AI development means integrating artificial intelligence into a working application — inference APIs, intelligent workflows, and AI-assisted features — so the AI output reaches users through the product, not a standalone notebook.
Who this is for
Businesses that have a specific workflow AI could meaningfully improve: automated analysis, prediction, personalization, or computer vision, where the value comes from AI being embedded in a real product rather than existing as an isolated experiment.
Problems it solves
- Manual analysis or decision-making that AI could accelerate or augment
- Existing AI experiments that never made it into a production application
- A need for AI features (recommendations, computer vision, prediction) inside an existing or new product
Capabilities
- AI-powered application features and intelligent workflows
- Third-party AI/LLM API integration into production systems
- Computer vision and motion/pose analysis
- Predictive and recommendation systems
- Model inference API design and deployment
Delivery process
The AI capability is scoped against a specific, measurable workflow first. Depending on the case, that means integrating an existing API or training a custom model (see AI Model Development), then wiring the inference layer directly into the production application.