The AI opportunity map

Industries

Seven industries. 273 use cases. One platform, on infrastructure you own, inside your own jurisdiction.

7industries
273AI use cases
77Tier-1 must-haves
16reusable solutions

This is an opportunity map, not a record of work delivered. It sets out 273 AI use cases across seven industries, each with the problem it addresses, the technique behind it and how far the market has taken it. Of those, 77 are Tier-1: the ones an operator in that industry is expected to have in production.

Read across the seven and the same components keep reappearing. Retrieval over an internal corpus, forecasting, optimisation, anomaly detection, document processing, agents — a refinery, a transit authority and a regulated lender would each assemble these from the same parts. That is the point of one platform behind all seven: the industry difference sits in the data, the constraints and the domain models, not in the infrastructure underneath. Neor builds and operates that platform on hardware you own, inside your jurisdiction, on open components your engineers can review, and then hands it to them.

Seven industries, one platform

How to read it

Three tiers

Tier 1 is must-have: mature in the market, widely adopted across the industry, and the shortest route into production. Tier 2 is expansion the market has already validated; Tier 3 is emerging, with a longer time to value.

Tier 1

Must-have

Proven, prevalent, fast ROI

Tier 2

High-value expansion

Validated, strong ROI, moderate effort and change management

Tier 3

Advanced / emerging

Commercially emerging, longer payback, strategic optionality

Build once, deploy everywhere

The solutions that repeat

Sixteen solutions recur across the seven industries, with only the data and the constraints changing. Design a knowledge assistant for a refinery and the same components would serve a claims department; the reuse score records how far each one travels.

  • H04Enterprise Knowledge Assistant (RAG / GraphRAG)
    7 / 7
  • H07Demand & Time-Series Forecasting
    7 / 7
  • H08Optimization (routing, scheduling, pricing, planning)
    7 / 7
  • H13Agentic AI Process Automation
    7 / 7
  • H14Speech & Voice AI (contact center, field, authentication)
    7 / 7
  • H03Intelligent Document Processing (IDP + OCR)
    6.5 / 7
  • H05Customer Service Conversational AI + Agent Assist
    6 / 7
  • H11Recommendation / Next Best Action
    6 / 7
  • H06Fraud & Anomaly Detection (incl. Graph ML)
    5.5 / 7
  • H10Digital Twins
    5.5 / 7
  • H15Geospatial & Earth-Observation Analytics
    5.5 / 7
  • H01Predictive Maintenance & Asset Health
    5 / 7
  • H12Generative AI Content Production
    5 / 7
  • H16Video Analytics for Operations (flow, occupancy, activity)
    4.5 / 7
  • H02Computer Vision for Safety (PPE, behavior, intrusion)
    4 / 7
  • H09Drone & Robotic Autonomous Inspection
    4 / 7

Reuse is scored across the seven industries: a strong fit counts one, a fit that needs adaptation counts a half.

Underneath

The capabilities they are built from

The 273 use cases draw on 22 AI capabilities, grouped in five layers: generative and conversational, knowledge and language, predictive and analytical, perception and physical, and optimisation, simulation and automation. A platform that carries all five carries the whole map.

Generative & Conversational AI

  • Generative AI (text/image/video/audio)4/7
  • Conversational AI7/7
  • AI Agents / Agentic AI7/7
  • Speech Recognition / Voice AI6/7

Knowledge & Language

  • LLMs + RAG / GraphRAG + Knowledge Graphs7/7
  • NLP & Text Analytics7/7
  • OCR + Intelligent Document Processing6/7

Predictive & Analytical AI

  • Predictive ML & Analytics7/7
  • Time-Series Forecasting7/7
  • Anomaly Detection7/7
  • Graph Analytics / Graph ML5/7
  • Recommendation Systems6/7
  • Predictive Maintenance4/7
  • Decision Intelligence6/7

Perception & Physical AI

  • Computer Vision & Video Analytics7/7
  • Image/Video + Drones/UAV & Robotics4/7
  • Robotics & Autonomous Systems4/7
  • Sensor / IoT Analytics5/7
  • Geospatial / Spatial Intelligence5/7

Optimization, Simulation & Automation

  • Optimization (OR + ML)7/7
  • Digital Twins5/7
  • Process Automation (RPA + AI)5/7

The exception

Where domain depth is required

Some things do not generalise. Seismic interpretation, closed-loop process control, train control, marketplace matching, credit decisioning and catastrophe modelling each need domain models built against the physics, regulation and data of a single industry — and still run on the same platform.

  • Oil & GasSeismic interpretation and drilling optimization
  • PetrochemicalsClosed-loop process control and soft sensors
  • TransportationTrain control / C-DAS and ATC support
  • Ride-HailingMarketplace matching and surge pricing
  • Financial ServicesCredit decisioning, AML and trade surveillance
  • InsuranceCatastrophe modeling, actuarial pricing and telematics UBI
  • Marketing & ContentMedia mix modeling and DCO

Tell us which industry you are in and which use case matters most, and we will come back with an architecture and a plan.

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Ali Salmaji

Ali Salmaji

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