You will get a senior AI system audit with a prioritized fix-it action plan
Rising Talent
Project details
Most AI systems don't fail on the model they fail on the boring parts: retrieval that returns the wrong thing, prompts with no guardrails, hallucinations no one tested for, and cost or latency that balloons at scale. In this audit I review your AI system end to end data flow, prompts, retrieval, guardrails, and evaluation and hand you a written report you keep no matter what: the highest-risk failure points, what's driving cost or latency, and a prioritized, effort-estimated plan to fix them. It's the same reliability discipline I used to ship a RAG assistant at 95% accuracy for ~500 daily users and a HIPAA-compliant clinical AI in production. You leave knowing exactly what's wrong and what to do next whether or not we build it together.
AI Development Type
Deep Learning, Model TuningWhat's included
| Service Tiers |
Starter
$750
|
Standard
$1,500
|
Advanced
$2,750
|
|---|---|---|---|
| Delivery Time | 3 days | 5 days | 7 days |
Number of Revisions | 1 | 2 | 2 |
AI Model Integration | - | - | - |
Detailed Code Comments | - | - | - |
Knowledge Graph | - | - | - |
Model Documentation | - | - | - |
Ontology | - | - | - |
Source Code | - | - | - |
Taxonomy | - | - | - |
Frequently asked questions
1 review
(1)
(0)
(0)
(0)
(0)
This project doesn't have any reviews.
CH
Christopher H.
Aug 11, 2026
AI Workflow & No-Code Systems Architect - Exit Planning Advisory Platform
Khurem delivered a detailed, well-organized comparative analysis of two competing architectural designs for me as an unbiased third party. Khurem was on schedule with his deliverable, detailed in his response, and provided great value for me.
About Khurem
AI/LLM Engineer | Production RAG, AI Agents & HIPAA-Ready GenAI
Lewisville, United States - 1:55 am local time
If your AI is hallucinating, retrieving the wrong information, responding too slowly, becoming expensive at scale, or remaining stuck in prototype mode, I can help you make it production-ready.
Most AI projects don’t fail because of the model. They fail because of unreliable data, weak retrieval, missing evaluation, uncontrolled hallucinations, poor latency, and costs that increase unexpectedly at scale.
Over the past six years across Upwork and off-platform product engagements I’ve helped 30+ teams turn AI concepts into systems used in real operational environments.
SELECTED RESULTS
→ Built a RAG assistant across a 10,000+ document knowledge base, achieving 95%+ evaluated answer accuracy and supporting approximately 500 daily users.
→ Delivered a clinical documentation product that reduced documentation time by up to 70% and improved transcription accuracy by 30%.
→ Developed and tested computer-vision models for real-time unsafe-driving detection, including the evaluation and monitoring needed for production use.
WHAT I CAN HELP YOU WITH
→ Production RAG systems
→ LLM applications, copilots and customer-facing assistants
→ AI agents with tools, memory, validation and human review
→ Retrieval evaluation and hallucination testing
→ Hybrid search, reranking and vector database architecture
→ AI workflow automation and API integrations
→ Healthcare and privacy-sensitive AI applications
→ Rescue and stabilization of incomplete AI products
→ AI performance, latency and token-cost optimization
→ Production deployment, monitoring and maintenance
MY RELIABILITY PROCESS
1. Audit
I examine your data, users, current architecture, failure cases and success criteria before recommending a solution.
2. Ground
I design retrieval, prompts, permissions, validation and guardrails so responses remain connected to trusted information.
3. Evaluate
I build repeatable tests for retrieval quality, answer accuracy, hallucinations, edge cases, latency and cost.
4. Deploy
I implement monitoring, fallbacks, access controls and production safeguards so the system continues performing after launch.
CORE TECHNOLOGIES
Python · OpenAI · Anthropic · LangChain · LlamaIndex · FastAPI · PostgreSQL · pgvector · Pinecone · Weaviate · Chroma · Redis · Docker · AWS · GCP · Azure
A GOOD FIT IF YOU:
→ Need to take an AI prototype into production
→ Have a RAG system producing inaccurate answers
→ Need an AI agent that can safely perform multi-step work
→ Want to reduce LLM latency or operating cost
→ Need an independent technical assessment before investing further
→ Have inherited a partially completed AI application that needs rescuing
Not ready for a complete build? We can begin with a fixed-scope AI Reliability and Architecture Audit.
Send me a short description of what you are building or what is currently failing and I’ll respond with the first technical questions I would investigate.
Steps for completing your project
After purchasing the project, send requirements so Khurem can start the project.
Delivery time starts when Khurem receives requirements from you.
Khurem works on your project following the steps below.
Revisions may occur after the delivery date.
.
Client purchases the project and shares system access, prompts, and where it's breaking.
.
I audit the data flow, prompts, retrieval, guardrails, and evaluation, and map the failure points.