ArniTech Digital Solutions

AI Training / Enterprise Data and API Integration for AI

Training track

Enterprise Data and API Integration for AI

Connect AI safely to systems of record with API-first and event-driven patterns.

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Naming and scope note (checked October 2026). Vendor-neutral integration patterns. Examples include REST and event-driven designs, Apache Kafka, and enterprise middleware such as webMethods; we align examples with the tools you use. Product names are trademarks of their owners.

Best fit: Integration and platform teams, and leaders planning AI that must read from and write to core systems.

Courses by audience

Engineers, architects and technical teams

Enterprise Data and API Integration for Modern AI Systems

Duration: 3 days (proposed) · Format: Hands-on cohort: private, or open when scheduled

Who it is for

Integration architects, API and platform engineers, data engineers.

Prerequisites

Experience with APIs or integration platforms.

Learning outcomes

  • Design API contracts and event streams that AI services can use safely
  • Keep writes to systems of record deterministic, idempotent and auditable
  • Choose between API, event, batch and CDC patterns

Curriculum

  • API-first design, versioning and contracts
  • Event-driven backbones and schema governance
  • Hybrid-cloud middleware and gateway patterns
  • Idempotency, outbox, retries and reconciliation
  • Data access control and masking for AI
  • Observability and audit trails

Hands-on exercise

Design and prototype the integration between a core transaction system and an AI service.

Takeaway materials

  • Integration pattern catalogue
  • API and event contract templates
  • Reconciliation and audit checklist

Completion outcome

ArniTech completion certificate (not a vendor certification).

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Executives and business leaders

Integration Strategy for AI Programmes

Duration: Half day (proposed) · Format: Workshop, on site or live online

Who it is for

Technology leaders funding AI that touches core systems.

Prerequisites

None.

Learning outcomes

  • Spot integration debt that will stall AI programmes
  • Set architecture principles for AI-to-core connections
  • Sequence modernisation and AI delivery

Curriculum

  • Why prototypes fail at integration
  • Systems of record and deterministic boundaries
  • Build, buy and middleware decisions
  • Roadmap and risk

Hands-on exercise

Map your top AI use cases to the systems and integrations they depend on.

Takeaway materials

  • Decision checklist for approving AI use cases
  • One-page adoption roadmap template
  • Board-level briefing outline

Completion outcome

ArniTech completion certificate (not a vendor certification).

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What happens after you enquire

  1. You complete a short form naming the track and audience. It prepares an email draft, and you press Send.
  2. We reply by email with scoping questions: group size, tools, environment and delivery preference.
  3. You receive a written proposal with agenda, duration, format and price, tailored to your teams.
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