AIVAN by Oivan

Agentic AI Development. Under Your Control.

Meet AIVAN, Oivan’s framework for applying agentic AI to software delivery.

AIVAN brings AI agents, engineering practices and supporting infrastructure together to help teams deliver software more efficiently, with human accountability and control over the technology they use.

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Built by engineers working on real client systems. Shaped by Oivan’s software and critical-platform experience in Saudi Arabia since 1998.

Introducing AIVAN

AI Needs More Than a Coding Tool

Generating code is one part of software delivery. Understanding requirements, working within an existing architecture, testing changes and maintaining accurate documentation all demand context and judgment.

AIVAN is Oivan’s proprietary agentic AI framework and technology stack for addressing these challenges. It combines reusable task templates, agent runtimes, model access and delivery controls with the experience of the engineers responsible for the outcome.

  • Today: software delivery

    AIVAN focuses entirely on software development and its delivery lifecycle.

  • Roadmap: across the enterprise

    AIVAN’s roadmap extends the same approach across the enterprise. We’re laying the groundwork for finance, HR and operations teams to easily deploy and run AI agents securely and at scale.

Agents Do the Work. People Own the Outcome.

We select tasks according to their risk and suitability for AI. Engineers review the results, and people remain responsible for approving what ships.

AIVAN for your role

More Delivery Capacity, with a Clear Measure of Value

AIVAN helps teams explore where agentic AI can shorten delivery time and reduce repetitive work without losing sight of quality or accountability.

  1. 01

    Address Delivery Bottlenecks

    Apply agents to bounded development, testing and documentation tasks so experienced people can concentrate on decisions that require their judgment.

  2. 02

    Improve the Systems You Already Have

    Start with a real change to an existing application. Evaluate how AI handles the codebase, dependencies and accumulated technical debt.

  3. 03

    Measure the Complete Task

    Compare delivery time and human effort with an agreed baseline, including review and corrections. Assess the quality of the accepted result alongside model costs.

  4. 04

    Keep Technology Choices Open

    Choose models according to the task and data requirements. AIVAN’s architecture aims to reduce dependence on any single model provider or agent engine.

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Model and infrastructure choice

Your Data Requirements Shape the Solution

Model quality, cost and data handling all influence whether an AI workflow is suitable for a particular project.

AIVAN uses a common model gateway to separate model access from the delivery workflow. In AIVAN work, Oivan has used both external model services and models running on its own infrastructure.

For each engagement, we assess approved data, model access, hosting requirements and contractual restrictions before selecting the implementation. The architecture is designed for portability, with deployment readiness assessed for the chosen environment.

Oivan’s AI expertise

Engineering the Application and the Environment around It

  • Agentic Software Delivery

    Introduce AI into development with suitable tasks, reusable instructions, engineering review and measurable pilot outcomes.

  • AI Applications and Knowledge Assistants

    Build applications that connect language models with your organization’s information, systems and business rules.

  • AI-Assisted Modernization

    Apply AI to understanding existing code, implementing changes, improving tests and maintaining documentation.

  • Intelligent Operations

    Combine monitoring, automation and AI interpretation to give operations teams clearer information for investigation and response.

  • Secure AI Infrastructure

    Design and operate the platforms, access controls and security services that AI workloads depend on.

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AI in practice

Experience from Real Engineering Work

Client case

A Private AI Assistant for Urban Planning

For a major Saudi giga-project, Oivan developed an assistant that helps users find answers in complex planning information.

The solution combines a rules-based FAQ layer with a language model and retrieval from more than 50 planning documents. It runs in the client’s own data center, keeping the information within the organization’s infrastructure.

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Client case

Introducing AI into Software Delivery

Oivan introduced Windsurf into the development organization of a government-backed Saudi real estate technology company.

Adoption grew to more than 30 developers. The work combined hands-on enablement with rules for approved use, testing and human review, while identifying where AI assistance worked well and where complex codebases required more context.

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Engineering initiative

Making Anomaly Alerts Easier to Act On

In an Oivan engineering initiative, we combined Elasticsearch Machine Learning, n8n automation and language-model analysis to enrich monitoring alerts.

The workflow gathers relevant context and produces readable explanations with suggested validation steps, giving engineers a better starting point for investigation.

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Our partners

Technology for Secure AI Adoption

Oivan works with GitLab, SUSE and F5 to help organizations choose and implement the technologies around their AI workloads. We assess the combination against each client’s delivery, infrastructure and security requirements.

GitLab

AI within the software delivery workflow

GitLab Duo Agent Platform brings AI agents into software development, with capabilities for coding, review, security analysis and delivery workflows. GitLab Self-Managed also supports self-hosted model options.

Oivan helps teams connect AI adoption with their DevSecOps practices, permissions and review processes.

SUSE

Infrastructure for private AI

SUSE’s AI portfolio and Rancher Prime provide foundations for deploying and managing AI workloads on infrastructure the organization controls.

Oivan brings Kubernetes, private-cloud and infrastructure operations expertise to help establish an environment that teams can maintain and secure.

F5

Protection for AI applications and interactions

F5 AI Guardrails helps protect models and agents against threats such as prompt injection and sensitive-data leakage. F5 AI Gateway provides controls for model traffic, access and usage.

Oivan helps organizations assess these capabilities alongside application delivery, API security and operational resilience.

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Why Oivan

Built from Delivery Experience

Oivan has developed software and operated critical digital platforms in Saudi Arabia since 1998.

Our teams combine software engineering with experience in cloud operations, cybersecurity and government-services integration. We understand that introducing AI into an established organization involves existing systems, client commitments and people who remain accountable for delivery.

We develop and use AIVAN in our own work. Lessons from real projects shape its task templates, controls and model choices.

More about Oivan
Get started

Start with One Software Delivery Challenge

Choose a task that matters to your team and is small enough to evaluate properly.

  1. 01

    Establish the Baseline

    Agree on the task, expected result and current delivery effort.

  2. 02

    Define the Boundaries

    Assess risk, approved data, model access and the required human reviews.

  3. 03

    Run and Evaluate

    Use AIVAN on real work. Review the result and compare total effort, quality and cost.

  4. 04

    Decide What Comes Next

    Expand successful patterns, adjust what needs improvement and retain manual approaches where they work better.

Tell us about your application, delivery challenge and operating environment.

Discuss an AIVAN pilot