LINX LABS / 05
AI Integration & Business Workflow Automation
Useful intelligence that connects your tools and simplifies daily work.
Start a projectWhat we can build
A scope that fits your project
Start with the work that needs to get easier. We identify practical opportunities for AI and automation, then connect the right services with clear controls and human oversight.
Workflow automation
API integrations
02 / HOW WE WORK
A clear process.
A shared ambition.
01
Discover
Understand your business, your audience, and what success should look like.
02
Design
Turn the direction into a clear, coherent experience before development begins.
03
Build
Develop, test, and refine the details across devices and real user journeys.
04
Launch
Prepare the release, hand over the essentials, and plan the next iteration.
Where this service fits
For teams spending time copying data, sorting incoming requests or searching internal information. We start with one measurable workflow and review the data, permissions and exceptions. Automation should have a clear owner and a way to recover when an external service or model returns an unexpected result.
LINX / PROJECT NOTES
Questions before you start
A quote built around your scope.
Share the main user journeys, required integrations, current tools, target launch date and any content or designs you already have. We use these details to agree on deliverables, review milestones and cost before development. Hosting, third-party subscriptions, maintenance and source-code handover are clarified in the proposal. Payment is by bank transfer after you approve the quote and agreed deposit terms.
Which tasks are suitable for AI automation?
Document sorting, assisted drafting and information retrieval may benefit from AI when there is an appropriate review process. Predictable tasks such as moving validated data between systems may work better with conventional rules. We choose the approach around the task rather than adding AI to every step.
How do you handle sensitive data and incorrect AI output?
During scoping, we review what data an integration needs, which providers receive it and which actions need human approval. Access limits, validation and error handling are planned for the workflow. AI output can be inaccurate, so consequential actions should not rely on an unchecked model response.
THE NEXT CHAPTER
What are you
thinking about?
A new website. A better app. An idea ready to take shape.
Start a project