Turn AI production into an operating capability with an Enterprise AI Factory
Behind every Enterprise AI Factory are two connected layers, each solving a different challenge on the path to production.
LAYER 01
Defines how AI demand moves into production. It brings together intake, prioritization, delivery stages, reusable assets, governance controls, and accountable execution.
LAYER 02
Provides the technical foundation for production. Compute, data pipelines, models, orchestration, observability, and platform services determine how far the factory can scale.
Factory AI turns delivery into a standing enterprise capability rather than a sequence of disconnected engagements
01
A client-specific POD operates inside the enterprise environment, aligned to one production roadmap and one operating context.
02
Engineering and domain roles adjust to the use case, enterprise architecture, delivery priorities, and current AI maturity.
03
Success measures, acceptance criteria, and commercial milestones are agreed before delivery begins.
04
Two-week cycles keep working software, technical decisions, and emerging delivery risks visible throughout production.
The strength of an AI Factory comes from how its people, processes, and technology work together to deliver AI consistently over time.
Implementing an Artificial Intelligence Factory changes the fundamental trajectory of how capacity expands across high-impact releases
The AI factory starts at the capability required today and grows with the production estate
Positioning
Building the First Production AI Capability
Enterprise Profile
Early production AI with foundational capabilities still developing.
POD Focus
Validate use cases, improve readiness, and deliver the first production solution.
Core Roles
Validate use cases, improve readiness, and deliver the first production solution.
Outcome
First production AI solution with assessed data readiness.
Typical Duration
3 to 6 months
Positioning
Expanding AI Across the Enterprise
Enterprise Profile
Growing AI adoption with increasing demand for governance and scale.
POD Focus
Expand deployments, strengthen governance, and improve AI performance.
Core Roles
Foundation roles, AI Architect, Domain Specialist
Outcome
Governed multi-agent AI deployment.
Typical Duration
6 to 12 months
Positioning
Operating AI as a Continuous Capability
Enterprise Profile
Mature AI estate requiring continuous ownership and optimization.
POD Focus
Run the AI lifecycle, optimize operations, and drive continuous improvement.
Core Roles
Growth roles, QE Engineer, Change & Adoption Lead
Outcome
Fully operational Enterprise AI Factory.
Typical Duration
12 months+
Create repeatable AI delivery across the enterprise
The enterprise AI factory keeps qualified opportunities moving through a clear and accountable production flow
Leadership reviews working software every two weeks, keeping progress and production decisions visible.
Commercial milestones remain connected to agreed performance benchmarks throughout delivery.
Qualify the opportunity against business value, technical feasibility, data readiness, and production impact.
Configure the delivery team around the use case, enterprise estate, domain context, and required technical depth.
Set performance benchmarks, delivery milestones, acceptance criteria, and commercial accountability.
Develop, validate, integrate, and release the solution inside the enterprise environment through governed sprint cycles.
Monitor performance, tune models, improve workflows, and move the next qualified use cases into the production pipeline.
Activate an established delivery model instantly, or methodically develop internal capabilities from the ground up.
The enterprise AI factory brings production discipline to environments where complexity carries real operational weight
Financial Services
Automate high-volume financial processes with embedded governance, traceability, compliance, and audit controls.
Mortgage
Streamline document-intensive lending workflows with intelligent extraction, decision support, and platform integration.
Oil and Gas
Connect field operations, enterprise systems, and operational data to improve visibility and decision making.
Manufacturing
Transform shop floor data into faster quality, maintenance, production, and supply chain decisions.
Retail
Improve merchandising, inventory, supply chain, and customer operations through faster AI-powered execution.
The enterprise AI factory reflects operating experience gained across real production environments
The same operating model powering client delivery also runs across AppsTek operations.
The Enterprise AI Factory creates the operational capability for continuous AI delivery.
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Production starts with the right model
