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AI Transformation Portfolio
After a successful Workflow Transformation Sprint, expand into a governed portfolio — multiple workflows, shared infrastructure, and consistent human oversight over 3–6 months.
3–6 mo
Typical portfolio engagement timeline
3–8
Workflows in a governed portfolio
1
Shared infrastructure layer across workflows
100%
Governance and oversight at portfolio level
Portfolio capabilities
Not a catalog of custom AI projects — a governed expansion of workflows on shared infrastructure, built after your first sprint proves AI works in production.
After a successful sprint, expand into a portfolio of connected workflows — shared triggers, data pipelines, and handoffs between processes instead of isolated automations.
Example applications
Portfolio-level policies for when AI acts autonomously, when humans must approve, and how exceptions escalate — consistent across every workflow in the portfolio.
Example applications
One integration layer, one monitoring stack, one knowledge base — reused across workflows so each new process ships faster and costs less to maintain.
Example applications
Customer-facing and internal chat workflows that share context, memory, and escalation paths — deployed as part of the portfolio, not standalone bots.
Example applications
Retrieval-augmented systems that power multiple workflows — documentation search, policy lookup, and context injection shared across the portfolio.
Example applications
Cross-workflow dashboards — throughput, error rates, human intervention frequency, and cost per workflow — so you optimize the portfolio, not just individual processes.
Example applications
Connect the portfolio to your full stack — CRM, ERP, ticketing, data warehouse, and legacy systems — through a maintained integration layer.
Example applications
Training, documentation, and operating procedures so your team runs the portfolio confidently — with clear ownership per workflow and escalation paths.
Example applications
Ready to expand beyond your first workflow? Discuss scope for a 3–6 month portfolio engagement — no published pricing, fixed proposal after assessment.
Discuss scopeWhy work with us
The portfolio delivers what a single sprint cannot: shared layers, consistent oversight, and a team that operates AI at scale across your operation.
Each workflow in the portfolio reuses integration layers, monitoring, and AI infrastructure built during your first sprint — so expansion is faster and cheaper than starting from scratch each time.
Consistent human oversight policies, audit trails, and approval workflows across every process — so leadership trusts AI at scale, not just in one pilot.
The portfolio connects to CRM, ERP, ticketing, data warehouse, and internal tools through a maintained middleware layer — AI embedded in operations, not bolted on.
Every workflow ships with monitoring, logging, error handling, and graceful degradation — the same production standards established in your sprint, applied portfolio-wide.
Cross-workflow dashboards measure throughput, cost, human intervention rates, and business impact — so you prioritize the next workflow based on data.
Training, runbooks, and change management so your team operates the portfolio after launch — with clear escalation paths and documented procedures.
How it works
A structured expansion from sprint foundation to governed portfolio — infrastructure first, then workflow-by-workflow deployment with shared governance throughout.
We review your sprint outcomes, map remaining high-friction workflows, and prioritize the portfolio roadmap — with governance requirements and shared infrastructure design.
Build the shared layer — integration middleware, monitoring, knowledge bases, and approval systems — that every subsequent workflow will reuse.
Deploy additional workflows on the shared foundation — each following sprint discipline with human oversight, testing, and production launch.
Portfolio-wide review — performance dashboards, cost optimization, governance audit, and a roadmap for ongoing expansion or handoff to your team.
Not sure whether to start with a sprint or consultancy?
If you have not transformed a workflow yet, start with a Workflow Transformation Sprint. If you need broader assessment first, our AI Consultancy maps opportunities before you commit to build.
Two paths in
Start with a Workflow Transformation Sprint
The portfolio builds on a proven first workflow. Our 4–8 week sprint transforms one high-friction process into production AI with human oversight — the foundation everything else expands from.
Expand into the portfolio
With one workflow live and trusted, we scale to a governed portfolio — shared infrastructure, multiple workflows, and consistent oversight over 3–6 months. Scope is discussed, not published.
The transformation ladder
Portfolio expansion is the natural next step after a successful sprint — and part of a broader AI transformation path across Azuya services.
Results
Portfolio clients expand from one proven workflow to governed multi-workflow operations — here are representative outcomes.
80%
Custom AI system for automating quality control in manufacturing. Computer vision replaces 80% of manual inspections with greater accuracy and speed.
95%+
Intelligent system for automatic call classification and routing. AI analyzes conversations in real time, classifies inquiry type, and routes to the agent with the best expertise.
70%
AI system for automatic processing of medical documentation — from extracting data from reports to structuring digital records. Physicians get 70% of their time back.
30 minutes · No pitch deck · Senior team on the call
FAQ
We strongly recommend it. The sprint proves AI works in one process your team trusts — and builds the integration foundation the portfolio expands from. Jumping straight to portfolio without a live workflow usually means slower delivery and lower adoption.
We do not publish pricing — scope depends on the number of workflows, integration depth, and governance requirements. After assessment we provide a fixed proposal. Discuss scope with us to get a tailored estimate.
Typically 3–6 months: infrastructure foundation in the first 6 weeks, workflow expansion through months 2–4, and governance optimization in the final phase. Timeline depends on workflow count and complexity.
Portfolio-level policies for autonomous AI actions, human approval gates, escalation paths, audit logging, and role-based access — consistent across every workflow, not reinvented per process.
Same standards as the sprint: self-hosted models when required, enterprise agreements for cloud models, encryption at rest and in transit, and GDPR-compliant documentation.
Yes. The shared infrastructure is designed for ongoing expansion — either with us on a retainer, through additional portfolio phases, or by your team using the runbooks and monitoring we deliver.
The sprint transforms one workflow in 4–8 weeks. The portfolio scales to multiple workflows on shared infrastructure with governance — typically after a successful sprint, over 3–6 months.
Start with AI Consultancy for a structured assessment, or go straight to a sprint if you already know which workflow hurts most. We will recommend the right entry point during scoping.
Transform your operation workflow by workflow — on shared infrastructure your team can trust and operate.