Catalog of projects, systems and applied AI cases.

The store has products loaded, but descriptions are short, categories are not well organized and few qualified inquiries arrive.

The site exists, but does not sell clearly: benefits, comparisons, FAQs and stronger calls to action are missing.

AI web audit, category prioritization, product sheet improvements and business content calendar.

Work is done on WordPress/WooCommerce, optimized copy, FAQs, SEO structure, plugin recommendations and simple automations.

Clearer catalog, better shopping experience and a base prepared for campaigns or recurring content.

Sensitive business information is summarized to show only the work approach.

The business answers questions about hours, menu, bookings, promotions and location through social networks and WhatsApp.

Replies depend on who is available, messages get lost and content is published without strategy.

Organize FAQs, prepare business replies, create a publishing calendar and a simple booking flow.

An assistant connected to WhatsApp or forms was defined, with an editable menu page, content prompts and human routing for sensitive bookings.

Fewer repeated questions, more consistent communication and better use of weekly promotions.

The flow can adapt to a bar, restaurant, venue or local venture.

The company receives orders through WhatsApp, email and spreadsheets. Sales checks stock with the warehouse several times a day and administration builds reports manually.

Information is scattered, internal questions repeat and business decisions arrive late.

Map workflows, create an internal knowledge base, organize frequent products and define an assistant for stock, order and report questions.

An internal panel was prepared, connected to spreadsheets or a database, with controlled prompts, permissions by area, summarized reports and an initial automation for frequent questions.

Fewer interruptions between teams, faster answers for sales and a base to scale toward ERP or ecommerce integration.

A summarized version is presented to protect internal processes, operational data and business decisions.

The team handles quotes, PDFs, work changes and messages between office, suppliers and site managers.

Documents pile up, priorities mix together and it is hard to detect risks or missing items before sending a proposal.

Create a document review workflow with checklist, executive summary, pending items and condition comparison.

AI was prepared on a private VPS or local environment, with PDF analysis, checklist templates, folders by project and exportable reports.

Better control before quoting, fewer omissions and a faster way to review changes between versions.

Construction documents, quotes and terms are treated as confidential information.

Reception always answers the same questions about schedules, study preparation, coverage and administrative steps.

The team loses time on repetitive replies and cannot calmly handle the cases that really require human attention.

Separate public information from sensitive data, create approved answers, define clear limits and route sensitive matters to a person.

A web/WhatsApp assistant was defined, with controlled knowledge base, prior forms, inquiry tracking and privacy rules.

More organized service, less repetitive workload and better preparation before reception intervenes.

The scope is presented commercially; in health, work is done with strict limits and without automated diagnoses.

A small agency delivers several sites per month and needs to review quality before publishing.

Each delivery depends on a manual checklist and SEO, accessibility, copy or visible security details can slip through.

Build a repeatable AI audit workflow with checklists by site type and reports that clients can easily understand.

Use of OpenClaw on VPS, page analysis, GitHub repositories, SEO/marketing/security reports and recommendation templates.

More consistent deliveries, higher-value reports and less time spent on repetitive reviews.

Each client technical findings are not published.

A freelance developer wants to use AI without always depending on online tools or exposing client code.

He has GitHub repositories and projects on Windows and Linux, but no clear workflow to use local models.

Prepare an environment with Ollama, models based on hardware, controlled folders, OpenCode/OpenClaw and usage guides by task type.

Installation and testing with models such as Qwen, DeepSeek or Hermes, prompts for code review, documentation, visible security and change analysis.

A more private workflow to review code, speed up documentation and work with assistants without disorganizing the project.

Client code stays out of public examples.

A junior developer wants to learn better by working on real repositories and her own exercises.

Isolated tutorials do not explain how to organize a project, review errors or document decisions.

Create a learning environment with repositories, review prompts, step-by-step guides and API exercises.

Docker configuration, local environment, AI models, exercise review, practice pull requests, documentation and good-practices checklist.

More applied learning, better judgment when reading code and a routine to practice without depending only on courses.

It adapts to students, trainees or developers who want to level up.