AI workflow blueprint: decide where automation belongs before you build
An AI Workflow Blueprint is a paid project, normally two to four weeks, that ends in a decision. It maps one workflow or a small group, tests where AI would actually help, and hands back a scope you can approve, change or stop. It is a step you buy, not a free proposal or a pilot paid for twice.
Submit a project See the automation build serviceReviewed by David Nguyen (CEO) · Updated 6 Oct 2026
What the blueprint produces
Most AI spending decisions fail on the same three questions: which work is worth automating, whether the data supports it, and what a correct result looks like. The blueprint answers those three questions with evidence, and records what it could not answer.
At the end you hold a prioritized roadmap, a target workflow design, a justified prototype, an architecture, a data plan, a baseline and an implementation scope. You also hold the option to stop: a blueprint that recommends doing nothing has done its job.
What does the blueprint cover?
OutsourcingVN is operated by Netbase JSC, and this page describes Netbase's own service. It covers the assessment and design work in front of an automation build, and nothing else:
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AI opportunity review
Ranking candidate workflows by volume, handling effort, error cost and data readiness.
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Workflow redesign
How a chosen process would run if AI handled part of it, including exception routes and the point where a person decides.
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Data-readiness assessment
Whether the records the workflow depends on exist, are accurate enough and may lawfully be used.
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Agent feasibility
Whether tool-using software can safely take the workflow, or it should stay a narrow assisted step.
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Build-versus-buy analysis
Comparing a configured product, a platform module and a custom build against the workflow you actually have.
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Architecture and integration design
The systems, interfaces, permissions and boundaries an implementation would need.
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Measurement design
The evaluation cases, thresholds and baseline metrics an implementation would be judged against.
Other engagements are on the services page.
Is a blueprint the right first step?
Good fit
- You have a budget question to settle and want evidence before you commit to a build
- A named process owner can describe how the work runs today and who owns the result
- You can grant read access to the systems, samples and documents the workflow uses
- A decision is genuinely open, including the decision not to automate
Another route fits better
- You already know the workflow and the acceptance rule, and just want it built
- Nobody can be released to answer questions for a few hours a week
- No access to real examples is possible, so findings would rest on description alone
- The outcome is already fixed and the study is wanted as internal justification
Compare a configured product, a process change, an internal study, a direct build and other discovery suppliers by one test: can the result support a build, buy, redesign or stop decision?
What is the blueprint not?
It is not a production build. The prototype, where one is built, exists to test a hypothesis and is not deployed to users. When the workflow is already understood and the argument is settled, go straight to AI Workflow Automation, or to Custom Product Engineering when the outcome is a product rather than a process.
It is not a health check of your existing systems. If the real question is whether a codebase, cloud setup or security posture is sound, that is a technical audit sprint, which produces an evidence pack instead of a design.
It is not a way to unblock a platform that cannot carry the workflow in the first place. Where the blocker is an ageing application, legacy application modernization comes first and the blueprint follows it.
What we will ask for at the start
A first review moves faster with a description of the workflow and how often it runs, the systems it touches, a handful of anonymised real examples, who owns the result, and any hard constraint such as a data residency rule. Gaps become questions in the first week.
What is in the decision pack?
The exact list is agreed before the project starts. A blueprint delivers:
- a current-state map: steps, systems, volumes, exceptions, decision points and the person accountable for each result;
- a ranked opportunity list with reasoning, including rejected candidates and why;
- a data-readiness finding per candidate: what exists, what is missing, what is usable and the rights position;
- a target workflow design showing what the software does, what a person does, and what happens when the software is unsure;
- a prototype where one is justified, with the question it was built to answer and the answer it gave;
- an architecture and integration outline with the permission and data boundaries it assumes;
- an evaluation plan: representative cases, the definition of a correct result, and the threshold a build would have to meet;
- an implementation scope and milestone outline ready for a proposal, with its assumptions stated.
How the work is done
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Map and measure
Walk the workflow with the people who run it, record the steps and exceptions, and collect real examples. Establish the baseline you will later be measured against.
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Assess the data and the rights
Check the records the workflow depends on for availability, quality and permitted use, and write down what would have to change.
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Test the candidates
Shortlist the options, and where a question can only be settled by trying it, build a narrow prototype against real examples rather than arguing from a demonstration.
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Design, scope and decide
Produce the target workflow, the architecture, the evaluation plan and the implementation scope, then hold a decision session where you choose to proceed, change direction or stop.
Netbase delivers remote-first from Hanoi in Agile increments with weekly reviews, using AI-assisted engineering under human review. A blueprint team is small; the project delivery page describes how a Netbase project is planned, reported and accepted.
Milestones and acceptance
A blueprint runs as two or three milestones inside a fixed timebox, each naming its deliverables, the access and decisions it needs from you, and how it will be accepted. Most Netbase projects are agreed as fixed-scope contracts after discovery; a blueprint is often the discovery that makes such a scope possible, and engagement models explains how the arrangements differ.
Acceptance is a review of documents and, where a prototype exists, a demonstration against the examples it was built for. The closing deliverable is the decision session itself: the record of what was recommended, what you chose, and what was left open.
Risks we plan for
Reported as a finding with the work it would take, not hidden inside an optimistic scope.
Where accountability is unclear, the blueprint says so, because an automation without an owner cannot be accepted or corrected later.
Every prototype is labelled with its purpose, its limits and why it must not reach customers as it stands.
Whether the data may lawfully be used for this purpose is checked in the first milestone, not at the end.
Secure code review and version control, role-based access control and multi-factor authentication for admin dashboards are standard practice, contributors work under NDA, and NDAs and data processing agreements are available on request.
Models, data and human review
The blueprint is model-agnostic. Netbase works with commercial and open-source AI models chosen per project, based on the task, where the data may sit, operating cost and your constraints. A shortlist that names a model also names when it would be reconsidered.
Where your rules restrict AI tool use, for example on confidential source code or regulated records, that restriction is agreed before the project starts and applied to both the analysis and any prototype. Every recommendation in the pack is reviewed and owned by a named Netbase engineer or analyst; output from a model is never presented as a finding on its own.
Frequently asked questions
Two to four weeks is the normal timebox for one workflow or a small related group. A wider portfolio review is scoped as its own project.
No. The pack is written so that another supplier, or your own team, could implement from it. That is a deliberate test of whether the documentation is good enough.
That is a valid result. The pack then records why, what would have to change for the answer to differ, and which cheaper non-AI change is worth making instead.
Yes, when the workflow is understood, the data is known to be usable and the acceptance rule exists. Otherwise a fixed scope quoted in the dark helps nobody.
The process owner, someone who can grant read access to systems, and whoever will make the decision at the end. A few hours a week each is the normal load.
It stays with you as a test artefact with its limitations documented. Turning it into something people use is a separate build, which the blueprint scopes.
What has Netbase delivered after this kind of decision?
Netbase has delivered anonymised client AI projects including retrieval-based knowledge assistants, document AI and MLOps pipelines. The nearest published example of a design-and-prototype milestone leading into a build is the WhatsApp AI chatbot record: intent and conversation-flow handling, an LLM API (GPT-4 in the stack) and CRM synchronisation, delivered in milestones from design and prototype to knowledge transfer and 30 days of support over 4-8 weeks. It was a build, not a stand-alone blueprint. Every record is on the Work page; the methodology sets out their evidence rules.
Netbase designed and built an AI chatbot on WhatsApp Business that handles intents and conversation flows and keeps lead and customer data in step with the client's CRM, delivered in milestones from prototype to knowledge transfer.
Keep ReadingWhich guide should you read before a blueprint?
Read the guide first, then the closest case.
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The business workflow transformation guide
A business process that costs too much handling time
Then the closest case Marketplace operations, customer support, ERP and back office, orders and payments, documents and approvals, dispatch and delivery, business directories, B2B ordering portals, data platform readiness
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The emerging technology adoption guide
A technology you are asked to adopt
Then the closest case Production inference, RAG and context engineering, semantic search, multimodal document AI, edge AI, speech interfaces, robotics software, agent tool permissions, AI assurance
Ready to settle the question?
The natural next step from an approved blueprint is AI Workflow Automation, which builds and pilots the workflow the blueprint designed, and managed operations when you want the result monitored and improved after handover. Submit a project brief describing the workflow, who owns it and the decision you are trying to reach. OutsourcingVN is operated by Netbase JSC and is Netbase's own outsourcing-services platform.