Services
I offer
I collaborate with startups, labs, and teams to design, architect, and deploy intelligent solutions, from trained ML models to edge hardware prototypes that actually work in the field.
AI Systems & Applied Machine Learning
Designing, training, and deploying practical machine learning models tailored for real-world products and workflows.
- Custom classification and regression architectures using PyTorch and Scikit-Learn
- Transfer learning and fine-tuning convolutional networks and Vision Transformers
- Rigorous model evaluation, validation metrics, and confusion matrix profiling
- Decision intelligence ranking algorithms with explainable feature weights
Agentic AI & LLM Integration
Developing intelligent conversational agents, knowledge-grounded RAG pipelines, and prompt orchestration engines.
- Retrieval-Augmented Generation (RAG) referencing domain-specific documentation
- Prompt engineering and contextual reasoning pipelines with structured outputs
- Multi-agent task decomposition and asynchronous tool calling workflows
- FastAPI microservice endpoints connecting LLM reasoning to frontend apps
Computer Vision & Digital Forensics
Computer vision pipelines for object detection, produce sorting, explainable AI, and forensic image analysis.
- Edge object detection and classification using YOLOv8 and ResNet architectures
- Digital forensics feature extraction using Error Level Analysis (ELA) and DCT frequency analysis
- Explainable AI visualization using Grad-CAM attention heatmaps
- OpenCV image preprocessing, color segmentation, and background isolation
IoT Prototyping & Edge Hardware
End-to-end hardware prototypes connecting microcontrollers, sensor telemetry, and on-device edge inference.
- Raspberry Pi & Arduino Uno dual-architecture firmware and UART serial bridges
- Sensor integration (ultrasonic, PIR presence, MQ gas, DHT environmental sensors)
- Actuator and servo motor calibration for automated physical mechanisms
- Lightweight edge inference and MQTT cloud telemetry transmission
Custom Requirements
If your project spans multiple domains or needs a specialized architecture, like edge ML, custom training pipelines, or full-stack dashboards, let's figure it out together.
Book ConsultationFrequently Asked
Sneha specializes in computer vision pipelines (object detection, visual forensics, medical image triaging), context-aware AI copilots (AST parsing, token streaming, RAG), graph-augmented NLP (Neo4j, transformers), and edge AI hardware deployment. All solutions are built with production-grade frameworks like PyTorch, TensorFlow, FastAPI, and Next.js.
Yes. Sneha built DeepShield AI, a dual-domain visual forensics pipeline combining Vision Transformers (ViT-Base-16) with frequency-domain analysis (Error Level Analysis and Discrete Cosine Transform) and Grad-CAM explainability. It was evaluated on FaceForensics++ and DFDC benchmarks, with documented robustness analyses under social media compression.
Absolutely. Sneha engineers physical edge prototypes integrating Raspberry Pi and Arduino with optimized ML models. Her NeuraBin / GreenSort project (Top 6 / 160 at SustainX 2026) runs YOLOv8 on a Raspberry Pi 4 with Arduino Uno servo gate actuation, achieving 90 mAP across 4 waste streams at a 1.7s total cycle time with a ₹5,000 hardware budget.
Sneha is proficient in Python, Java, C/C++, TypeScript, JavaScript, and SQL/Cypher. For AI/ML: PyTorch, TensorFlow, Keras, Scikit-Learn, YOLOv8, and OpenCV. For web & APIs: Next.js 15, React, FastAPI, Flask, and Tailwind CSS. For databases: Neo4j, MongoDB, and MySQL. For embedded systems: Arduino, Raspberry Pi, and serial protocols.
Yes. Sneha is actively seeking AI/ML engineering and software engineering internships, research fellowships, and technical project collaborations. You can reach out directly via sneha.dpatel@outlook.com or through her contact page.
Sneha holds 5 verified credentials: AWS Academy Graduate (Machine Learning Foundations), Google Cloud Academy (GCP Data Engineering), Neo4j Certified Professional, IBM (Data Analysis with Python), and Cisco Networking Academy (IoT & Cybersecurity).