You will get an AI assistant that answers questions over your own documents
Project details
Sitting on a pile of documents your team keeps digging through by hand? I build AI systems that answer questions over your own content — accurately, with sources.
I set up the full retrieval pipeline: your documents are ingested, chunked, embedded into a vector database, and searched by meaning — then the system answers from the passages it finds, citing the exact source and page. So answers are grounded in your material, not guessed, and every claim is traceable.
It handles your whole corpus — PDFs, Word docs, web pages, spreadsheets, even scanned files via OCR — unified into one searchable knowledge base. Query it through a clean chat UI or an API your app calls. No fine-tuning, no lock-in: your data stays yours, and you can re-index anytime.
Built as typed, documented code you own, powered by Claude or the OpenAI API via a vendor-agnostic layer. Built by a senior full-stack engineer (ex-NBCUniversal, ex-Ancestry) who ships this kind of pipeline in production.
Pick a package below — from single-source Q&A to a full knowledge system — or message me and I'll scope it to your documents.
I set up the full retrieval pipeline: your documents are ingested, chunked, embedded into a vector database, and searched by meaning — then the system answers from the passages it finds, citing the exact source and page. So answers are grounded in your material, not guessed, and every claim is traceable.
It handles your whole corpus — PDFs, Word docs, web pages, spreadsheets, even scanned files via OCR — unified into one searchable knowledge base. Query it through a clean chat UI or an API your app calls. No fine-tuning, no lock-in: your data stays yours, and you can re-index anytime.
Built as typed, documented code you own, powered by Claude or the OpenAI API via a vendor-agnostic layer. Built by a senior full-stack engineer (ex-NBCUniversal, ex-Ancestry) who ships this kind of pipeline in production.
Pick a package below — from single-source Q&A to a full knowledge system — or message me and I'll scope it to your documents.
AI Algorithms
Large Language Model, Multimodal Large Language Model, Transformer ModelAI Applications
AI Content Creation, Conversational AI, Natural Language Generation, Natural Language Understanding, Sentiment Analysis, Text RecognitionAI Development Language
PythonAI Tools
Azure OpenAI, Gradio, Hugging Face, PyTorch, Streamlit, TensorFlowAI Models
ChatGPT, GPT-4What's included
| Service Tiers |
Starter
$750
|
Standard
$1,800
|
Advanced
$3,500
|
|---|---|---|---|
| Delivery Time | 5 days | 9 days | 16 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 |
Optional add-ons
You can add these on the next page.
Fast Delivery
+$300 - $800
Additional Revision
+$120
Additional document source
(+ 3 Days)
+$400
OCR / scanned document handling
(+ 4 Days)
+$500Frequently asked questions
About Alden
Full-Stack & AI Integration Developer | Claude, OpenAI
Salt Lake City, United States - 1:36 am local time
What I build for clients:
AI chatbots & assistants — Claude and OpenAI wired into your app, site, or internal tools, with clean prompt design and streaming responses
LLM & API integrations — vendor-agnostic architecture so you can swap providers (or run both) without rewriting your stack
Full-stack apps around the AI — Next.js, TypeScript, and PostgreSQL front to back, deployed on AWS or Cloudflare
Backend & CMS work — PHP, Laravel, and WordPress builds, plugins, and custom API layers
I've spent my career shipping software that has to work at scale and on deadline. As Lead Software Engineer at NBCUniversal's Golf Channel I built and maintained broadcast-grade web systems; at Ancestry I engineered the consumer flows behind DNA kit activation. Today I'm the sole architect and engineer behind a portfolio of SaaS products — including a multi-tenant, real-time scheduling platform — so I handle everything from database schema to deployment, not just one slice of it.
That range means I can take an AI project from "here's the idea" to a working, deployed feature without needing a team around me to fill gaps.
One more thing that sets me apart: I'm also a filmmaker and photographer, running a small production studio on the side. That eye makes me unusually strong on the parts most engineers rush — UX polish, visual detail, and explaining clearly to non-technical clients what they're actually getting.
Core stack: Next.js · React · TypeScript · JavaScript · Node.js · PostgreSQL · PHP · Laravel · Python· Django · FastAPI · WordPress · AWS · Cloudflare · Claude & OpenAI APIs
Have an AI feature or full-stack project that needs to actually ship? Send me the details and I'll tell you exactly how I'd approach it.
Steps for completing your project
After purchasing the project, send requirements so Alden can start the project.
Delivery time starts when Alden receives requirements from you.
Alden works on your project following the steps below.
Revisions may occur after the delivery date.
Scope & Sample
We confirm what you need to ask your documents, and I review a sample of your corpus — especially any scanned files — to gauge extraction quality. You'll get a written scope and success criteria before any build.
Ingest & Index
I build the pipeline: parse your documents (OCR for scans), chunk and embed them, and load them into a vector store — turning your whole corpus into one searchable, retrievable knowledge base.