You will get a Private AI Chatbot trained on your docs (RAG + guardrails)
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Project details
I will build a Retrieval-Augmented Generation (RAG) chatbot that answers questions based on your approved documents and webpages, with clear guardrails for safety and consistency. The goal is a practical assistant that your team (or customers) can use immediately, without turning into a large custom software project.
What you’ll receive (varies by tier):
• RAG assistant deployed on the best-fit stack for your constraints (AnythingLLM, n8n workflow approach, or AWS Bedrock if you already operate in AWS)
• Document ingestion per tier limits (PDF/Docs/URLs)
• “Source-grounded” behavior with citations where available and strong “I don’t know” guardrails
• Basic admin setup + runbook (how to add/update sources, test, and maintain)
• Advanced tier: one-way webhook/API handoff to one destination (CRM/ticket/email/Sheet)
Scope boundaries (to keep it reliable):
• No “unlimited” sources: each tier has caps on number of sources/pages
• No deep two-way CRM synchronization or complex business logic integrations
• No custom analytics dashboard
• No guarantee of ticket reduction or perfect accuracy; I deliver testing + guardrails and you approve final content
What you’ll receive (varies by tier):
• RAG assistant deployed on the best-fit stack for your constraints (AnythingLLM, n8n workflow approach, or AWS Bedrock if you already operate in AWS)
• Document ingestion per tier limits (PDF/Docs/URLs)
• “Source-grounded” behavior with citations where available and strong “I don’t know” guardrails
• Basic admin setup + runbook (how to add/update sources, test, and maintain)
• Advanced tier: one-way webhook/API handoff to one destination (CRM/ticket/email/Sheet)
Scope boundaries (to keep it reliable):
• No “unlimited” sources: each tier has caps on number of sources/pages
• No deep two-way CRM synchronization or complex business logic integrations
• No custom analytics dashboard
• No guarantee of ticket reduction or perfect accuracy; I deliver testing + guardrails and you approve final content
AI Algorithms
Large Language Model, Multimodal Large Language ModelAI Applications
AI Chatbot, AI Content Creation, AI Mobile App Development, AI-Enhanced Classification, AIOps, Conversational AI, Natural Language GenerationAI Development Language
PythonAI Tools
Azure OpenAI, Gradio, Hugging Face, Replit, Streamlit, Word2vecAI Models
ChatGPT, GPT-4, LaMDA, LLaMA, Midjourney AI, OpenAI Codex, Stable Diffusion, WhisperWhat's included
| Service Tiers |
Starter
$700
|
Standard
$1,300
|
Advanced
$2,200
|
|---|---|---|---|
| Delivery Time | 7 days | 12 days | 20 days |
Number of Revisions | 1 | 2 | 5 |
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 | - | - | - |
Optional add-ons
You can add these on the next page.
Additional Revision
+$30
Additional documents (per 50 documents)
(+ 2 Days)
+$100
Additional training session
(+ 2 Days)
+$100
Basic data cleaning
(+ 7 Days)
+$300Frequently asked questions
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About Danilo
AI Systems Architect | Cloud, Automation & Technical PM.
100%
Job Success
Miami, United States - 6:03 am local time
I help companies move from AI curiosity to real business impact, by selecting the right models, designing practical use cases, and delivering production-ready solutions.
I turn product vision into secure, scalable AI systems, and organizational chaos into structured, measurable execution.
🏆 Expert-Vetted by Upwork | ☁️ AWS-certified | 🎓 Master’s in Engineering Management | 🚀 10+ years delivering cloud and AI systems
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🔍 What I bring
🧠 AI Strategy & LLM Evaluation
I evaluate and benchmark LLMs (Claude, ChatGPT, Gemini, and open-source models like Kimi, MiniMax) based on cost, performance, and real business use cases.
I help teams select the right model and architecture — not just the most popular one.
🏢 AI Adoption & Team Enablement
I set up and operationalize tools like Claude for Teams / ChatGPT Enterprise, including plugins, connectors, and MCP-based workflows.
Focus: real adoption, governance, and measurable productivity gains across teams.
⚙️ AI Pilots & Business Use Cases
I design and deliver targeted AI pilots (2–6 weeks) for specific business functions:
– Sales automation
– Internal knowledge assistants (RAG)
– Document processing
– Workflow automation
Using official APIs (OpenAI, Anthropic, Google) or OpenRouter when flexibility is needed.
🤖 AI/LLM Engineering & MLOps
Hands-on with RAG systems, fine-tuning, inference pipelines, and observability.
Stack includes: Bedrock, SageMaker, Vertex AI, LangChain, LangGraph, vector DBs.
☁️ Cloud & Infrastructure
Production deployments on AWS and GCP: IAM, VPCs, CI/CD, serverless, containers, monitoring, secure data pipelines.
📊 Product & Delivery Leadership
I own delivery end-to-end: clear scope, timelines, stakeholder alignment, and predictable execution.
No scope creep. No black-box development.
🔄 Automation & Tooling
n8n, workflow orchestration, API integrations, AI-assisted pipelines.
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🚀 Selected recent work
📌 AI Adoption Enablement — Marketing Agency
Set up ChatGPT Enterprise workflows, defined usage guidelines, trained teams, and implemented repeatable AI processes across departments.
📌 LLM Opportunity Analyzer
Built a full-stack platform to evaluate and prioritize business opportunities using Gemini + AWS models, with structured outputs and decision support.
📌 RAG Systems for Internal Knowledge
Designed and deployed document intelligence systems using vector databases and LLM orchestration.
📌 AI + CRM Integration
Integrated AI into Salesforce, HubSpot, and Pipedrive, including data preparation, prompt structuring, and workflow automation.
📌 Automation Pipelines (n8n)
Built end-to-end workflows combining APIs, LLMs, and dashboards for decision-making.
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🧩 Services I offer
• AI Strategy & LLM Selection
→ Model evaluation, architecture decisions, ROI-focused roadmap
• AI Pilot (2–6 weeks)
→ Design + deploy a working AI use case for your business
• Technical Product Management
→ Lead your AI/cloud initiative end-to-end
• Cloud & AI Architecture
→ Production-ready infrastructure with security and scalability
• Fractional CTO / AI Advisor
→ Ongoing strategic and technical guidance
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🤝 Availability & working style
Based in Miami, FL (EST). I work closely with founders and teams through short discovery sessions, then deliver a clear execution plan with fast iterations.
If you're exploring AI but want to do it right (not just fast) feel free to reach out.
Steps for completing your project
After purchasing the project, send requirements so Danilo can start the project.
Delivery time starts when Danilo receives requirements from you.
Danilo works on your project following the steps below.
Revisions may occur after the delivery date.
Intake & Scope Lock
Deploy the chosen stack (AnythingLLM / n8n-based workflow / AWS Bedrock if already in AWS), ingest approved sources, configure prompt/tone, and implement guardrails (citations + “I don’t know” behavior + refusal rules).
Build RAG Assistant + Guardrails
I’ll deploy AnythingLLM on AWS for the basic tier or Azure/GCP for advanced tiers. You must create the necessary role or provide permission for account setup. Note: All cloud service costs are paid directly to the provider.