Data flow and preparation
Connect the required data sources, define transformations, and prepare the inputs and context needed by the feature.
AI & automation
AI pipelines that connect data to your product
AI pipelines that turn source data into a working product feature. We connect data preparation, model calls, retrieval, and output processing to the applications and services around them.
Discuss an AI pipeline
How we approach this work
An AI feature depends on the workflow around the model. Data needs to arrive in a useful form, the right context needs to reach the model, and the result needs to fit the product. We build those connections as part of the application architecture, with explicit handling for errors and changes in behavior.
What we work on
Model and retrieval integration
Orchestrate model calls and retrieval steps where they are useful, then connect their outputs to application APIs and product workflows.
Evaluation and operations
Define representative evaluation cases, track model and workflow versions, and make latency, failures, and usage visible to the team.
Explore the Use Cases
Illustrative scenarios with proposed tools and implementation notes.
For custom development
Describe the feature you want to build, the available data sources, and any existing models, APIs, or application workflows.