Your project
Useful AI starts with a well-chosen use case.
Internal assistant, document search, automation or chatbot: start from your teams, your data and your processes.
Your context
The challenges to translate into software.
You have identified a repetitive task, information that is hard to find or documents that take too long to process. The first decision is to choose a specific use case and define how its usefulness will be judged. Choosing a model comes next, along with data availability and access constraints.
- Choose a use case whose value can be evaluated
- Test a prototype with business users
- Prepare integration, data access and monitoring
Working together
From context to delivery.
We describe the current process, prepare representative examples and build a first journey. The prototype is evaluated with the people who will use the result. We also look at errors, missing information and actions that require approval. Delivery then brings in the APIs, interfaces and monitoring needed for go-live. If a prototype already exists, we start from it: that is the purpose of our AI POC to production service, which adds integration, access rights, evaluations and cost tracking.
Moving to delivery
The decisions and work to prepare.
The budget must separate development, integration and running the service. Model costs and response times depend on volumes and processing. A useful project keeps a human in the loop for cases that cannot be handled satisfactorily.
Learn more
Explore the scope further.
Let’s talk about your project.
Tell us what you want to build, who the users are and what your technical environment looks like. Together, we’ll define the first scope to explore.