What Global Engineering Leaders Say About Rohit

"Rohit transformed our manual document workflows into an autonomous multi-agent pipeline using LangGraph. His deep expertise in agent state reflection and tool routing reduced our operational latency by 85%. Truly an elite AI consultant."

"We had severe hallucination issues in our medical Q&A software. Rohit designed a hybrid Qdrant + BM25 RAG pipeline with Cohere reranking that achieved 99.4% retrieval accuracy. Exceptional knowledge of production LLM infrastructure!"

"Rohit's 2-week Agentic Sprint delivered a working proof-of-concept faster than our internal team thought possible. His practical approach to CrewAI and API guardrails saved us months of trial and error."

"Working with Rohit directly without intermediate account managers was a breath of fresh air. His background in PyTorch and time-series forecasting allowed us to launch our anomaly detection engine on schedule."

"Rohit helped us set up a private GPU cluster running vLLM for open-weight 70B models. Inference cost dropped by 62% compared to OpenAI API calls while keeping our proprietary code strictly on-premise."

"If you want to build autonomous multi-agent systems that actually run reliably in production, Rohit is the expert you need. Clear communication, crisp architecture, and outstanding ROI."

"Rohit's real-time streaming PyTorch fraud detection autoencoder processed 1,000,000+ Kafka transaction events per second under 140ms. His deep understanding of low-latency MLOps is unmatched."

"Rohit built our zero-retention BioBERT clinical search engine querying 4.5M PubMed trial papers in sub-82ms. His adherence to strict HIPAA privacy standards gave our board complete confidence."

"Rohit's PyTorch LSTM and XGBoost hybrid demand forecasting engine improved our SKU forecast precision to 94.2%, cutting our warehouse inventory holding costs by 34%."

"Our Zendesk support queue ticket backlog evaporated after Rohit deployed an autonomous AutoGen support agent crew. Auto-resolution jumped to 74% with a 2.4-minute resolution time."

"Rohit's CTGAN differential privacy tabular generator allowed our research consortium to train ML models on synthetic data with 100% HIPAA compliance while preserving 98.6% model accuracy."

"Rohit provided strategic AI advisory for our portfolio companies. His clear framework for evaluating open-weight model serving vs cloud APIs targeted a <90-day payback period."