Make AI part
of how
work gets done.
Assistants that know your business. Search that understands your documents. Useful AI features, built into the software your team already uses.
From the first use case to the application and infrastructure.
Prepare account access, assign a buddy, and schedule a first-week check-in.
↗ Sample onboarding checklistIllustrative workflow · example content
Start with a task.
Make it easier.
The useful question is where AI can help someone do their work. Here are three examples of the experiences we can build.
What does our onboarding checklist include?
Your example checklist has three steps: prepare account access, assign a buddy, and schedule a first-week check-in.
Interactive illustration with scripted responses. No AI service is called and no data is submitted.
Your application.
Your data decisions.
We help choose the model, connect the right information and define where human review belongs. Hosting and data handling are part of the design.
Integrate the right capability.
Use cloud models for assistants, content workflows and application features. We assess the provider, data processing settings, cost and quality against your requirements.
Explore a private deployment.
For suitable workloads, run an open model on infrastructure you control. We assess model quality, hardware capacity and operational needs before choosing the setup.
AI with a place
in the product.
PersoHR brings AI assistance into HR software. It is an example of how we connect application design, business workflows and AI integration in a product we build ourselves.
Explore PersoHR ↗Live product · Actual product interface shown
Useful starts
with specific.
We turn an AI idea into a defined engineering project, with representative examples and a way to judge whether it helps.
- Choose one useful task
Identify the users, the workflow and what a better result would look like.
- Connect the right context
Work through data sources, access permissions, model choice and the application's integration points.
- Evaluate before expanding
Test representative questions, unanswerable requests and handoff behavior. Review quality, latency and running costs.
- Build it into the workflow
Ship the integration, document the system and agree how it will be maintained.
A few good
questions.
Can you add AI to software we already use?
Yes, where the application and its interfaces allow it. We start with the workflow and integration options, rather than assuming a replacement system is needed.
Can an assistant answer from our own documents?
Yes. We can build document retrieval and source references into the application, with access controls appropriate to the content. We also define how the assistant should respond when the material does not contain an answer.
Can we run the model ourselves?
For suitable workloads, yes. Hardware requirements and the quality of the chosen model need to be assessed. A self-hosted model also needs ongoing operations.
How much does an AI integration cost?
It depends on the workflow, data sources, application and evaluation requirements. We scope the work with you and provide an estimate; there is no universal chatbot package.
What are you
working on?
A new product, a platform that needs attention, or an AI idea worth exploring. Let's talk it through.
info@labb-consulting.comTalk with an engineer. Reply within one business day.
Weekdays, 8:00–18:00 CET.