You will get an honest answer on whether AI actually solves your problem
Rising Talent
Rising Talent
Project details
Before you spend real money on an AI build, it is worth knowing whether AI is the right tool at all. Often it is not, and the honest version of that answer is a great deal cheaper than finding out six weeks into a project.
Send me the problem and twenty or so real examples of your data. I will tell you whether a model helps, what approach I would take, roughly what it would cost to build and to run, and where it would fail.
If the answer is that a deterministic parser or a rule you can read would do the job better, I will say so. That happens more often than this market admits, and those solutions are cheaper to run and easier to trust.
You get a written assessment you can hand to a developer, a partner, or a board. It is yours whether or not you ever work with me, and no obligation is attached to it.
For context on the judgment you are buying: I have shipped 14 LLM-extraction pipelines into a client production system running at roughly 98 percent success across 600-plus runs. Most of the value in that work came from deciding what not to send to a model.
Send me the problem and twenty or so real examples of your data. I will tell you whether a model helps, what approach I would take, roughly what it would cost to build and to run, and where it would fail.
If the answer is that a deterministic parser or a rule you can read would do the job better, I will say so. That happens more often than this market admits, and those solutions are cheaper to run and easier to trust.
You get a written assessment you can hand to a developer, a partner, or a board. It is yours whether or not you ever work with me, and no obligation is attached to it.
For context on the judgment you are buying: I have shipped 14 LLM-extraction pipelines into a client production system running at roughly 98 percent success across 600-plus runs. Most of the value in that work came from deciding what not to send to a model.
AI Algorithms
Large Language ModelAI Applications
Natural Language UnderstandingAI Tools
GitHub Copilot, Hugging FaceAI Models
ChatGPT, GPT-4What's included
| Service Tiers |
Starter
$250
|
Standard
$400
|
Advanced
$1,000
|
|---|---|---|---|
| Delivery Time | 1 day | 1 day | 2 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 | - | - |
Optional add-ons
You can add these on the next page.
Additional Revision
+$200About Matthew
Product Manager Who Builds | Next.js, React, Supabase, AI Integration
Forest Grove, United States - 4:43 pm local time
Fifteen years across product and delivery, most of it now spent building full-stack systems end to end: Next.js, React, TypeScript, Supabase and Postgres, with AI integration (Claude and OpenAI APIs) designed in from day one rather than bolted on after.
Recent builds through my studio, Bobi Labs:
Cascadia Forestry Platform. Full-stack operations platform replacing paper timesheets and Excel payroll for a Pacific Northwest forestry business. Mobile-first and offline capable for crews with no signal, bilingual English and Spanish at full parity, separate dashboards for office staff and field crews, and a payroll pipeline that loaded 91 percent of their historical records straight off paper field sheets.
Tweet Pulse. Real-time prediction-market intelligence dashboard, live in production at elontweetpulse X API ingest, 10 materialized views, regime detection, Telegram alerts.
Work Tracker. Free and open source under MIT at bobilabs-worktracker. No account, no server, no tracking. It runs entirely on your machine and your work never leaves it. Open it and start using it.
Pursuit. AI-scored opportunity pipeline: multi-source scrapers, Claude-based fit scoring, one-click capture extension. Free tier live at pursuit.bobilabs.
Before the studio: Product Manager at Neon One (nonprofit SaaS), Co-Founder and Product Director at Solana Sanctuary (web3), and a decade in fintech at Genesis Financial, where I built the PMO from the ground up.
Fixed-scope jobs are welcome too: data cleaning and migration, scraping, ETL, document conversion, QA scripting. Clear spec in, working software out.
If you want someone who can take a rough idea to deployed and iterating without hand-holding, that is the job I do.
Steps for completing your project
After purchasing the project, send requirements so Matthew can start the project.
Delivery time starts when Matthew receives requirements from you.
Matthew works on your project following the steps below.
Revisions may occur after the delivery date.
Your problem and data reviewed
I read the real examples, not a summary
Approach tested against your cases
including the non-AI options