Ship production AI systems that move business metrics.
Turn a validated AI opportunity into a workflow, internal tool, automation system, or AI-enabled product running inside your business.
Built by an AI-enabled delivery team. Designed for production. Measured by outcomes - not activity.
From $10,000/month
Month-to-month · No lock-in
From roadmap to running system
AI creates value when it changes how work gets done - and keeps working after the demo.
Production AI Delivery is for companies that already have a validated opportunity, a painful workflow, a stalled prototype, or a clear AI idea that now needs to become a real system.
Validated opportunity
What it usually meansDiscovery is done, the business case is clear, and the next step is buildWhat we deliverProduction AI workflow, automation, internal tool, or AI-enabled product
Painful process
What it usually meansWork is slow, manual, inconsistent, or hard to controlWhat we deliverRedesigned workflow supported by AI and integrated into existing tools
Stalled prototype
What it usually meansA demo worked, but nothing reliable shipped into the businessWhat we deliverProduction reset: architecture, scope, reliability, testing, and deployment
Internal capacity gap
What it usually meansYour team has the domain knowledge but lacks senior AI delivery capacityWhat we deliverAI-enabled delivery team that builds with your team and transfers ownership
The goal is not to "add AI." The goal is to ship a system that changes a business process and moves a measurable outcome: cycle time, team capacity, quality, consistency, throughput, or cost-to-serve.
What we build
Production AI Delivery can take different forms depending on the opportunity.
AI workflows
AI-assisted workflows that reduce manual work, speed up decisions, and make the process easier to control.ExamplesIntake triageResearch and summarization workflowsSales or recruiting workflowsQA and review workflowsDocument-heavy operational processes
Internal AI tools
Secure tools used by your teams to complete real work faster and more consistently.ExamplesInternal copilotsKnowledge assistantsCase or ticket analysis toolsReport and artifact generatorsWorkflow-specific decision support tools
Automation systems
AI-enabled automation connected to your existing systems, data, and business rules.ExamplesCRM or ATS automationDocument processingLead enrichmentCandidate screening supportBack-office workflow automation
AI-enabled products
Customer-facing or internal product capabilities powered by LLMs, agents, RAG, or AI orchestration.ExamplesAI product featuresDomain-specific assistantsEvaluation-backed AI modulesAgentic workflowsAI-powered data and content products
What changes in your business
You do not buy a team. You buy a measurable operational change.
Cycle time
A process that used to take days or hours becomes faster and easier to manage
Team capacity
People spend less time on repetitive work and more time on judgment, customers, and execution
Quality & consistency
Work becomes less dependent on individual habits, manual copy-paste, or inconsistent review
Throughput
The same team can process more requests, candidates, leads, tickets, documents, or tasks
Control
The workflow becomes observable, testable, and easier to improve over time
We define the target metric before building, then ship against it.
The process
How production delivery works
Align on the outcome
We start with the business metric, workflow, users, constraints, and definition of done. The first question is not which model to use - it is: what should change in the business when this system works?
Design the production path
We translate the opportunity into buildable scope:
- MVP boundaries
- Workflow design
- Data and integration needs
- Security and access assumptions
- Evaluation and QA approach
- Rollout plan
- Adoption and ownership model
Build in production sprints
We ship in short cycles with demos, feedback, and visible progress. Each sprint moves the system closer to business use - not just technical completion.
Validate reliability
Production AI requires more than prompt quality. We cover:
- Test cases
- Regression checks
- Output validation
- Human review paths
- Monitoring needs
- Failure modes
- Rollback and escalation logic
Operationalize and hand off
The system is documented, reviewed, and prepared for real use. Depending on your needs, we can continue scaling it, optimize it, or hand it off to your internal team.
What ships every month
Concrete progress, not status reports.
Production increments
Working releases of the AI workflow, tool, automation system, or product capability.
Stakeholder demos
Regular demos so business owners can see what changed, test assumptions, and redirect priorities early.
Tested and reviewed code
Code, prompts, workflows, and integrations reviewed for maintainability, reliability, and security.
Evaluation and QA coverage
Test cases and validation logic for the AI behavior, not only the surrounding application code.
Documentation and handoff material
System notes, workflow logic, operating assumptions, and ownership guidance.
Roadmap refinement
Monthly review of what shipped, what changed, what to improve, and what should happen next.
The delivery team behind the outcome
You do not need to hire a full AI department to ship the first production system.
We bring the roles needed to move from idea to operation.
Solution Architect
SADesigns the technical path, integration approach, architecture, and production constraints.
Product Manager
PMKeeps the work tied to business outcomes, users, scope, and delivery priorities.
AI / Agentic Developers
DEVBuild the workflows, tools, agents, integrations, and product capabilities.
QA / Reliability Engineer
QAMakes the AI system testable, reliable, and safe enough for real business use.
The team shape can scale up or down based on the workstream, but the goal stays the same: ship production AI that changes the business.
Onboarding timeline
How onboarding works.
Week 1
Outcome alignment & context transfer
- Kickoff with business and technical stakeholders
- Workflow, system, and access review
- Target metric and definition of done
- Sprint 0 planning
- Delivery workspace setup
Weeks 2-3
First production increment
- First workflow, feature, or automation increment shipped
- Weekly demo and feedback cycle
- Backlog refinement with your team
- Early validation against real users or real workflow data where possible
Week 4+
Production cadence
- Ongoing production sprints
- Continuous deployment or controlled release rhythm
- QA, evaluation, and monitoring improvements
- Monthly roadmap and outcome review
- Scale, optimize, or hand off as needed
Pricing
Start lean. Scale when the system proves value.
All tiers are month-to-month. No long lock-in. Start with the smallest delivery shape that can create a real production signal.
Starter
Best for first deployment or validating the production model.
- 1 active workstream
- Lean AI delivery team
- 1 sprint every 2 weeks
- Best for: first production workflow, internal tool, or automation
Growth
Best for companies ready to move beyond the first win.
- 2 parallel workstreams
- Expanded delivery capacity
- 2 sprints per month
- Best for: scaling after first production result or running parallel AI initiatives
Scale
Best for multi-department transformation or complex AI product delivery.
- Multi-stream capacity
- Cross-functional delivery team
- Continuous delivery
- Best for: AI-first transformation across business units, operations, or product lines
Is this right for you?
Good fit
- You have a validated AI opportunity and now need it built properly.
- You completed Discovery and have a roadmap, MVP scope, or business case.
- You have a painful workflow that needs to become an AI-supported operating system.
- You have an AI prototype that worked in a demo but did not ship into production.
- Your internal team lacks senior AI delivery capacity.
- You need production AI, not another proof of concept.
- You want to move fast without building a full internal AI delivery team first.
- You want a system your team can eventually own.
Not a fit
- You are still unsure whether AI applies to your business.
- You need a generic AI workshop or training session.
- You only want staff augmentation with no outcome ownership.
- You want a quick prototype without validating the business case.
- You are not ready to give access to process owners, systems, or decision makers.
- You do not have a business process, product idea, workflow, or metric to improve.
If you are still exploring where AI fits, start with the free Snapshot. If you need the business case and roadmap first, start with Discovery.
The proof
We built this model inside a real software company before offering it externally.
100+
Workflows deployed
81%
Faster QA
18 mo
Framework maturity
$0
Additional headcount required
AdvantageWorks was born inside Ascendix Technologies (founded 1997), a 30-year-old software company. The Portugal-based AdvantageWorks team was established in 2021 to operationalize AI transformation work - first internally, then for clients. The model was shaped through real internal delivery: engineering workflows, production systems, AI-enabled processes, and operating-model change across a team of 150 engineers.
The same delivery model now helps clients move from AI ideas and prototypes to production systems running inside the business.
Which engagement is right for you?
| AI Opportunity Snapshot | Discovery Sprint | Production AI Delivery | |
|---|---|---|---|
| Price | Free | $5,000 | From $10,000/month |
| Duration | 30 minutes | 1 week | 3-6 months |
| Best for | Unsure where to start or validating if there is a real opportunity | Ready to define the opportunity properly | Ready to ship a system that runs in the business |
| What you get | Opportunity read + named quick wins + go / no-go | Validated opportunity, MVP scope, ROI model, prototype, roadmap, and delivery plan | Production AI workflow, internal tool, automation system, or AI-enabled product running in your business |
| What changes | You know what is worth exploring next | You know what to build, what it may cost, and what it should return | A business metric moves: cycle time, team capacity, or quality / consistency |
| Depth | Directional | Strategic and technical | Implementation and operationalization |
| Next step | Go alone, Discovery, MVP path, or pause | Build internally or with us | Scale, optimize, or hand off |
Common questions.
Ready to ship production AI?
From $10,000/month. Month-to-month. No lock-in. Move from roadmap, prototype, or stalled AI initiative to a production system that runs in your business.
Senior AI delivery · Production systems · Measurable business outcomes