ThirdEye Data · AI Strategy Brief for Duration Capital Partners
AI for
Transportation
Mapping high-value AI use cases across freight, logistics, fleet management, and passenger transport — and grounding each one in ThirdEye Data's proven delivery track record.
01 — Industry Overview
01
Transportation & Logistics — The AI Opportunity
Five sub-sectors, one set of transformative capabilities
Why transportation is primed for AI
Transportation generates more sensor, telemetry, and operational data than almost any other industry — yet most of it goes unanalysed. AI turns that raw signal into margin, safety, and service quality.
1
Freight & Logistics
Route optimisation, load planning, warehouse automation, last-mile delivery prediction, and carrier performance analytics.
2
Fleet Management
Predictive maintenance, telematics analytics, fuel optimisation, and driver behaviour scoring across large mixed fleets.
3
Public Transit & Passenger Rail
Demand forecasting, schedule optimisation, real-time passenger information, and anomaly detection on rolling stock.
4
Port & Airport Operations
Yard management AI, baggage handling anomaly detection, gate utilisation optimisation, and customs document processing.
5
Energy & Infrastructure
EV charging load forecasting, traffic signal AI, road condition monitoring from image / sensor data.
Business pressure driving AI adoption
Fuel / energy cost pressure
Driver / labour shortage
Regulatory compliance burden
Customer ETA expectations
Asset downtime cost
Data volume / complexity
ThirdEye Data's edge: We have delivered production-grade AI across energy utilities, manufacturing, telecom, and ad-tech — all of which share core AI patterns with transportation: sensor data, predictive models, real-time pipelines, and operational dashboards.
02 — AI Use Cases Mapped to ThirdEye Data's Capabilities
02
Use Case Landscape — 8 Cluster Overview
From predictive maintenance to Agentic AI dispatch automation
Full use case matrix
| # | Use Case Cluster | AI Technique | ThirdEye Data's Capability | Business Outcome |
|---|---|---|---|---|
| 01 | Predictive Maintenance — vehicle, rail, equipment | ML regression, time-series, RL | Nimble/HPE, Stryker, HAL projects | ↓ 30–40% unplanned downtime |
| 02 | Route & Demand Optimisation | ML forecasting, reinforcement learning | Campaign Conversion, Inventory Opt. | ↓ fuel cost, ↑ on-time delivery |
| 03 | Computer Vision — Inspection & Safety | Deep learning, object detection | SCE Image Quality, Anomaly in Poles | ↓ incident rate, ↑ compliance |
| 04 | NLP — Document & Compliance Automation | NLP, NER, RAG, GenAI | ECHR Semantic Search, Lessons Learned | ↓ manual processing, ↑ audit speed |
| 05 | Operational Intelligence & Dashboards | MLOps, real-time analytics, BI | Xperi MLOps, Nokia Network Diag. | Real-time KPI visibility |
| 06 | Anomaly Detection — Network / Infrastructure | LSTM, fbProphet, Spark Streaming | Centerity AI Ops, Tata Comms | Early warning, ↓ SLA breach |
| 07 | GenAI Assistants — Copilots & RAG Chatbots | LLM, RAG, Agentic AI | Microsoft Copilots, Prochain Help Center | ↑ dispatcher & ops team productivity |
| 08 | Multi-Agent Workflow Automation | Multi-agent orchestration | Kobie Customer Loyalty Agents | End-to-end process automation |
03 — Fleet & Predictive Maintenance
03
Predictive Maintenance & Fleet Health AI
Reduce unplanned downtime by predicting failures before they happen
Transportation application
Every truck, locomotive, aircraft, or vessel is a machine with degrading components. AI built on telemetry and sensor streams can predict failure windows — enabling scheduled maintenance that avoids costly breakdowns.
Engine & Drivetrain Failure Prediction
ML regression models trained on OBD-II / CAN bus data predict which vehicles are likely to fail within a defined window, enabling proactive service scheduling.
Battery State-of-Health (EV Fleets)
Predict remaining battery life from early charge/discharge cycle data — directly analogous to ThirdEye Data's Stryker battery project, just applied to EV commercial fleets.
Brake & Tyre Wear Models
Active Learning approach — similar to the Stryker engagement — decides which vehicles need immediate inspection versus which can wait, minimising workshop throughput waste.
Automobile Component Failure
ThirdEye Data's active project for Hindustan Aeronautics Limited (HAL) detects rogue components, predicts time-to-failure, and estimates maximum repair cycles — directly applicable to aviation MRO.
ThirdEye Data capabilities mapped
ML Regression
Time-Series Forecasting
Reinforcement Learning
Active Learning
Feature Engineering
Real-Time Sensor Ingestion
Spark Streaming
Apache Kafka
Expected business impact
Unplanned downtime
Maintenance cost
Fleet utilisation
Sensor data ingestion speed
Proof point: For Nimble Storage (HPE), ThirdEye Data extended a predictive analytics platform to handle 10× more data points, increased ingestion rate by 50%, and improved query response times by 900%. The same engineering patterns apply directly to fleet sensor pipelines.
04 — Route & Demand Optimisation
04
Route Optimisation, Demand Forecasting & Inventory AI
Smarter loads, smarter lanes, fewer empty miles
Use cases
Freight carriers and logistics operators live and die by utilisation rates. AI that predicts demand, optimises loads, and recommends routes can cut fuel spend and empty miles simultaneously.
Freight Demand Forecasting
Predict volume by lane, by customer, and by season. Feed forecasts into capacity planning to eliminate both under- and over-provisioning.
Dynamic Route Optimisation
Real-time and batch route calculation incorporating traffic, weather, fuel prices, driver HOS rules, and load constraints — updated as conditions change.
Inventory & Parts Optimisation
ML models that balance spare-parts inventory across depots so the right component is available at the right location — not sitting idle 800 miles away.
Sales & Capacity Forecasting
ThirdEye Data built a Sales Forecasting system for Tex-Isle (oil & gas distributor) on top of a 200-source data lake — the same architecture serves freight carriers' lane pricing and capacity models.
ThirdEye Data capabilities mapped
ML Forecasting
Data Lake Design
200+ Source Ingestion
Azure ML
PowerBI Dashboards
Batch + Real-time Pipelines
Reference: Tex-Isle Inventory Optimisation
Client
Tex-Isle — energy tubulars distributor, Houston TX
What we built
Data lake ingesting 200+ sources; batch, real-time, and incremental pipelines; ML inventory optimisation models; predictive maintenance module; sales forecasting system
Stack
Azure Cloud, Azure ML, Azure Data Factory, Azure Blobs, SQL Data Warehouse, PowerBI
Transport parallel
Freight depot spare-parts inventory, carrier capacity planning, lane demand forecasting
05 — Safety, Vision & Compliance AI
05
Computer Vision — Infrastructure Inspection & Safety Monitoring
AI-powered eyes on roads, rails, poles, and cargo
Use cases
Transportation infrastructure — roads, bridges, rail, overhead power lines, port cranes — degrades invisibly until it fails. Computer vision applied to drone and fixed-camera imagery catches defects before they become disasters.
Road & Rail Infrastructure Inspection
Drone imagery run through object detection models identifies surface cracks, track deformations, overhead line anomalies, and signage damage — without requiring track or road closures.
Cargo & Load Image Quality Validation
Before shipping documentation is generated, an AI quality gate validates that load photos are clear, correctly angled, and unoccluded — the same pipeline ThirdEye Data built for Southern California Edison's electric pole inspection.
Anomaly Detection on Electric / Rail Infrastructure
Detect defective components, predict deterioration probability, and route anomalous assets to maintenance queues — directly adapted from ThirdEye Data's Microsoft anomaly detection work on electric poles.
Automobile & Freight Quality Check (Sound + Vision)
ThirdEye Data's CenturyPly project detects internal defects by analysing audio signatures — the same approach applies to rail track tap-testing and structural integrity checks at freight depots.
ThirdEye Data capabilities mapped
Computer Vision (TensorFlow)
Object Detection (YOLO)
Structure Detection
Occlusion / Blur / Angle AI
Drone Image Pipelines
Anomaly Detection
Audio / Spectrogram ML
Master Image Pipeline
Two anchoring reference projects
SCE Image Quality Detection (Southern California Edison): End-to-end platform ingesting third-party images of electric poles, detecting structure, tags, occlusion, blur, and angle — then routing quality-cleared images to downstream anomaly detection. Stack: TensorFlow, Google Vertex AI, Azure Data Factory, CosmosDB.
Microsoft Anomaly Detection in Electric Poles: Drone-captured images ingested to Azure Blob; AI identifies poles, detects anomalies in sub-parts, predicts deterioration probability. Used by Microsoft's customers and field sales worldwide.
06 — Operational Intelligence & Network Analytics
06
Real-Time Ops Intelligence, MLOps & Network Diagnostics
Monitor thousands of signals simultaneously — alert before SLAs are breached
Use cases
Modern transportation networks — from telecoms-connected fleets to train control systems — produce thousands of metrics per second. AI that watches all of them simultaneously can catch early warning signals that human operators would never see in time.
Fleet Telematics Anomaly Detection
ThirdEye Data's Centerity AI Ops platform detects anomalies on 10,000+ metrics simultaneously. Applied to fleet telematics: engine temperature spikes, abnormal fuel consumption, tyre pressure drift — all flagged in real-time before they become breakdowns.
Network Diagnostics for Connected Transport
ThirdEye Data proved for Nokia that ML-based network diagnostics can save millions in manual log analysis. The same approach applies to V2X (vehicle-to-everything) network monitoring for freight corridors and smart highways.
MLOps Platform for Transportation AI
As transport operators accumulate dozens of AI models (maintenance, routing, vision), they need a production MLOps platform. ThirdEye Data built exactly this for Xperi — Data LakeHouse, ML Flow, model versioning, and deployment pipelines.
ThirdEye Data capabilities mapped
Apache Spark Streaming
Kafka Real-Time Pipelines
TensorFlow LSTM
fbProphet Time-Series
MLOps (MLFlow + MinIO)
ElasticSearch
Grafana / Prometheus
GraphDB
Key references
10k+
Metrics
Anomaly detection capacity in Centerity AI Ops platform
900%
Query Speedup
Analytical query improvement for Nimble Storage (HPE)
$M
Savings Proven
Nokia: ML diagnostics vs manual log analysis cost
07 — GenAI & Agentic AI for Transportation
07
Conversational AI, Document Automation & Multi-Agent Workflows
LLM-powered copilots for dispatchers, compliance teams, and operations centres
High-value GenAI use cases in transportation
Transportation generates enormous volumes of unstructured content — inspection reports, customs documentation, driver logs, incident reports, regulatory filings. GenAI converts this paper trail into searchable, actionable intelligence.
Dispatch & Operations Copilot
A RAG-based copilot gives dispatchers instant answers about vehicle locations, ETA predictions, driver availability, and maintenance status — all from natural language queries. Parallel to ThirdEye Data's AIDW Assistant and Billings Assistant for Microsoft.
Compliance & Regulatory Document Automation
GenAI extracts key data from freight bills, customs declarations, CMRs, and inspection certificates — and converts them between formats automatically. ThirdEye Data's Optira product (Azure OpenAI + complex prompt engineering) does exactly this for document format conversion.
Incident Reporting & Root Cause Summarisation
When an incident occurs, AI assembles all related telemetry, driver reports, and maintenance history into a structured incident brief — ready for safety teams and regulators. Mirrors ThirdEye Data's Lessons Learned project for the Australian government.
Driver / Crew HR & Scheduling Copilot
An onboarding and scheduling copilot helps new drivers navigate compliance requirements, HOS rules, and training records. ThirdEye Data built this pattern for Microsoft's Power Platform as the Onboarding Buddy Chatbot.
Agentic AI — Freight Booking & Carrier Management
Multi-agent systems that handle quote requests, carrier selection, booking confirmation, invoice validation, and exception management end-to-end — adapted from ThirdEye Data's 12-agent Kobie Customer Loyalty platform.
ThirdEye Data GenAI / Agentic capabilities
Azure OpenAI (GPT-4)
RAG Frameworks
Copilot Studio
Multi-Agent Orchestration
LangChain
Snowflake Cortex
Azure AI Search
Databricks Vector Search
Prompt Engineering
NER / NLP Extraction
Agentic AI project: Kobie (direct parallel)
Platform
Snowflake Cortex AI + LangChain + FastAPI + Angular + Redis
Agents built
12 agents including Audience Builder, Member Chatbot, Fraud Management, Vendor Management, and Account Management — all orchestrated in production
Transport adaptation
Replace loyalty use cases with: Carrier Selection Agent, Booking Agent, Invoice Validation Agent, Exception Management Agent, Compliance Agent
08 — Project References Relevant to Transportation
08
Anchoring Reference Projects from ThirdEye Data's Portfolio
Every reference below maps to one or more transportation AI patterns
Predictive maintenance & sensor analytics
Manufacturing · Nimble Storage / HPE
Predictive Maintenance Platform
Extended Nimble's cloud-based predictive analytics to handle 10× more data points. Achieved 50% faster ingestion, near real-time analytics, and 900% improvement in query response times. Stack: Apache Spark, Kafka, Ignite, Hadoop, HP Vertica, Python.
Fleet sensor parallel
Real-time telematics
Healthcare · Stryker
Battery Remaining Life Predictions
ML regression model predicts remaining battery life from early cycle data. Used Active Learning and Reinforcement Learning to guide the testing process. Directly applicable to EV fleet state-of-health monitoring. Stack: TensorFlow, SciKit Learn, Python, MySQL.
EV fleet parallel
Active Learning
Manufacturing · HAL (Ongoing)
Predictive Maintenance & Component Failure Analysis
For Hindustan Aeronautics Limited: detects rogue components, predicts hours-to-failure, estimates maximum repair cycles. Document ingestion with entity extraction. Direct aviation MRO application.
Aviation MRO
Component failure AI
IT · Microsoft (Strategic Partnership)
Predictive Maintenance Solution with ARM
Built in collaboration with Microsoft under a strategic non-exclusive partnership. Uses ARM templates for automated infrastructure provisioning, enabling rapid deployment and full enterprise customization across any customer environment. Optimized for Azure but cloud-agnostic — can be adapted for other cloud providers or on-premises deployments. Directly applicable to transport fleet asset monitoring at enterprise scale.
Enterprise fleet deployment
Azure ARM templates
Cloud · Amazon AWS (Marketplace)
Predictive Analytics Solution — AWS Marketplace
Developed Amazon AWS's first Predictive Maintenance solution on the AWS Marketplace. Single-click deployment — up and running in minutes. Integrates native and third-party AWS services, applies ML models for predictive analysis, surfaces insights via analytical and predictive dashboards, and delivers real-time failure notifications via a mobile app. Applicable to connected transport asset monitoring at scale.
One-click fleet deployment
Mobile alerting
Manufacturing process intelligence & quality systems
Manufacturing · Glas Trosch (Switzerland)
Predictive Metrology for Control Systems
Developed an Open-Loop-System for a 100+ year-old European glass manufacturer. Receives live sensor data, computes predicted end-of-line metrology values and corrective parameter suggestions in real-time while panes are being coated. Results displayed via a shop-floor GUI. Improves product quality and reduces waste — a direct analogue to real-time quality control in transport component manufacturing.
Real-time process control
Predictive quality AI
Manufacturing · Tex-Isle (Houston, TX)
Inventory Optimization System
Built a data lake ingesting 200+ heterogeneous sources for a leading oil-rig pipe manufacturer transforming into a data-first company. Delivered ML-driven inventory optimization, a Predictive Maintenance system for the manufacturing division, and a Sales Forecasting system for the commercial team. Data pipelines handle batch, real-time, and incremental ingestion — applicable to spare-parts and MRO inventory management in transport fleets.
Inventory & MRO optimization
Sales forecasting ML
Manufacturing · Hydrow (Boston, MA)
Data Platform Development
Built the first-ever data platform for a VC-backed connected-hardware startup, enabling analytics across sales, marketing, and business stakeholders. Conducted an enterprise Data Readiness Audit presented to board-level VCs, and evaluated AI/ML use cases for predictive, forecasting, and recommending capabilities — directly transferable to connected-vehicle telematics and fleet analytics platform builds.
Connected device analytics
Data readiness audit
Healthcare-Manufacturing · Resolve Digital Health (Toronto)
Pill Detection from Images (AI Vision Pipeline)
End-to-end AI pipeline using Deep Learning image recognition to ensure correct medication delivery. Built a HIPAA-compliant data lake ingesting real-time and batch data, applied Sentiment Analysis on patient-experience signals, and surfaced insights via D3.js dashboards. Computer vision and real-time inference pipeline architecture mirrors automated visual inspection systems used in automotive and aerospace parts manufacturing.
Computer vision inspection
Real-time AI inference
Computer vision & infrastructure inspection
Energy · Southern California Edison
Image Quality Detection Platform
End-to-end platform ingesting drone images of electric poles; AI models for structure detection, tag deciphering, occlusion, blurriness, and angle detection. Master pipeline branches to appropriate data pipeline per object type. Stack: TensorFlow, Google Vertex AI, Azure Data Factory, CosmosDB.
Infrastructure inspection
Drone image pipelines
IT · Microsoft
Anomaly Detection in Electric Poles
Drone images ingested to Azure Blob; AI identifies poles, detects anomalies and sub-part defects, predicts deterioration probability. Used by Microsoft customers and field sales worldwide as a repeatable solution accelerator.
Road / rail inspection
Predictive deterioration
Manufacturing · CenturyPly (Ongoing)
Automobile & Freight Quality Check System (Audio ML)
Deep learning on audio recordings of hammer-tap tests detects internal structural defects. Noise removal and spectrogram analysis used to classify good/bad quality. Analogous to tap-test based rail track and bridge inspection.
Structural inspection
Audio-based defect AI
Operational intelligence & real-time analytics
IT · Centerity
AI Ops Anomaly Detection Platform
Open-source anomaly detection on 10,000+ metrics simultaneously using TensorFlow LSTM and fbProphet on Spark clusters. Auto-AI, alerting, root-cause drill-down. Stack: Spark, Kafka, InfluxDB, Kapacitor, Docker, Kubernetes, AWS.
Fleet telematics
Real-time alerting
Telco · Nokia
Real Time Network Diagnostics
ML predictive model for network infrastructure problems. Proved ML can save millions vs manual log analysis. Stack: Apache Hadoop, Hive, Pig, HBase, Java — directly applicable to V2X and connected-fleet network monitoring.
Connected transport
V2X monitoring
IT · Xperi
MLOps Engineering Platform
Full MLOps platform: Data LakeHouse design, data pipelines (ingestion, cleansing, transformation), and ML Flow for model development, training, deployment, and versioning. Stack: Apache Kafka, MLFlow, MinIO, GraphDB, ElasticSearch, Enterprise Java & Python.
Transport AI platform
Model governance
Route mapping, optimization & ride-sharing
Finance · Inter-American Development Bank (IDB)
Healthcare Network Optimizations
Built an AI-powered geospatial network optimization system for IDB — the largest development finance institution for Latin America — to identify optimal hospital placement and catchment-area coverage across the region. Visualized average distances, population counts, and optimal facility locations on an interactive map. Stack: Django, Apache Spark, SparkML, Apache Livy, MongoDB, Python, IBM Watson, IBM Alchemy API.
Geospatial network optimization
Catchment area mapping
Retail · Delivery Solutions (Texas)
ML-based Delivery ETA Predictions
Built an ML system predicting estimated time of arrival (ETA) with 90%+ accuracy for same-day last-mile delivery across any pick-up / drop-off pair. Results exposed via API for downstream system integration. Stack: Amazon SageMaker, Amazon S3, Amazon API Gateway, Python, Boto3, MongoDB. Pipeline: Data profiling → EDA → pre-processing → model building → evaluation → prediction.
Last-mile ETA prediction
90%+ accuracy ML
Consulting · IND Consulting (Washington D.C.)
Pharmacy Route Optimization System
Developed a TSP-style route optimization engine for a pharmacy delivering medications to nursing homes. The system determines the two best routes (by total miles and time) across N addresses, always returning to the depot. Stack: Python, Google Maps API, Django, MySQL, Azure Cloud. Directly applicable to multi-stop fleet dispatch and last-mile delivery optimization.
Multi-stop route optimization
Google Maps API
Transport · Obhai (Bangladesh)
AI Optimizations for Ride-Sharing Platform
Full AI stack for a national ride-sharing platform (cars and CNG auto-rickshaws): grid-based demand forecasting, ride-density heat maps, fuel-efficient driver routing, AI-based fare pricing, dynamic fare adjustment, fraud detection, behavioral driver-passenger matching, push-notification engagement, and loyalty incentive targeting. Stack: Amazon EC2, Amazon S3, Python, Google Maps API, Mapbox. Forecasting jobs run daily; models retrained weekly.
Demand forecasting
Dynamic pricing AI
GenAI, Agentic AI & document automation
IT · Kobie
AI Agents for Customer Loyalty (12 Agents)
Production-grade multi-agent system with 12 agents covering audience building, member chatbot, fraud management, vendor management, coupon management, and more. Stack: Snowflake Cortex AI, LangChain, Angular, Redis, FastAPI.
Freight booking agents
Dispatch automation
IT · Microsoft (Power Platform)
Onboarding Buddy & Supplier Copilot
Copilot Studio chatbots for HR onboarding and supplier invoice management. Role-based data security, contextual Dataverse queries, and end-to-end process guidance. Directly applicable to driver onboarding, HOS compliance, and carrier invoice workflows.
Driver HR copilot
Carrier invoice AI
IT Services · VP Internationals
GenAI Document Format Conversion (Optira)
ThirdEye Data's own product Optira uses Azure OpenAI and complex prompt engineering to convert hundreds of documents between formats automatically. For transportation: CMRs, bills of lading, customs declarations, inspection certificates.
Customs docs automation
Freight paperwork AI
Government · Myriad / Microsoft
Lessons Learned — NLP Summarisation
Deployed NLP to extract "Lessons Learned" from government reports using 6 extractive summarisation algorithms. User feedback loop selects the best-performing algorithm. Applied to transportation: incident reports, near-miss summaries, safety audits.
Incident reporting AI
Safety audit summaries
IT · Microsoft
AIDW Assistant & IP Search (RAG)
AI-powered knowledge repository chatbots using Azure AI Search, OpenAI embeddings, and semantic search. Auto-tagging, bulk search, near real-time Dataverse indexing. Applied to transport: technical manuals, route databases, regulatory knowledge bases.
Ops knowledge base
Regulatory RAG
Telecom · Tata Communications (Ongoing)
Optimal Frequency Selection — ML/DL
ML/DL models predict interference-free frequency bands in unlicensed spectrum; automates frequency change process; integrates with Network Management System. Applied to: private 5G in ports, airports, and rail yards.
Port / airport 5G
Rail yard connectivity
09 — Demos of AI Solutions
09
Pre-built AI Solutions — Live on AI Demo Central
Try working demos instantly · No setup required
🤖
ThirdEye Data's AI Demo Central — Manufacturing & Transport AI, Ready to Explore
All six demos below are live, production-quality prototypes running on democentral.ai. Access them instantly with the shared credentials below — no installation, no configuration.
Demo Access Credentials
Explore all demos on AI Demo Central
More solutions available · New demos added regularly
10 — AI Readiness Program
09
Enterprise Data Readiness & Governance
Foundational audit, architecture, and governance program — the prerequisite to any AI initiative
Why data readiness is the AI on-ramp for transportation
Strategic
Predictive maintenance, route optimization, and demand forecasting all depend on clean, governed, centralized data. ThirdEye Data's readiness program ensures data is ready for analytical and AI consumption before any model is built.
Immediate
Improving equipment reliability, reducing maintenance costs, and enhancing operational efficiency begin the moment data pipelines and governance policies are in place — before a single ML model is deployed.
Risk
Proactively addressing data gaps and security posture eliminates the risk of costly model failures, compliance breaches, and production delays driven by poor data quality downstream.
ThirdEye Data's two-phase approach
Phase 1 · Explore Existing Landscape
Discovery & Current-State Analysis
Understand business goals, use cases, and data flow at both functional and system level. Map every data source used by each business unit. Assess current data load and usage strategies across the enterprise.
Phase 2 · Develop a Firm Understanding
Architecture, Governance & Cost Plan
Define scope, use cases, system architecture, and process flow. Identify Data Visualization KPIs. Establish Data Governance and Security infrastructure. Size the required team and estimate full implementation costs.
Key deliverables
Roadmap
Phased project plan with deliverables by timeline, infrastructure cost monitoring plan, and maintenance & support programme.
Architecture
Full-system data architecture recommendation: evaluation of existing systems/schema, gap analysis vs. future state, technical data stack selection, and source data quality assessment.
Governance
Data steward/CDO structure, data classification, master data management (master customer and product lists), data authoring policies, data quality & cleansing rules, and process metadata standards.
Security
Four-layer enterprise security stack: User Access Control (AAD / RBAC), Data Protection (encryption at rest and in motion), Network Security (virtual network / VPN), and Monitoring & Auditing.
Analytics
Sample dashboards, KPI identification and evaluation, UAT management, and a modern data platform connecting raw/staging ODS → data warehouse → data science platform → BI dashboards and REST APIs.
Reference customers — Data Readiness & Governance engagements
Energy · Southern California Edison
Enterprise Data Readiness & Platform
Conducted a full data readiness audit and enterprise data platform build for the major Southern California utility. Outputs fed directly into AI-powered electric-pole inspection and asset-health prediction pipelines. A direct blueprint for transport infrastructure data programmes.
Infrastructure data platform
Asset health analytics
Semiconductor · Marvell Technology
Data Governance & Platform Architecture
Delivered data governance framework, master data management strategy, and data platform architecture recommendation for the global semiconductor leader. Applicable to transport companies managing complex multi-system ERP and IoT data landscapes.
Master data management
Data governance framework
Services · Service Corporation International
Centralized Data Lake & Analytics Platform
Built a centralized data lake ingesting multiple enterprise sources for one of North America's largest service corporations. Established data pipelines (batch, real-time, incremental), data quality rules, and role-based analytical dashboards for all business stakeholders.
Multi-source data lake
Role-based dashboards
Manufacturing · Hydrow (Boston, MA)
Data Readiness Audit & Platform Strategy
Conducted an enterprise Data Readiness Audit presented to board-level VCs for this VC-backed connected-hardware startup. Delivered a comprehensive report covering data landscape, governance gaps, and AI/ML use-case roadmap — directly transferable to connected-fleet telematics readiness assessments.
Board-level data audit
AI/ML use-case roadmap
Education · Brave Thinking Institute
Data Platform Build & Governance Programme
Designed and implemented a data platform with governance policies, data classification, and analytical dashboards for this growing education organisation. Demonstrates ThirdEye Data's ability to stand up governed platforms from scratch in data-immature environments — typical of many transport operators.
Greenfield data platform
Data classification
Manufacturing · Tex-Isle (Houston, TX)
Data Lake, Governance & AI Readiness
Set up a data lake ingesting 200+ heterogeneous sources with batch, real-time, and incremental pipelines as part of Tex-Isle's data-first transformation. Delivered data governance framework enabling downstream ML models for inventory optimization, predictive maintenance, and sales forecasting.
200+ source data lake
Governance-to-ML pipeline
11 — Next Steps
11
From Conversation to Delivery
A clear, low-risk path to AI value in transportation
From conversation to delivery — a clear path forward
ThirdEye Data works in focused, low-risk engagements that generate measurable value quickly. The steps below move from alignment through proof-of-value to full production — at whatever pace suits your organization.