AI Help For Your Business

I help businesses save time and solve problems using AI.

I build simple, working AI tools that take over the slow, repeated tasks eating up your day — so you and your team can spend that time actually solving problems.

MSc in Artificial Intelligence, Cardiff University · 4+ years of experience

Bhanu Prakash Adireddy, AI Engineer and founder of VirtueAI
BHANU PRAKASH ADIREDDY, AI ENGINEER
83.8% Exact-match accuracy
Spider 1.0 benchmark
50K+ Monthly active users
served in production
<120ms p95 latency
at production scale
+23% Click-through lift
confirmed by A/B test

What I Do

Six things I get called in for

I start with your problem, not with the technology.

AGT

LLM & Agentic AI Systems

Multi-agent platforms built with LangGraph that route natural-language requests to the right specialist agent — RAG, SQL, or task automation — turning manual lookups that took minutes into answers in seconds.

RAG

RAG & Intelligent Search

Production retrieval pipelines using hybrid search (BM25 + pgvector embeddings) with reranking — evaluated with RAGAS so retrieval quality is measured, not assumed.

REC

Recommendation Systems

Hybrid collaborative + content-based recommendation engines served through low-latency FastAPI and Redis architectures, validated with structured A/B tests before rollout.

RT

Real-Time AI Applications

WebSocket, token-streaming assistants with confidence-based escalation to a human — backed by Kafka pipelines processing thousands of events per minute.

OPS

Cloud Infrastructure & MLOps

Deployments across AWS and GCP with Docker, Kubernetes, and Terraform — backed by CI/CD pipelines with automated evaluation gates, so a regressed model never reaches production.

BI

Data Analytics & Decision Support

Analysis and dashboards (SQL, Power BI, Tableau) that turn operational data into the specific intervention that moves the metric you actually care about.

My Work

Recent projects

A few examples of what I've built — with the real results, not just marketing talk.

CASE 01 REF: SPIDER-1.0

Text-to-SQL Agent with Automated Query Repair

A six-layer Text-to-SQL architecture — input processing, prompt engineering, LLM generation, execution, validation/repair, and output generation — with an iterative, execution-driven repair loop. Improved on the no-repair baseline by 20.8 percentage points across 1,034 questions and 20 databases, beating the referenced STRUG result.

LangGraphGPT-4oQuery repair
83.8% exact-match accuracy View source →
CASE 02 REF: GEMINI-API

LLM Guardrails

A FastAPI service wrapping Google's Gemini API with input screening for prompt injection and jailbreak patterns, plus output validation to catch unsafe, empty, or leaked-secret content — with structured allow/block decisions and category codes.

FastAPIGemini APISafety layer
3-stage input/output/model checks View source →
CASE 03 REF: A/B-4WK-10%

Hybrid Recommendation Engine

Collaborative + content-based filtering serving 50,000+ monthly active users at p95 latency below 120ms. Validated with a structured four-week, 10% holdout A/B test, then deployed on Kubernetes with Terraform-managed infrastructure and CI/CD evaluation gates.

FastAPIRedisKubernetes
+23% / +11% CTR / conversion lift
CASE 04 REF: NHS-DNA

NHS Wales — Patient No-Show Analysis

Analysed 5,000+ diabetes clinic appointment records to identify the key drivers of missed appointments — age, rurality, deprivation, and appointment type — and built Power BI dashboards that shaped a targeted SMS-reminder intervention.

Power BISQLHealthcare
14% → 6% target DNA rate

Method

Five steps, no black box

01

Discover

Understand the workflow, the data, and the actual business metric we're trying to move.

02

Design

Architect the simplest system that solves the problem — not the trendiest one.

03

Build

Ship working software in short, visible iterations you can react to early.

04

Deploy

Production infrastructure with CI/CD, monitoring, and evaluation gates from day one.

05

Support

Iterate against real usage data after launch — not assumptions from before it.

Get started

Two ways to start the conversation

My clients use AI to automate the everyday work in their business — answering questions, finding information, handling repeat tasks — so their team can spend time on bigger things. Book fifteen minutes, or just submit your problem below: I read every message myself, and I'll get back to you with a solution within one business day.

Book a call

Fifteen minutes, no obligation. I'll tell you honestly whether AI is the right fix for what you're dealing with.

Book a call Or call directly: +44 7741 012603

Submit your problem

Tell me what's slow, manual, or eating up your team's time — I'll get back to you with how AI can fix it.

Bhanu Prakash Adireddy

About

Bhanu Prakash Adireddy

I'm an AI engineer based in the UK with 4+ years building production AI and machine learning systems — from LLM-powered agents to recommendation engines serving tens of thousands of users. I hold an MSc in Artificial Intelligence from Cardiff University, where my research on LLM-powered Text-to-SQL systems and automated query repair achieved 83.8% exact-match accuracy on the Spider 1.0 benchmark.

Through VirtueAI, I work directly with businesses to design, build, and deploy AI systems that solve a specific operational problem — not proofs of concept that never make it past a demo.

Education
MSc Artificial Intelligence, Cardiff University (2024–2025)
Certifications
Model Context Protocol · Claude with Google Cloud's Vertex AI
Core stack
Python, LangGraph, FastAPI, PostgreSQL/pgvector, Kafka, AWS, GCP, Kubernetes

Direct contact

Prefer to reach out directly?

Email, call, or find the work itself — whichever's easiest.

Email
adireddybhanudatascience@gmail.com
Phone
+44 7741 012603
GitHub
github.com/adireddybhanu
LinkedIn
linkedin.com/in/adireddybhanu