You will get a custom AI assistant with persistent memory that learns your business
Rising Talent
Project details
You'll get an AI assistant that actually remembers your business - your docs, your decisions, your context - instead of starting from zero every conversation.
I build persistent-memory assistants on a multi-layer architecture (vector + full-text + knowledge graph), so the assistant gets smarter every time your team uses it. It auto-captures context as you work, self-heals when a service fails, and backs itself up nightly - the same design I run in daily production, encoding over a year of my own accumulated decisions and rules.
You own the deployed code outright, plus a clear architecture diagram and a 1:1 handoff session so your team can run and extend it without me. This isn't a ChatGPT wrapper that forgets you the moment you close the tab - it's a company brain that compounds.
I build persistent-memory assistants on a multi-layer architecture (vector + full-text + knowledge graph), so the assistant gets smarter every time your team uses it. It auto-captures context as you work, self-heals when a service fails, and backs itself up nightly - the same design I run in daily production, encoding over a year of my own accumulated decisions and rules.
You own the deployed code outright, plus a clear architecture diagram and a 1:1 handoff session so your team can run and extend it without me. This isn't a ChatGPT wrapper that forgets you the moment you close the tab - it's a company brain that compounds.
AI Algorithms
Large Language Model, Transformer ModelAI Applications
AI Chatbot, Conversational AI, Natural Language Generation, Natural Language UnderstandingAI Development Language
PythonAI Models
ChatGPT, GPT-4, LLaMAWhat's included
| Service Tiers |
Starter
$850
|
Standard
$3,500
|
Advanced
$6,500
|
|---|---|---|---|
| Delivery Time | 7 days | 14 days | 18 days |
Number of Revisions | 1 | 2 | 3 |
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 Kevin
AI Automation & Agent Builder | Full-Stack Apps That Ship Live
Santa Ana, United States - 2:55 pm local time
Most freelancers prove one thing. Here's what I've actually shipped:
- A live subscription app on the Apple App Store, Google Play, and the web, processing real Stripe payments today. Solo - architecture, payments, native mobile release, and the growth funnel around it. The hardest, most-faked milestone in software, done alone.
- A production autonomous AI/ML decision platform that has run unattended for over six months and counting: ~35 analysis modules across 7 stages, a dual-engine consensus design that hard-blocks when its rules engine and ML ensemble disagree, an LLM review gate that fails CLOSED on any timeout or error (never auto-approves), and a daily model retrain with automatic rollback on regression. Real safety engineering, not a demo.
- A persistent-memory AI assistant system I run in daily production across multiple businesses - hybrid vector + full-text + knowledge-graph retrieval, automatic capture, self-healing, and backups. It compounds context instead of forgetting it, which is exactly where most stateless RAG bots fall down.
- A live paid-acquisition engine delivering qualified leads at around $15-20 each, well under the typical market rate. I don't just build the product - I bring it customers and prove the cost per result with real numbers.
What ties it together: I can build the thing AND get it used. AI systems and full-stack apps are the engine; automation and growth are how the engine produces results.
Background: B.A. Accounting (Cal State Fullerton) and a finance career before this, so I build like an owner - unit economics, margins, and ROI baked into every decision, which matters when there's real money on the line (payments, ad budgets, deployments that have to be right).
If you need one builder who can own a hard system end to end - AI, app, automation, or the growth around it - and actually finish, let's talk. Tell me the outcome you need and I'll tell you exactly how I'd build it.
Steps for completing your project
After purchasing the project, send requirements so Kevin can start the project.
Delivery time starts when Kevin receives requirements from you.
Kevin works on your project following the steps below.
Revisions may occur after the delivery date.
Discovery & memory mapping
We map your use case and pin down exactly what the assistant should remember, where its knowledge lives, and what a clear win looks like - before any code is written.
Build the memory architecture
I set up the multi-layer memory - vector + full-text + knowledge graph - and wire in your chosen AI model and data sources so it actually retains and recalls context.