy & Water Sectors Free Reliability Audit

What types of UK infrastructure does GridOps Intelligence support?

+
GridOps Intelligence supports SME Independent Power Producers (IPPs), localized grid substations, renewable energy sites (solar and wind), water distribution networks, district heating networks, industrial manufacturing facilities, and facilities management estates. The platform's modular architecture allows rapid cross-sector deployment without retraining the core drift detection logic.

Do we need to replace our existing SCADA hardware?

+
No. GridOps Intelligence's proprietary "Zero-Overhaul" SCADA Bridge is specifically designed to extract and structure data from aging Modbus and DNP3 industrial protocols without requiring expensive hardware replacements. UK SMEs can unlock Tier-1 predictive intelligence from their existing infrastructure within weeks at 10% of the CAPEX of traditional enterprise upgrades.

How does the Federated Learning Repository protect our data?

+
GridOps encodes failure precursors into anonymized signatures using a federated learning architecture meaning raw, commercially sensitive operational data never leaves your infrastructure. The system allows SMEs to benefit from industry-wide failure patterns without sharing sensitive asset data. All data is processed under UK GDPR, stored in Microsoft Azure UK South data centres, and aligned with ISO/IEC 27001 and OT security standards.

Does GridOps work in remote sites without internet connectivity?

+
Yes. GridOps is built with an "Offline-First" Edge-AI architecture. Critical telemetry is processed locally on NVIDIA Jetson Orin modules, ensuring 24/7 monitoring even in remote wind farms and rural substations with limited or no connectivity. The system sustains 95% of its predictive functionality during complete network dropouts, and synchronizes data once reconnected.

How long does implementation take?

+
Full GridOps predictive operations deployment is typically operational within 4–6 weeks. Weeks 1–2 cover SCADA bridge connection and legacy protocol integration. Weeks 2–3 involve asset criticality baseline establishment and drift detection calibration. Weeks 3–5 see live failure precursor detection and alert validation. Week 6 onwards activates full NIS 2018 compliance reporting and federated learning contribution.

Why can competitors not easily replicate GridOps Intelligence?

+
GridOps' competitive moat is built on five defensible pillars: (1) the proprietary Zero-Overhaul SCADA bridge requiring deep legacy protocol domain expertise; (2) the federated failure precursor repository that grows stronger with every deployment; (3) native UK NIS 2018 and Ofgem compliance alignment that global giants ignore; (4) the hardware-software synergy of lightweight Edge-AI that makes enterprise rip-and-replace obsolete; and (5) UK-specific asset training datasets unavailable to generic IIoT platforms.
Still Have Questions?

Talk to Muhammad Shujaat Shabbir Directly

The GridOps Intelligence team is available for pilot discussions, technical briefings, and live demonstrations of the predictive operations platform for UK infrastructure SMEs and utility service providers.

Contact & Pilot Programme

Request a Pilot Programme or Infrastructure Demonstration

GridOps Intelligence is actively onboarding UK energy operators, renewable infrastructure providers, industrial facilities, and utility contractors seeking predictive operational oversight. Connect directly with our team to discuss pilot deployments, infrastructure reliability audits, and Edge-AI monitoring integrations.

Email gridopsuk@outlook.com
Location United Kingdom · Energy, Water & Industrial Infrastructure Sectors
Pilot Programme

Join The Phase-1 UK Reliability Cohort

GridOps Intelligence is recruiting 10–15 UK utility operators, renewable energy facilities, and industrial infrastructure providers for a 12-week predictive operations pilot focused on drift detection, outage prevention, and infrastructure resilience validation.

12-Week Pilot Edge-AI Reliability Monitoring Free Infrastructure Audit

Request a Demonstration