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    IT consulting for data, AI & SAP

    Data and AI that work in production.

    With a focus on Databricks and SAP: we connect your SAP world with a modern data platform and take AI agents, Copilot and automation into operations on top — on Azure, as code, with governance.

    Certified in

    • Databricks
    • SAP
    • Microsoft Azure

    The situation

    The pilot works. Now the platform has to.

    Many companies already have their first AI prototypes, a handful of pipelines and some cloud resources. What’s missing is the foundation for running them in production. That’s exactly where we come in.

    • Sprawl instead of a platform

      Environments, permissions and costs without shared rules.

      Our answer

      One shared platform with clear roles, governance and cost control — as code, e.g. with Databricks Unity Catalog.

    • SAP data as a black box

      Master and transactional data arrive late, incomplete or duplicated.

      Our answer

      Clean master data and reliable SAP integration all the way into your data platform.

    • GenAI with no path to production

      Prototypes, but no serving, no monitoring, no sign-off.

      Our answer

      An agent platform with tracing, evaluation, monitoring and approvals — all the way into operations.

    Live example

    How an AI agent works in your processes.

    Pick a case and start the flow. The agent reads, checks and prepares — people make the decisions.

    Agent log · Example with fictitious dataRead the invoice, match it against SAP, route deviations for approval.
    1. Invoice arrivesEmailPDF invoice from Sample Ltd. received
    2. Read the documentDocument IntelligenceInvoice no., date, 12 line items and total extracted
    3. Match the purchase orderSAP S/4HANAPurchase order found — line 7: quantity 120 instead of 100
    4. Assess the deviationAI agentDeviation above tolerance → approval required
    5. ApprovalHuman in the loopProcurement confirms the over-delivery in Teams
    6. PostSAP S/4HANAInvoice posted, document created, case logged

    Agent / systemHuman in the loop

    OutcomeThe result appears after the last step …

    Why A2H-Consulting

    Why companies work with us.

    More about us →
    • Data, AI and SAP in one team

      Master data, integration, Databricks and AI from one team — no hand-off losses.

    • Enterprise experience, delivered lean

      Experience from projects at companies with 10,000+ employees — delivered with short paths.

    • All the way to production — and beyond

      Not a demo but an accepted solution as code, with documentation and handover.

    • A direct network of experienced specialists

      Vetted senior specialists from our network when needed — with one point of contact.

    Projects

    Experience from regulated, data-intensive industries.

    All projects →
    • Pharma & Medical Technology · 5,000–10,000 employees

      Databricks platform with GenAI as a shared service

      One shared platform on which teams deliver new GenAI use cases from existing building blocks.

    • Transportation & Logistics · 1,000–5,000 employees

      Scalable data pipelines with Databricks and Data Factory

      Automated, monitored data pipelines instead of manual loads.

    • Automotive · 10,000+ employees

      Central business partner data in SAP

      One system of record for business partners with automated quality checks.

    Industries:Pharma & Medical TechnologyTransportation & LogisticsAutomotiveIndustrial Manufacturing & Machinery
    • Lakehouse platformsbuilt from architecture to acceptance
    • Data productsdesigned and taken into production
    • 10+ yearsdata, AI and SAP projects
    • CertifiedDatabricks, Microsoft and SAP

    Process

    End to end — from project start to operations.

    See the full process →
    1. Phase 1

      Initiate & understand

      • 01Project start
      • 02Analysis & requirements

      OutcomeGoals, scope and requirements are clear and agreed.

    2. Phase 2

      Design

      • 03Functional design
      • 04Technical design

      OutcomeFunctional and technical design are in place — delivery is plannable.

    3. Phase 3

      Build & assure

      • 05Development
      • 06Testing & QA
      • 07Documentation

      OutcomeA tested, documented solution as code.

    4. Phase 4

      Roll out & operate

      • 08Acceptance
      • 09Go-live & rollout
      • 10Operations & evolution

      OutcomeAccepted, live and supported in operations.

    Frequently asked questions

    How does working with you look in practice?

    In the initial call we clarify your goals and current situation. You then receive a short proposal with a clear scope and defined deliverables. We deliver together with your team, document as we go and hand over so you can carry on independently.

    Databricks, Microsoft Fabric or SAP Business Data Cloud — what fits us?

    We don’t decide by preference but by your data, the share of SAP, your AI plans, existing skills and cost. You get a reasoned recommendation — often it is a combination.

    Can we start with a small piece?

    Yes, we even recommend it. For example with a platform review, a single AI use case, Terraform and CI/CD, introducing Unity Catalog or one master data process.