AI application development

Build AI features your team can use

I connect LLMs to applications and workflows with Python, APIs, and interfaces for reviewing the output. I can help you take an AI feature from its first integration to a tested workflow.

From an AI idea to working software

LLM API integrations

Connect OpenAI or Gemini to an existing product or a new application. Define the inputs, prompts, and structured outputs the next step needs.

Prompt management and evaluation

Organise prompts, keep versions, and run evaluation jobs against agreed examples so your team can compare changes.

Application integration

Build FastAPI or Flask endpoints, background jobs, input validation, and a review step for AI-generated output.

Related project work

PromptVault demonstrates prompt operations and background evaluation jobs. AutoTube connects AI-assisted scripting and narration to a desktop video workflow.

  1. Prompt operations API

    PromptVault

    Production-style lifecycle management for prompts, tests, and evaluations.

    • FastAPI
    • PostgreSQL
    • Redis
    • Docker
  2. AI automation desktop app

    AutoTube

    YouTube automation software for AI-assisted scripts, video assembly, and publishing Shorts from one desktop workflow.

    • Python
    • FFmpeg
    • YouTube API
    • AI automation

Define the feature before choosing the model

We’ll agree on what the feature needs to do, the data it can use, and how we’ll review its output. That gives us concrete examples for testing quality, response time, and API cost.

If the work also involves connecting business tools, explore my workflow automation services.

Let's discuss the work.

Share the problem, existing tools, and the result you need. I can discuss implementation scope, technical tradeoffs, and relevant project work.