You will get AI generated docs for your app plus a pipeline that keeps them current
Project details
You will get documentation generated from your actual source code, and a pipeline that keeps it current after I leave. Documentation projects usually fail the same way: someone writes it once, it is accurate for a month, then it quietly rots and everyone goes back to asking in Slack.
I have built this for real. At a B2B SaaS company I built a product knowledge platform generated from source code, pushed through a pipeline into a vector database and served to every team. It now answers 54% of support conversations without a human, and ticket volume fell 35%.
The work is generation plus review, not generation alone. AI drafts from your code, I read every page, and anything ambiguous comes back to you as a question rather than a confident guess. Then it goes into CI so it rebuilds and redeploys on merge.
I have built this for real. At a B2B SaaS company I built a product knowledge platform generated from source code, pushed through a pipeline into a vector database and served to every team. It now answers 54% of support conversations without a human, and ticket volume fell 35%.
The work is generation plus review, not generation alone. AI drafts from your code, I read every page, and anything ambiguous comes back to you as a question rather than a confident guess. Then it goes into CI so it rebuilds and redeploys on merge.
AI Algorithms
Large Language ModelAI Applications
AI Content Creation, AI-Generated Code, AIOpsAI Models
ChatGPT, GPT-4What's included
| Service Tiers |
Starter
$1,000
|
Standard
$2,500
|
Advanced
$5,000
|
|---|---|---|---|
| Delivery Time | 10 days | 21 days | 30 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 Garth
Fractional CTO | AI Transformation for SaaS & SMEs | Web Builds
Windsor, United Kingdom - 10:06 pm local time
Most of my recent work has been putting AI to work properly rather than as a demo. Engineering cycle time down 41% across 800 issues through AI assisted code review and test generation. 54% of support conversations resolved without a human, using a knowledge pipeline I built that generates product documentation straight from source code into a vector database. Non technical teams at my company now build their own tooling.
Three things I'm useful for here:
AI transformation. Working out where AI actually helps and where it's a waste of money. Multi-model strategy, cost control per feature, and getting teams to use the thing rather than just having access to it.
Fractional and interim CTO. Tech strategy, scaling engineering teams, architecture review, technical due diligence, ISO 27001 and SOC 2 readiness. I've taken a business through both certifications and through a private equity backed exit.
Websites and web apps. I still write code most weeks and build sites for clients directly. Recent work includes custom WordPress themes for a performance coaching business and a book launch site for a published author, both designed and built from scratch rather than assembled from a page builder.
I'm direct about what's worth doing and what isn't. If your problem is better solved by not hiring me, I'll say so.
Steps for completing your project
After purchasing the project, send requirements so Garth can start the project.
Delivery time starts when Garth receives requirements from you.
Garth works on your project following the steps below.
Revisions may occur after the delivery date.
Scope and structure
I read the codebase and agree what gets documented and how deep. We settle the structure before generating at volume, because fixing structure later is expensive.
Generation and human review
AI drafts from your source. I read every page. Anything the code does not answer comes back to you as a question instead of a confident guess.