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HERMON

AID ยท AI, Data & Automation

Put AI to work where it earns its place.

We start with the process, not the model. We find where AI, automation and better data can improve how work gets done, then build, integrate and govern the solution.

Discuss your requirementsCore capabilities

Business problems we solve

What gets in the way.

  • Pilots that never reach production

    AI experiments look good in demos but stall on data access, security review or integration.

  • Data scattered across systems

    Reporting takes days because data sits in disconnected systems with no shared definitions.

  • Knowledge locked in documents

    Staff spend hours searching policies, manuals and past tickets for answers.

  • Repetitive manual work

    High-volume tasks such as data entry, document handling and approvals still depend on people.

Core capabilities

What AI, Data & Automation covers.

  • AI strategy and use-case discovery

    Workshops and assessments that rank use cases by value, feasibility, data readiness and risk.

  • Generative AI solutions

    Applications built on large language models, with retrieval, guardrails and evaluation, in Arabic and English where the chosen models support it.

  • Enterprise AI agents

    Agents that act within defined permissions across your systems, with logging and human approval steps.

  • Workflow automation

    Automation that combines integrations, business rules and AI steps, and sends exceptions to people.

  • Data engineering

    Pipelines, data models and quality checks that move data reliably from source systems to where it is used.

  • Analytics and business intelligence

    Governed data models, dashboards and self-service reporting built on consistent definitions.

  • Knowledge assistants and AI integrations

    Assistants grounded in your own documents, and AI features embedded in the applications people already use.

Delivery workflow

How delivery runs, step by step.

  1. Step 1

    Discover

    Map candidate use cases, data sources, owners, constraints and risks.

  2. Step 2

    Prove

    Build a time-boxed prototype and evaluate it against criteria agreed in advance.

  3. Step 3

    Build

    Engineer for production: security, integration, access control and monitoring.

  4. Step 4

    Govern

    Evaluate outputs, monitor drift and cost, and keep an audit trail of agent actions.

  5. Step 5

    Scale

    Extend proven patterns to new teams and processes.

Typical use cases

Typical starting points.

  • Policy and procedure assistant

    A knowledge assistant that answers staff questions from approved internal documents and cites its sources.

  • Document processing

    Extract and validate data from invoices, contracts and forms, with people reviewing low-confidence results.

  • Operations analytics

    Bring operational data into one governed model with dashboards for managers.

  • Service-desk automation

    Classify, route and draft responses for incoming tickets, with agents approving the final reply.

Engagement options

Ways to engage for this service.

What you can expect

  • A ranked list of AI use cases, each with a business owner.
  • Prototypes judged against criteria agreed before work starts.
  • AI that runs within your security and data policies.
  • Reporting built on one set of definitions.

Related services

AI, Data & Automation

Tell us what you need from this service.

Describe your environment and objectives. We will reply by email to arrange a conversation with the relevant specialist.

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