AI application development and integrations
Connecting a model is only part of the product. I build applications where AI works with a user’s context, materials and actions: content planning, writing tools, research and customer conversations.
What we can build
Content and publishing
Plan, generate, edit and prepare materials for publishing in one workspace.
Writing tools
AI commands in an editor, drafts, research and source-based workflows.
Application integrations
Bring AI into an existing process with the right context, permissions and user controls.
What the work includes
- Product architecture and model selection for the task
- Interface, API and AI provider integrations
- Queues, error handling, limits and usage tracking
- Evaluation on agreed examples and deployment
How development works
Define the result
We identify the work AI should help with and the examples we will use to assess it.
Validate the approach
We test the model and context on typical tasks before building the full workflow.
Build the product
I implement the interface and backend, including waiting states, retries and usage restrictions.
Launch and evaluate
We review output quality and resource use. Further improvements follow real usage.
Related projects
Before we start
Can AI be added to an existing service?
Yes. First we review its architecture, APIs and available data, then choose the integration point and scope of changes.
Can every answer be guaranteed correct?
No. Important actions need checks and user oversight. The product can include editable outputs, source links and confirmation before an action is carried out.
What costs are separate?
Model usage and external services depend on the provider and workload. We separate those costs from development and discuss them when choosing an approach.