You will get a production readiness review of your AI agent, RAG, or LLM system
Project details
The demo works. That is not the question. The question is what happens on run number four thousand, when a tool times out, the context fills up, and a user types something nobody planned for.
I am an AWS AI Hero and hold the AWS Certified Generative AI Developer Professional certification. At Aivilo I built Strands and LangChain agents and designed the platform side of running them: AI trace capture, evaluations, prompt management, agent runs, tool traces, and agent policies. At MechanizedAI I architect GenAI systems on Bedrock and Azure OpenAI with Step Functions, Lambda, and ECS. I have spoken on deploying GenAI agents in production at the AWS Summit.
I read the prompts, tool definitions, retrieval, memory, and control flow, then push the system with adversarial inputs, failed tool calls, and long context. You get findings ranked three ways: what will break, what will cost more than you expect, and what will drift without anyone noticing.
Every finding names the file and the change. The report is written for whoever has to implement it, not for a slide.
Availability is under 30 hrs/week.
I am an AWS AI Hero and hold the AWS Certified Generative AI Developer Professional certification. At Aivilo I built Strands and LangChain agents and designed the platform side of running them: AI trace capture, evaluations, prompt management, agent runs, tool traces, and agent policies. At MechanizedAI I architect GenAI systems on Bedrock and Azure OpenAI with Step Functions, Lambda, and ECS. I have spoken on deploying GenAI agents in production at the AWS Summit.
I read the prompts, tool definitions, retrieval, memory, and control flow, then push the system with adversarial inputs, failed tool calls, and long context. You get findings ranked three ways: what will break, what will cost more than you expect, and what will drift without anyone noticing.
Every finding names the file and the change. The report is written for whoever has to implement it, not for a slide.
Availability is under 30 hrs/week.
AI Algorithms
Large Language Model, Multimodal Large Language ModelAI Applications
AIOps, Conversational AI, Natural Language UnderstandingAI Development Language
PythonAI Tools
Azure OpenAI, Hugging FaceAI Models
GPT-4What's included
| Service Tiers |
Starter
$600
|
Standard
$1,500
|
Advanced
$3,000
|
|---|---|---|---|
| Delivery Time | 5 days | 9 days | 14 days |
Number of Revisions | 1 | 1 | 2 |
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 | - | - | - |
Frequently asked questions
About Matias
Fractional CTO | Cloud Architect | AWS AI Hero | GenAI | DevOps
100%
Job Success
Ciudad de Buenos Aires, Argentina - 9:03 pm local time
I am a member of the AWS AI Engineering Community Builders program and have been a multi-time finalist in the AWS DeepRacer competition. These experiences have deepened my understanding of AWS technologies and reinforced my passion for machine learning.
Certifications
I hold several valuable certifications that validate my technical proficiency and expertise:
AWS Solution Architect Professional
AWS Machine Learning Speciality
AWS Machine Learning Engineer Associate
AWS AI Practitioner
AWS Cloud Practitioner
AWS Solution Architect Associate
Red Hat Certified Engineer, along with four more certifications
With a comprehensive skill set that includes development, infrastructure, and artificial intelligence technologies, a strong background in leading global distributed teams, and a track record of success, I drive innovative solutions and deliver results in a dynamic, fast-paced tech landscape.
Steps for completing your project
After purchasing the project, send requirements so Matias can start the project.
Delivery time starts when Matias receives requirements from you.
Matias works on your project following the steps below.
Revisions may occur after the delivery date.
Read the system and run it against hard cases
Prompts, tool definitions, retrieval, memory, and control flow. Then I push it: adversarial inputs, tool failures, long context, and the edge cases your demo never hits.
Findings, costs, and what to fix first
Ranked: will break, will cost more than you think, will drift quietly. Each with the file and the change. Plus cost per run today and where it goes as you scale.