You will get a AI lead nurture pipeline
Top Rated
Project details
You will get an end-to-end automation workflow to improve and handle your lead pipeline. This project workflow is universal and can be applied to variety of businesses including real estate, marketing, retail, SaaS products and so on.
AI Algorithms
Convolutional Neural Network, Generative Adversarial Network, Large Language Model, Long Short-Term Memory Network, Multilayer Perceptron, Multimodal Large Language Model, Recurrent Neural Network, Regression AnalysisAI Applications
AI Text-to-Speech, AIOps, Conversational AI, Image Analysis, Image Processing, Image Recognition, Natural Language Generation, Object DetectionAI Development Language
PythonAI Tools
Azure OpenAI, GitHub Copilot, Hugging Face, Jasper AI, PyTorch, Replit, TensorFlowAI Models
BERT, ChatGPT, DALL-E, GPT-4, Jurassic-2, LaMDA, LLaMA, Midjourney AI, Stable Diffusion, WhisperWhat's included $5,000
These options are included with the project scope.
$5,000
- Delivery Time 7 days
- AI Model Integration
- Database Integration
- Detailed Code Comments
- Model Deployment
- Model Documentation
- Model Monitoring
- Model Testing & Optimization
- Model Tuning
- Natural Language Processing
- NLP Tokenization
- Pre-Training
- Prompt Engineering
- Setup File
- Source Code
38 reviews
(34)
(2)
(1)
(0)
(1)
This project doesn't have any reviews.
RC
Ryan C.
May 13, 2026
Marketing Data Engineer (Shopify, GA4, Meta APIs) – Build Performance Dashboard
Kapil successfully implemented the initial data layer for our dashboard project, but we have changed the scope and direction for our needs on this project. We appreciate his work in getting us to this point.
VD
Valli D.
Feb 6, 2026
Data Analytics Implementation Specialist Needed
BS
Brian S.
Dec 15, 2025
Data Integration & Dashboard Engineer
Our needs changed on this so this was a much shorter engagement than expected but I do hope and anticipate to work with Kapil again. He knows his stuff and is a great communicator.
JH
Joseph H.
Dec 15, 2025
Data Processing for Master Salon List Creation
Kapil was extremely timely and communicative with all tasks and updates. Very professional.
JJ
Jack J.
Dec 12, 2025
API Expert – Python, FastAPI, Redis, PostgreSQL
Kapil did a great Job and we will hire again for new project that starts tomorrow... He is The Best!
About kapil
Senior Data & AI Engineer | Production Data Pipelines, LLM/RAG Systems
94%
Job Success
Indore, India - 6:35 am local time
Most of my data engineering work is end to end. I take a messy data problem, or an AI feature that "almost works," and turn it into something reliable that runs in production without someone babysitting it. After 15+ years as a data engineer, you learn the hard part is rarely the model or the framework. It's the data, the edge cases, the pipelines, and keeping the system maintainable once you've handed it over.
As an AI engineer I treat LLM and RAG work the same way: take a prototype that almost holds together and make it a production AI system that survives real traffic, real users, and real data.
Recent data engineering and AI engineering projects:
- An AI inbound phone system built on Twilio with OpenAI Whisper and GPT-4, handling real-time voice intake and call routing.
- Enterprise Power BI data models for healthcare and financial reporting, around 30 tables and 40+ DAX measures, including IFRS 9 staging, RAROC, and NIM trends.
- HL7 FHIR R4 integrations with Epic, Cerner, and Athenahealth for a clinical AI platform.
- Cut LLM inference cost on a high-volume voice product by 25% by reworking how it used the OpenAI Realtime API and its per-turn token replay.
Data engineering: Apache Spark, PySpark, dbt, Apache Airflow, ETL and ELT pipelines, data warehousing, data modeling, Snowflake, BigQuery, Redshift, Databricks, Delta Lake, Kafka, Kinesis, Fivetran.
AI engineering and machine learning: OpenAI GPT-4o, Claude, Gemini, LangChain, LlamaIndex, RAG pipelines, AI agents, prompt engineering, vector search (Pinecone, Weaviate, pgvector), PyTorch, TensorFlow, scikit-learn, MLflow, model deployment.
Cloud and DevOps: AWS (Glue, EMR, Lambda, Redshift, SageMaker, Athena), GCP (BigQuery, Dataflow, Vertex AI), Azure (Synapse, Data Factory, Azure ML), Terraform, Docker, Kubernetes, GitHub Actions.
Automation and integration: n8n, Make, Power Automate, REST and GraphQL APIs.
Governance and compliance: GDPR, HIPAA, SOC 2, RBAC, PII masking, encryption, data lineage.
Languages: Python, SQL, Scala, PySpark, FastAPI, Flask.
How I work: I'd rather ask the right questions up front than build the wrong thing quickly. I'll tell you when something is a bad idea, give you timelines I can keep, and leave you with code and documentation your own team can maintain. I've delivered data engineering and AI engineering projects for startups and enterprises across the US, Europe, and Asia.
If you're looking to hire a data engineer or AI engineer who can own the work end to end, from raw data pipeline to production AI system, I'm available now. Tell me what you're building and I'll give you a straight answer on how I'd approach it.
Steps for completing your project
After purchasing the project, send requirements so kapil can start the project.
Delivery time starts when kapil receives requirements from you.
kapil works on your project following the steps below.
Revisions may occur after the delivery date.
Requirements discussion and align on the expectations
If during the detailed discussion of requirements, anything changes in the timeline and budget due to additional requests or features, I will provide updated estimates and timeline.