You will get GenAI Workflow Audit to Identify High-ROI Automation Opportunities
Project details
GenAI Workflow Audit & Opportunity Map helps you decide what to build, what not to build, and where GenAI will actually create operational value — before you invest time or money in implementation.
This is not a strategy deck or experimentation phase. It’s a practical, execution-focused audit of your existing workflows, tools, and decision logic. I analyze up to 3 real workflows to identify automation opportunities, risks, constraints, and clear build vs. don’t-build recommendations.
You’ll receive a prioritized opportunity map you can directly apply to implementation — either internally or through a Production GenAI Workflow Sprint.
Designed for operators, founders, and teams who want confidence and speed, not hype.
Fixed scope. Fast turnaround. Actionable outcomes.
This is not a strategy deck or experimentation phase. It’s a practical, execution-focused audit of your existing workflows, tools, and decision logic. I analyze up to 3 real workflows to identify automation opportunities, risks, constraints, and clear build vs. don’t-build recommendations.
You’ll receive a prioritized opportunity map you can directly apply to implementation — either internally or through a Production GenAI Workflow Sprint.
Designed for operators, founders, and teams who want confidence and speed, not hype.
Fixed scope. Fast turnaround. Actionable outcomes.
AI Algorithms
Feedforward Neural Network, Large Language Model, Multimodal Large Language Model, Transformer ModelAI Applications
AI Content Creation, AI-Generated Code, AIOps, Conversational AI, Natural Language Generation, Natural Language Understanding, Sequence Modeling, Text RecognitionAI Development Language
PythonAI Tools
Azure OpenAI, GitHub Copilot, Gradio, Hugging Face, Microsoft 365 Copilot, Replit, StreamlitAI Models
ChatGPT, GPT-3, GPT-4, LLaMA, OpenAI Codex, WhisperWhat's included
| Service Tiers |
Starter
$450
|
Standard
$950
|
Advanced
$1,500
|
|---|---|---|---|
| Delivery Time | 2 days | 5 days | 7 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.
Apply audit toward a GenAI Workflow Sprint
+$1
Stakeholder walkthrough & Q&A session
(+ 1 Day)
+$300Frequently asked questions
About Maca
Applied AI Operator building GenAI workflows teams actually use
Santiago, Chile - 3:23 pm local time
I’m not an ML engineer and I don’t do research or experiments.
I work as an Applied AI Automation & Workflow Builder, focused on execution, adoption, and real operational results.
What I do
- Design end-to-end GenAI workflows (intake → reasoning → output → logging)
- Orchestrate tools like Make, Zapier, Google Workspace, APIs, Wix Velo
- Implement QA, guardrails, and templates so workflows don’t break or get abandoned
- Translate business needs into working AI systems for non-technical stakeholders
Typical problems I help solve:
- Too much manual coordination and back-and-forth
- AI ideas that never make it into daily operations
- Processes that are slow, error-prone, or depend on one person
- Teams overwhelmed by tools but lacking usable systems
Proof of work:
1/ ADA — AI-Assisted Workflow System
Designed and implemented a full production GenAI workflow:
onboarding → structured intake → AI reasoning → QA → WhatsApp delivery → logging & metrics
Stack: Wix Velo, Make, Google Workspace, LLMs
Impact: faster turnaround time, reduced manual coordination, real user adoption
I work best with early-stage to mid-stage teams that need things built fast, clean, and usable — without heavy infrastructure or ML pipelines.
If you’re looking for AI that actually runs inside your operation, we’ll work well together.
Steps for completing your project
After purchasing the project, send requirements so Maca can start the project.
Delivery time starts when Maca receives requirements from you.
Maca works on your project following the steps below.
Revisions may occur after the delivery date.
Intake & context review
You submit workflow descriptions, tools involved, and objectives. I review current processes, constraints, and handoffs.
Friction & GenAI fit analysis
I identify bottlenecks, repetition, decision logic, and assess where GenAI helps — and where it shouldn’t be used.