You will get Enterprise AI Tech Stack and Architecture Review

Shanto D.Status: Offline
Shanto D. Shanto D.
4.8
Top Rated

Let a pro handle the details

Buy Generative AI services from Shanto, priced and ready to go.
Shanto D.Status: Offline
Shanto D. Shanto D.
4.8
Top Rated

Let a pro handle the details

Buy Generative AI services from Shanto, priced and ready to go.

Project details

Most AI projects fail because of unscalable, insecure, or cost-prohibitive architectural decisions. If you are building a multi-agent system, a RAG pipeline, or an AI SaaS product, you need a definitive reality check from a Fractional CTO who actually ships production systems.

I will tear down your proposed or existing architecture, identify scaling bottlenecks, and map out a bulletproof execution plan. We will validate your vector databases, LLM routing, and cloud infrastructure to ensure your system is reliable, accurate, and economically viable at scale.

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→ Tech Stack Validation: A hard review of your chosen tools (Python, TypeScript, LangChain, Pinecone, AWS/GCP) to ensure they fit your specific enterprise needs.

→ Cost & Scaling Analysis: Identifying where token costs or compute latency will bottleneck your business.

→ Risk Assessment: Highlighting security, compliance, or hallucination risks in your current data flow.

→ The Architecture Blueprint: A comprehensive technical document detailing the exact architecture, database schemas, and multi-agent loops required to build your system correctly the first time.
AI Algorithms
AdaBoost, Convolutional Neural Network, Feedforward Neural Network, Generative Adversarial Network, Large Language Model, Long Short-Term Memory Network, Multilayer Perceptron, Multimodal Large Language Model, Recurrent Neural Network, Transformer Model
AI Applications
AI Chatbot, AI Content Creation, AI Mobile App Development, AI Text-to-Speech, AI-Generated Code, AIOps, Conversational AI, Natural Language Generation, Natural Language Understanding, Sentiment Analysis, Time Series Analysis, Time Series Forecasting
AI Development Language
Python
AI Tools
Azure OpenAI, GitHub Copilot, Hugging Face, Jasper AI, NVIDIA AI Platform, PyTorch, Replit, Streamlit, TensorFlow, Word2vec
AI Models
BLOOM, ChatGPT, DALL-E, GPT-3, GPT-4, GPT-Neo, LLaMA, Midjourney AI, Naive Bayes Classifier, OpenAI Codex, Stable Diffusion, Whisper
What's included
Service Tiers Starter
$1,999
Standard
$4,999
Advanced
$8,999
Delivery Time 4 days 7 days 15 days
Number of Revisions
333
AI Model Integration
Batch Normalization
Database Integration
Detailed Code Comments
Image Upscaling
MLOps
Model Deployment
Model Documentation
Model Monitoring
Model Testing & Optimization
Model Tuning
Natural Language Processing
NLP Tokenization
Pre-Training
Prompt Engineering
Setup File
Source Code
4.8
12 reviews
83% Complete
8% Complete
8% Complete
1% Complete
(0)
1% Complete
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PA

Paul-Miki A.
5.00
Jun 30, 2025
Build full-stack He is such an intelligent and efficient freelancer. He went above and beyond for the project and it always available to troubleshoot and fix issues. I will definitely hire him again.

SD

Sam D.
5.00
Mar 23, 2025
Senior Blockchain Developer for NFT Marketplace Shanto is serious, proactive and reliable. he is open to research and resolving challenges.

CB

Cooldige B.
5.00
Dec 15, 2024
30 minute consultation

SD

Sam D.
5.00
Oct 30, 2024
Senior Blockchain Developer for NFT Marketplace Thank you very much!!!

DH

Daniel H.
3.00
Sep 20, 2024
Build a React Native and TypeScript mobile app
Shanto D.Status: Offline

About Shanto

Shanto D.Status: Offline
Senior Solutions Architect | Production RAG/LLM, AI Governance, Claude
100% Job Success
4.8 Ā (12 reviews)
Dhaka, BangladeshĀ - 8:03 pm local time
I'm an AI solutions architect who builds production-grade AI agents for teams that can't afford a demo: agentic AI systems that run in production, scale across tenants, and survive a compliance review.

Most AI agents don't survive contact with a real workload or an audit. As an AI architect and agentic AI engineer, I design the multi-agent systems that do, for healthcare, fintech, pharma, legal, and other regulated environments where production reliability and HIPAA-grade data handling are not optional. This is enterprise AI architecture, not prototype work.


WHAT I BUILD

ā–» Production AI agents & agentic workflows: multi-agent systems and AI agent orchestration with LangGraph, LangChain, CrewAI, AutoGen, and MCP. Human-in-the-loop oversight, not autonomous black boxes.

ā–» Production RAG & semantic search: RAG pipelines, LLM integration, vector search, and hybrid retrieval tuned for accuracy under real production traffic. Document intelligence, knowledge bases, and knowledge-graph retrieval that actually returns the right answer.

ā–» Enterprise AI architecture & governance: AI architecture, AI governance, HIPAA and SOC 2 compliance, and auditability designed in from day one. AI compliance and security treated as design constraints, not retrofits.

ā–» Conversational & voice AI: AI chatbots, conversational AI, RAG chatbots, customer-support assistants, and voice AI agents wired into your real systems and data.

ā–» AI automation & integration: AI workflow automation, business process automation, and API integration across your stack, from OpenAI and Claude (Anthropic) to your internal tools.


INDUSTRIES

Ā» Healthcare and digital health (HIPAA)
Ā» Fintech and financial services
Ā» Pharma and life sciences
Ā» Legal and insurance
Ā» Regulated environments where AI has to pass audit.


RECENT ENTERPRISE DELIVERIES

ā˜… Built a compliant AI agent pipeline for a pharma client: automated 90% of manual review with full regulatory auditability architected in from day one.

ā˜… Designed a multi-agent system for a fintech client: cut review processing time on a pipeline handling complex financial data at scale.


A GOOD FIT IF YOU NEED

āœ“ A HIPAA-compliant AI agent or healthcare AI platform that passes audit
āœ“ A production RAG chatbot or document-intelligence system trained on your own data
āœ“ A multi-agent system to automate a complex, high-stakes workflow
āœ“ An AI SaaS taken from MVP to a multi-tenant, audit-ready production system
āœ“ A fractional AI CTO or AI architecture review before decisions get expensive


HOW I ENGAGE

āž” Fractional AI CTO & technical advisor: strategy plus build from one partner.

āž” Enterprise AI architecture review: find the problems before they reach production.

āž” AI MVP to production: take an AI prototype to a scalable, multi-tenant, compliant system.


STACK

LangGraph, LangChain, CrewAI, AutoGen, MCP, production RAG, vector search (Pinecone, Qdrant, pgvector), semantic & hybrid retrieval Ā· OpenAI, Claude / Anthropic, Open-weight models, AWS Bedrock, GCP Vertex AI, Python, TypeScript, FastAPI, PostgreSQL, encryption at rest and in transit, prompt-injection defense, row-level security, multi-tenant isolation.

100% Job Success Ā· Top Rated Ā· CEO, ExecuteML LLC Ā· Kellogg (Northwestern) High-Performance Collaboration certified.

The bottleneck in enterprise AI isn't the model: it's finding an AI architect who treats production reliability, AI governance, HIPAA, and SOC 2 as design constraints rather than obstacles. That's been my operating environment on every agentic AI engagement, across healthcare and fintech.

If you're building production AI agents, agentic AI, or a HIPAA or fintech AI platform that has to work inside a regulated environment, message me. On the first call I'll tell you whether your current AI architecture will cause problems downstream.

Steps for completing your project

After purchasing the project, send requirements so Shanto can start the project.

Delivery time starts when Shanto receives requirements from you.

Shanto works on your project following the steps below.

Revisions may occur after the delivery date.

Discovery & Document Review

I will review your provided PRDs, existing codebase, and architecture diagrams (Miro, Lucidchart) to map out your current technical baseline.

Stakeholder Strategy Session

We will hold a deep-dive call to align your technical architecture with your business goals, expected user scale, and budget constraints.

Review the work, release payment, and leave feedback to Shanto.