AI FACTORY BUILDER
We help regulated institutions like banks, telcos and government entities design, build and run their own AI factories for software, governance, cloud, data, MLOps and training. Each factory runs in your tenant, in your country. Your engineers own it when we leave.
SIX FACTORIES
↑ first factory, live in 16 weeks
SHARED CORE
Meta-model · recipes · model gateway · policy-as-code · evaluation · evidence
YOUR TENANT · IN-COUNTRY
Any major cloud, in UAE and KSA regions
01 · WHAT
A factory is a governed production system. Agents and pipelines run versioned recipes inside guardrails, and every run leaves evidence. You choose which factories to build and in what order. All six share one core, so each new factory costs less than the one before.
AI SOFTWARE FACTORY
Spec-driven, multi-agent delivery. Analyst, architect, developer, tester, security and reviewer agents do the work. People approve the spec, the design, the merge and the release.
Built first · 16-week build
GOVERNANCE FACTORY
Produces the enterprise architecture artefacts, control mappings and registers that auditors and regulators ask for. Every obligation is traced to a control, and every control to its evidence.
Alongside the first factory · 8–12 weeks
CLOUD FACTORY · IAC
Infrastructure-as-code recipes for the major clouds, with configuration management built in. CBUAE, SAMA and NCA policy checks run on every plan before it applies.
Often second · 8–12 weeks
DATA PLATFORM FACTORY
Data contracts, quality rules, lineage and classification tags on every dataset. Classification decides where data may go. Every non-production environment uses synthetic data.
8–12 weeks
MLOPS FACTORY
Model registry, independent validation, deployment and drift monitoring, aligned to the CBUAE Model Management Standards. A prompt registry and RAG evaluation cover LLM applications.
8–12 weeks
AI TRAINING FACTORY
Role-based certification with hands-on labs for each learner. Tracks for Factory Operator, Recipe Author, Agent Reviewer and AI Risk Steward. Labs use synthetic data only.
Runs alongside every build
THE SHARED CORE
One core makes every next factory cheaper
Built on open standards and open source
DOMAIN PACKS
Agents work in your sector's language: BIAN service domains and semantic APIs for banks; TM Forum ODA, eTOM, SID and TAM for telcos; GovStack building blocks for governments.
INSIDE THE GOVERNANCE FACTORY
Audits and regulatory reviews fail on missing evidence, not missing intent. The Governance Factory keeps the architecture and the compliance record current as the systems change. It reads the same specifications, code and pipelines the other factories produce, so the evidence is never a separate project.
OBLIGATION
Agents extract obligations from regulations and policies, such as CBUAE, SAMA, NCA, PDPL and ISO/IEC 42001, into one register.
CONTROL
Each obligation maps to controls in a shared library, owned by a named person and enforced as policy-as-code where possible.
EVIDENCE
Evidence is collected from the factories on every change: specs, decisions, scans, tests, approvals and deployments.
AUDIT PACK
Audit and regulator packs are assembled on demand, versioned and signed. A compliance officer approves each pack before release.
evidence is produced by the work, not collected after it
ENTERPRISE ARCHITECTURE ARTEFACTS
REGULATORY REGISTERS
AUDIT AND REGULATOR PACKS
Agents draft; people approve. The Chief Architect signs off architecture artefacts and the compliance officer signs off registers and packs.
02 · WHY
AI coding tools are now on almost every desk. Without a governed system around them, they move risk faster than they move value.
ADOPTION
90%
AI raises throughput, but it still goes with lower delivery stability. The gain depends on platforms, small batches and safety nets.
Source: Google Cloud DORA, State of AI-assisted Software Development, 2025
SOVEREIGNTY
From UAE and KSA regions, many frontier models run only through cross-region routing. Each model call must be routed by data classification, and each route must be logged.
Source: AWS Bedrock, Azure AI Foundry and Google Vertex AI regional documentation, 2026
REGULATION
Outsourcing rules, AI guidance and cyber controls expect data residency, human oversight and a model inventory. ISO/IEC 42001 makes the system auditable.
CBUAE Circular 14/2021 · CBUAE AI/ML Guidance Note, 2026 · SAMA CSF 3.4.3 · NCA ECC
CAPABILITY
When a vendor runs the factory, the know-how leaves with the contract. Your team must own the recipes, the policies and the evaluation suites.
THE CASE FOR FACTORIES
A proof of concept is easy. Production is not. Before go-live, every project must pass three control gates: Security, Legal & Compliance, and Production Sign-Off (PSO). Pilots arrive at these gates without the evidence they ask for, and they wait. A factory produces that evidence on every change, so the gates become checks, not walls.
PILOT BY PILOT
FACTORY
every delivery improves the recipe for the next one
SECURITY
THE GATE ASKS FOR
A threat model, secure code, scanned dependencies, controlled data flows and access.
THE FACTORY BRINGS
A threat model per design, code and dependency scans, secret checks, a software bill of materials and signed builds on every change.
LEGAL & COMPLIANCE
THE GATE ASKS FOR
Data residency, outsourcing rules, data protection and model risk, with proof.
THE FACTORY BRINGS
Data classification, in-country model routing, control mapping to CBUAE, SAMA, NCA and PDPL, and a model inventory with owners.
PRODUCTION SIGN-OFF (PSO)
THE GATE ASKS FOR
Operational readiness: runbooks, monitoring, rollback and an approved change.
THE FACTORY BRINGS
Runbooks, service levels and alerts, a tested rollback plan and a complete change record, produced with the release.
PILOTS
95%
of generative AI pilots show little or no measurable P&L impact
PROOFS OF CONCEPT
30%
of generative AI projects forecast to be abandoned after proof of concept by the end of 2025
Source: Gartner prediction, 2024
PARTNERING
3×
Working with a specialist partner succeeds about three times as often as building alone
| WHY PILOTS STALL | WHAT THE FACTORY DOES |
|---|---|
| Weak data quality | Data contracts, quality rules and classification are part of every recipe. |
| Insufficient risk controls | Policy-as-code, four human approval gates and evidence on every change. |
| Rising costs | One shared core and reusable recipes. Cost per change is measured and falls over time. |
| Unclear business value | A delivery and cost baseline before the build; value is measured against it. |
| Tools that never learn the workflow | Workflow-first design from your SOPs. Recipes improve with every delivery. |
Causes: Gartner (2024) and MIT NANDA (2025). DORA 2025 adds that 90% of organisations already run an internal platform, and that high-quality platforms are what let AI benefits scale: a factory builds on that platform.
COMPUTE FACTORIES
FACTORY BUILDER PROGRAMME
The two work together: our delivery factories run on the AI infrastructure you choose.
03 · HOW
You buy one phase at a time. Each phase ends at a gate where you decide whether to continue. At every gate, you keep everything delivered so far.
EXECUTIVE BRIEFING
Half day
A briefing for your ExCo on AI factories and regulation, with a live factory demo.
READINESS ASSESSMENT
3–4 weeks
We score maturity on eight dimensions, take your DORA baseline and map your SOPs and value chain.
G-A · Go to design
Sponsor, pilot team and budget named
FACTORY DESIGN
4–6 weeks
ArchiMate target architecture, factory definition, policy pack, operating model and business case.
G-B · Go to build
Design and data flows approved
BUILD THE SOFTWARE FACTORY
16 weeks
We co-build the AI Software Factory in your tenant. A pilot team delivers real work on it.
G-C · Go to scale
Pilot targets met, staff certified
your team runs it from here
SCALE TO FACTORIES 2–6
8–12 weeks each
Governance, Cloud IaC, Data Platform, MLOps and Training factories. Our share of the work falls with each one.
S5 · ALONGSIDE, FROM S3
Five tracks: Factory Executive, Factory Operator, Recipe Author, Agent Reviewer and AI Risk Steward. Labs run on a separate, low-cost environment with synthetic data only.
S6 · AFTER, ANNUAL
Recipe and policy updates arrive as pull requests. Quarterly health reviews, regulatory watch and a bank of advisory hours. Three tiers: Essential, Professional, Sovereign.
ADVISE
For institutions with a strong platform team. We lead the design and the gate reviews.
Our share of the build: about 20%
CO-BUILD · DEFAULT
Our engineers pair with yours. By week 10 of the build, your engineers make half of the factory commits.
Our share: about 50%, falling to 20%
ACCELERATE
For thin teams or urgent mandates. We deploy the licensed kit; your team trains alongside us.
Our share: about 70%, falling to 30%
04 · SECTORS
We do not invent a domain model. Banks start from BIAN, telcos from TM Forum ODA, and governments from GovStack. Agents and recipes speak that language from day one.
BANKING · BIAN
The Banking Industry Architecture Network (BIAN) is our reference model for banks. It divides banking into standard service domains, each with a defined purpose, semantic APIs and business objects. Agents use it to name, scope and connect every service they build.
MAP REQUIREMENTS TO SERVICE DOMAINS
We place each requirement in the BIAN Service Landscape, by business area, business domain and service domain, so the scope is clear before the build.
DOMAINS BECOME BOUNDED CONTEXTS
Each service domain becomes a bounded context. Its semantic APIs and business objects are the contract between services.
CONFORMANCE IN THE PIPELINE
Recipes scaffold services from BIAN API definitions, and the pipeline checks every API against them. Deviations are recorded as decisions.
REGULATION ON EACH DOMAIN
We overlay CBUAE and SAMA controls on each service domain: data residency, outsourcing and model risk.
↑ the unit agents build and test against
EXAMPLE SERVICE DOMAINS
Payment Execution · Current Account · Customer Agreement · Party Reference Data Directory · Consumer Loan
Source: BIAN Service Landscape, accessed October 2026. We apply BIAN's published standard; BIAN is an independent industry association.
TELCO · TM FORUM ODA
TM Forum's Open Digital Architecture (ODA) is our reference model for telcos. It replaces monolithic BSS and OSS with standard ODA Components that expose TM Forum Open APIs and run on the ODA Canvas. Frameworx stays the shared language for processes, data and applications.
MAP TO PROCESSES AND DATA
We map each requirement to eTOM processes and SID information entities, and place it in the application map with TAM.
COMPONENTS BECOME RECIPES
Each ODA Component becomes a factory recipe: TM Forum Open APIs, SID-aligned data and a deployment for the ODA Canvas.
CONFORMANCE IN THE PIPELINE
Open API conformance tests run in the pipeline for every component before it is released.
AI-NATIVE ODA, LOCAL RULES ON TOP
We follow TM Forum's AI-native ODA direction, where components expose MCP interfaces to agents, and add UAE TDRA and KSA CST requirements.
↑ the unit agents build, deploy and certify
FRAMEWORX, KEPT AS THE SHARED LANGUAGE
eTOM for business processes · SID for information and data · TAM for applications
Source: TM Forum Open Digital Architecture, accessed October 2026. We apply TM Forum's published standards; TM Forum is an independent industry association.
GOVERNMENT · GOVSTACK
GovStack defines reusable building blocks for digital public services: autonomous software modules that expose REST APIs, are standards-based, preferably open source, and designed for scale. Its specifications inspire our government method and form the domain pack for government factories.
START FROM THE PUBLIC SERVICE
We map each citizen or business service to the building blocks it needs, using GovStack service patterns and use-case examples.
SPECIFICATIONS BECOME RECIPES
Each building block specification becomes a factory recipe and a conformance test. Agents build to the spec, and the pipeline checks every API against it.
REQUIREMENTS BECOME GATES
GovStack cross-functional requirements for development, deployment, architecture, quality, security and data run as policy-as-code gates.
LOCAL RULES ON TOP
We add the national layer: UAE TDRA and KSA NCA controls, NDMO data classification, and in-country hosting.
↑ secure data exchange between agencies
GOVSTACK PRINCIPLES WE APPLY
Openness · modularity · interoperability · sustainability · security · data ownership · user-centred design · API-first access · reusability
Source: GovStack specifications, accessed October 2026. GovStack is an independent initiative; we apply its open specifications.
05 · OUTCOMES
These are our default targets for the pilot team. We set the final targets during design, from your own baseline.
SPEED
−20%
Lead time for changes, with change-failure rate no worse
QUALITY
60%
Agent pull requests accepted by human reviewers
OWNERSHIP
50%
Factory commits made by your engineers by week 10
SOVEREIGNTY
0
Confidential data sent on offshore model routes
EVIDENCE
100%
Production changes with complete evidence
Source: programme targets, not reported results.
WHAT YOU KEEP
Everything we build in your tenant is yours. The core Builder kit is licensed to you for internal use. Without a subscription, the factory keeps running; only updates stop.
HOW WE STAY OUT OF YOUR DATA
Your staff operate the factory. We need no standing access to production or customer data, so your compliance team can classify the work correctly from the start.
06 · START
We bring a factory thesis for your institution, the regulatory picture for the UAE and KSA, and a live factory demo. You leave with one decision: assess, or not.
Or write to contact@majlisofai.com
Abu Dhabi · serving the UAE, KSA and the wider GCC
