AI workflows · application engineering
Build useful AI into the systems your business already uses. We connect the workflow, check the output, and make responsibility clear.
An Aligned engineering practice.
From a practical decision to software in everyday use.
A customer requests
a delivery change.
Useful capability.Clear operating responsibility.
Engineering behind the outcome01 / How we help
One workflow, a useful prototype, or a decision about where to start. Each can be an independent engagement.
A workflow to improve
Connect AI to the applications, information, and handoffs your team already uses. Build in output checks, exception handling, human review, and a clear route to operating it.
What we work towardA scoped workflow, implemented and tested against agreed criteria.
A prototype to rely on
Review, strengthen, and deploy an application built with AI coding tools. Work through access controls, secrets, data handling, tests, deployment, and recovery. The application itself need not contain AI.
What we work towardA practical release decision, agreed fixes, and an operating plan.
A decision to make
Compare buying, configuring, integrating, and building around a named business need. Account for data access, implementation effort, adoption, running costs, and who will maintain the result.
What we work towardAn actionable recommendation you can commission separately.
02 / Illustrative applications
A few places to look for a useful first project. The right scope depends on your systems, information, and review requirements.
A customer request arrives in an inbox. The workflow identifies the request, looks up the relevant record, and prepares a proposed update.
Interpret the request and extract the relevant information.
Check required fields, account access, and the current record.
Approve a consequential change or resolve an exception.
A document needs to become structured information in an existing business application. The workflow extracts fields and routes uncertain or conflicting values for review.
Extract and classify information from the document.
Validate formats, required values, duplicates, and business rules.
Review uncertain fields before the record is accepted.
A team member needs an answer from approved business information. The workflow retrieves relevant sources and drafts an answer with references.
Draft a response grounded in retrieved material.
Respect source permissions and check whether supporting information is present.
Review sensitive responses and handle questions the sources cannot answer.
Already built something with AI?
A useful vibe-coded application can be a starting point. Before the business relies on it, we review the code, data, integrations, and operating needs, then agree what to retain, change, replace, or stop.
Bring one prototype or a recurring backlogRelease against agreed criteria.
Document the risks that remain.
03 / How we work
We stay close to the applications, data, and infrastructure. The operating details belong in the plan from the start.
Name the workflow, users, information, and outcome. Compare the options and agree access, constraints, costs, and how the result will be assessed.
Implement the integration and test it against representative cases. Include quality evaluation, consequential-action review, exceptions, and recovery.
Agree who uses and maintains the system, what it costs to run, and how problems are handled. Keep accounts, code, and operating knowledge accessible.
We build around suitable existing applications and cloud foundations. Microsoft tools can be part of the implementation, with access, licensing, integration, and support needs established for the actual workflow.
The engineering practice behind AI Works
Led by Chris Constantin, a hands-on architect and engineer with 25+ years of experience. He holds Microsoft Certified Multi-Agent AI Solutions Expert and Azure Solutions Architect Expert credentials.
Meet the people behind the workAt Responsive, Aligned simplified cloud infrastructure and automated customer onboarding alongside the client’s engineers. That work shows the integration and operating foundations we bring to new projects.
Read the published engineering caseBefore we talk
No. Bring a workflow, an application, or a decision. We compare practical options and explain what would need to be connected, tested, paid for, and maintained. We use conventional automation where it is more dependable or economical.
No. An owner, COO, or other accountable sponsor can commission the work. We involve workflow users, data owners, technical leaders, and existing providers where available, then agree who will approve changes and operate the result.
Yes. Microsoft 365 and Azure are a natural starting point where they already support your business. We assess the relevant applications, permissions, data, licensing, and integration routes before selecting an approach. Suitable existing systems and providers remain part of the plan.
Yes. We scope around a useful first outcome. A recurring application backlog is also possible, with shared foundations where needed and separate review and release decisions for each application. Not every prototype should be released.
We agree scope, deliverables, acceptance criteria, and fees before work begins. Hosting, licensing, and usage costs are made explicit. You control your accounts and retain access to source, configuration, and operating knowledge, respecting third-party licenses. Maintenance is optional and separately scoped.
Bring something worth making work
Tell us about a workflow, a prototype, or a decision. We’ll discuss whether AI belongs in it and what it would take to make the result useful.
Talk to Aligned AI Workshello@aligned.netPrefer a form? Send an inquiry through Aligned
Scope, fees, and operating responsibilities are agreed before work begins. Continued maintenance is a separate, optional agreement.
