Multi-Project AI Agent Setup

I have several ongoing initiatives that each require their own AI agent—some conversational, others focused on data extraction or decision support. I need someone who can take an idea, choose an appropriate framework (for example, Python with LangChain or Rasa for chat, TensorFlow or PyTorch for analysis-heavy tasks), and turn that into a production-ready microservice or packaged module.

Typical flow
• Review the project brief with me and translate objectives into agent capabilities
• Propose the tech stack and model choice, clearly explaining trade-offs
• Build, test, and fine-tune the agent, then expose it through a clean API or SDK
• Hand over clear documentation and lightweight maintenance scripts (Docker or similar)

Because each project differs, modular architecture and well-commented code are essential so I can extend or swap components later. Quality is measured by unit tests that hit at least 85 % coverage, latency below 500 ms for inference on standard cloud hardware, and reproducible results via a provided requirements.txt or environment.yaml file.

If this sounds like your wheelhouse, let’s discuss the first agent and establish a repeatable pattern for the rest.