Portrait of Fredrick Alli

Hi, I'm Fredrick Alli

An AI Engineer, Data Scientist & Data Engineer specialising in GenAI/RAG systems, LLM agents, machine learning, and cloud-native data engineering. I help organisations turn raw data and language models into production-ready, actionable systems.

View Some of My Work

Professional Summary

I lead FA Grace Consulting Ltd., a London-based technology consultancy specialising in AI Engineering, Data Science, and Data Engineering. Over the past 5+ years, I've designed & deployed high-performance data platforms, built GenAI/RAG systems and predictive ML models, and automated CI/CD pipelines for clients in finance, healthcare, smart-city, and construction logistics sectors.

My Story

Early on I discovered that data isn't just numbers, it's the heartbeat of modern business. I dove deep into ETL pipelines and real-time analytics, then expanded into LLM agents, RAG systems, and cloud architectures to deliver end-to-end solutions. Today, I love architecting systems that run reliably at scale and uncovering insights that drive real impact.

Whether I'm building a RAG pipeline over clinical or regulatory documents, training a computer vision model for MRI classification, or automating deployments with Terraform and Kubernetes, my goal is the same: empower teams with robust, maintainable AI and data platforms.

Core Services

  • AI Engineering & GenAI

    Design and build multi-agent LLM systems for regulated domains (insurance claims triage, healthcare prior-auth, fintech AML scoring), combining LLM reasoning with deterministic fallback logic. Build RAG pipelines end to end: document ingestion and chunking, SBERT/Sentence-Transformer embeddings, FAISS and Pinecone vector search, and FastAPI services with test coverage.

  • Voice AI

    Text-to-speech and speech recognition pipelines, and conversational voice agents that combine ASR, LLM reasoning, and TTS into a single voice-driven interface.

  • NLP & Language Models

    Fine-tune transformer models (BiomedBERT, BioBERT, ModernBERT) for classification, multiclass subject tagging, and named entity recognition (GLiNER). Build semantic search and RAG evaluation pipelines over hundreds of thousands of samples, served through FastAPI and Django, with everything running on local HuggingFace models, no external API dependency.

  • Computer Vision & Health AI

    Train and deploy CNNs (EfficientNetB0, ResNet18) for medical image classification, including a 4-class brain tumor MRI classifier at ~97.8% test accuracy and a multi-label chest X-ray disease classifier with Grad-CAM interpretability. Also build tabular clinical models (Random Forest, Logistic Regression, XGBoost) for disease-risk prediction such as heart attack likelihood.

  • Data Engineering

    Build medallion-architecture pipelines (bronze, silver, gold) with dimensional modelling (dim/fact tables) on Databricks, Microsoft Fabric OneLake, and Snowflake, using PySpark, Delta Lake, dbt, and Azure Data Factory to turn raw data into business-ready metrics.

  • Cloud & DevOps

    AWS, Azure Synapse, and GCP infrastructure provisioned with Terraform, containerised with Docker and Kubernetes, and deployed through CI/CD pipelines with automated testing and container builds.

  • Business Intelligence

    Power BI dashboards with DAX and Power Query, plus Tableau and Dash, for real-time business metrics and decision support.

Outside of Work

When I'm not architecting data platforms, you'll find me:

  • Hiking & exploring the UK countryside
  • Playing football or swimming laps
  • Experimenting with new recipes
  • Reading sci-fi novels with my family

Let's Talk!

Interested in an AI or data-driven transformation? Get in Touch