AI inside a product
A product feature that summarizes, drafts, classifies, or answers a specific user question, with clear controls and useful feedback.
AI product development / Santa Monica
Custom AI product development.
Eonstar develops custom AI applications and AI features for existing products. The work connects product strategy, interaction design, model behavior, and software engineering around a clear user task.
Start with
real work.
Examples of project scopes to discuss with Eonstar. The right scope depends on the people, information, and tools involved.
Knowledge and research tools
An interface for finding and working with relevant documents or business information, with source context and review built into the experience.
From concept to a usable interface
A focused prototype or application that brings the core user journey, AI behavior, and supporting integrations together.
The work
Considered
at every step.
A project scope can include:
- Define the audience, primary task, and acceptance criteria.
- Design the main experience and the states around the AI output.
- Connect model calls, relevant data, and the supporting application.
- Evaluate useful behavior, failure states, and the path to deployment.
Useful answers
Questions,
answered.
What does an AI product studio do?
An AI product studio combines product strategy, interface design, model integration, and software engineering. Eonstar uses those disciplines to turn a specific user task into an application or an AI feature within an existing product.
Can Eonstar work on an existing product?
An existing product can be the starting point. Include its current workflow, technology, and the behavior you want to add in your project brief so the scope can be discussed around the product you already have.
What is the difference between an AI product and an AI agent?
An AI product is the complete experience a person uses. An agent is one possible system inside it: a workflow that can select tools or steps within defined boundaries. Eonstar also has a dedicated agentic systems practice.
What should I prepare before starting an AI application project?
A description of the users, one important task, examples of the desired output, the available data, and any existing product or prototype are useful starting points. Share known integration requirements and constraints through the contact form.
Start a project
Give the idea
a clear shape.
Tell us who the product serves, the task it should improve, the data it will use, and whether you have an existing prototype or codebase.
Send a project brief