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AI/ML & Generative AI Development
I build practical AI and machine learning solutions using Python, FastAPI, LLMs, RAG, and modern AI technologies. I focus on creating scalable, reliable, and real-world solutions that help businesses automate processes and turn ideas into intelligent products.
@Md jahid Alam FastAPI and RAG are a practical pairing for production AI systems. How are you handling retrieval evaluation and monitoring as those workflows scale?
Great question! I’m approaching it with a mix of retrieval metrics, LLM-based evaluation, and production monitoring for latency, relevance, and failure cases. The goal is to continuously identify retrieval gaps and improve the RAG pipeline as usage scales.
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Partnero AI took 3rd place in the Flowstep Challenge!
It's going to be published to the App Store soon! I'll make an announcement here.
I handle full-cycle Design & Development, delivering apps and websites in under 4 weeks.
Take a look at this case study and write me a message to discuss your idea!
Outstanding result and a solid case study! Turning ideas into live products in such a short timeframe is top-tier work.
Looking forward to the official launch!
Before adding another feature to a half-built AI product, run one core journey through four checks:1. Flow: can a new user finish without explanation?2. Evidence: can you prove the path works, not just demo it once?3. Resilience: do loading, empty, error, and retry states keep trust?4. Release: are the acceptance criteria and go/no-go decision explicit?If one fails, “more AI” usually isn’t the next move—the bottleneck is release readiness. I built this scorecard to scope one fixable journey into a seven-day diagnostic.
I’m currently building a RAG system for an e-commerce company, basically giving an AI assistant access to the company’s own knowledge and product information so it can give useful, context-aware responses instead of just generating random answers.
The interesting part isn’t just connecting an LLM.
It’s making sure the AI can:
→ Find the right information
→ Understand the user’s question
→ Retrieve relevant context
→ Give an accurate response
→ Actually be useful in a real business workflow
Still working on it, but I’m excited about where it’s going.
This is the kind of AI automation I enjoy building, systems that solve actual business problems, not just AI demos.
Building something similar? Let’s talk.
