AI applied to business, without hype or buzzwords
Articles by WITS on real-world AI implementation, automation and infrastructure security. ROI, architecture, common mistakes and practical guides.
OpenAI dots: an agent that works for you wherever you are (and what it means for your business)
OpenAI's dots are agents that work on their own, in the background and from whatever channel you use, and ask for approval only when it matters. What they are, what you can do with them, and how to bring them into a company's operations.
WhatsApp ERP and CRM integration in Mexico: a guide (official API, options and costs)
WhatsApp is already your sales and collections channel; your ERP and CRM are where operations live. How to connect them with Meta's official API, which architecture to choose and what it costs in 2026.
WhatsApp + Odoo + AI: from a message to a sale
WhatsApp is the channel, AI is the interface and Odoo is the system of record. This is how the full sales process connects, from the first message to payment.
How exposed is your AWS infrastructure?
A system's availability doesn't prove its security. IAM, Access Keys, S3, Security Groups, secrets, CloudTrail: the places where an AWS infrastructure that runs perfectly can have an open door.
Still have port 22 open? Your server's security shouldn't depend on an SSH key
An SSH key is better than a password — but it's not a fortress wall. In the era of automated scanning and AI, the right question is no longer "do I have a key?", but "how many layers of security does my infrastructure have?".
AI agents for sales: what can be automated in the sales process (and what can't)
Vendors promise pipelines that fill themselves. The useful reality: stage by stage, what an agent does well, where it only assists and what stays human.
How to identify AI opportunities in your company (method, not hype)
"Where do I put AI?" is the wrong question. The right one: which work in your operation has the signals AI handles well? The method, without the hype.
How to integrate your business systems: patterns, order and mistakes
Every system works — the problem is they don't talk to each other. Symptoms, patterns and a sensible order so information flows without re-keying.
Case study: the 16-module ISO 9001 platform that cut audit prep by 75%
Audits, nonconformities and documents in scattered spreadsheets → a 16-module SaaS with full traceability. The QualityWeb 360 case.
Which processes to automate first in your company
Lists of "10 processes you can automate" don't answer what matters: which one first. A prioritization method, not another list.
How to choose an AI implementation partner (without getting lost on safari)
There are hundreds of AI tools and they all promise the same thing. The hard part isn't choosing the tool: it's implementing it in your business. What to look for in a partner.
Chatbot vs AI agent: the real difference (and which one your company needs)
Chatbot and AI agent are used as synonyms — they aren't. The difference determines what the system can solve, what it costs and which risks you must control.
How to choose an AI chatbot for business: 3 options and when each one fits
The best AI chatbot doesn't exist in the abstract: it depends on the job it has to do. The 3 real options, objective criteria and when each one fits.
When custom software development makes sense (and when it doesn't)
Do I buy software or have it built? A decision that's expensive to get wrong in either direction. The honest criteria — including when NOT to build.
Process automation: real examples by department
The best way to understand automation isn't theory: it's examples. What gets automated today in sales, customer service, administration and operations — and where to start.
What are AI agents (explained for business)
Everyone talks about AI agents, but few definitions help you decide. What an agent is, how it differs from a chatbot and when it makes sense to bring one into your processes.
What is a chatbot (and where it falls short)
The chatbot is many companies' entry point to AI. What it is, what it does well, and the clear signs that your operation already needs the next step.
What is process automation (and what it can do for your company)
Automating isn't installing a tool: it's turning repetitive tasks into workflows connected to your systems. What can be automated, what can't, and where to start.
Coding with AI: how Claude Code changes the way you work
AI stops being a tool for writing code and starts taking part in the development work itself: investigating, implementing, testing and validating on your real repository.
Claude Code vs Cursor vs GitHub Copilot: 2026 comparison
All three tools are good. None wins at everything. An enterprise comparison so you choose the right one for your organization — not the one with the loudest marketing.
What is Claude Code and how to adopt it in your company
Claude Code isn't Copilot on steroids. It's a different class of tool: an agent that reasons over your entire repository. A guide to understanding and adopting it.
Automate the SDLC with Claude Code and Codex: CTO guide
Your dev team still works like it's 2022 and the competition already ships 2× more per sprint. The difference isn't talent — it's how they organize the SDLC around AI agents.
Claude Code for dev teams: hooks, sub-agents and MCP
A well-configured coding agent changes the SDLC. Poorly configured, it generates technical debt faster than humans. This guide is the difference.
Production RAG with pgvector and Supabase: not a demo
80% of the RAG demos shown on LinkedIn would never reach production. This is the architecture that does — with real numbers, decisions and trade-offs.
5 AI adoption mistakes in Mexican companies
After 50+ AI projects in Mexico, the failures always show the same 5 symptoms. If you recognize any of them, pause before burning through your budget.
How to calculate the ROI of an AI agent for your business
Calculating the ROI of an AI agent isn't subtracting costs from revenue. It's identifying the person-hour saved, the lead not lost and the error not made.
The real cost of implementing AI in a Mexican SMB
No, AI for your SMB doesn't cost "whatever you can pay". It costs between $150k and $2M MXN depending on the case. Here's the realistic breakdown.
RAG vs fine-tuning: which one should your company choose
RAG is faster, cheaper and more transparent than fine-tuning in 80% of cases. But there's a 20% where fine-tuning is the only right option.
AI agents for customer service: a practical guide
A well-designed customer service AI agent escalates 40% of tickets to humans. A poorly designed one escalates 90%, frustrating everyone.
ChatGPT for Mexican companies: an implementation guide
Using ChatGPT in your Mexican company is more complicated (and more useful) than paying 20 USD/month per account. This guide covers what nobody tells you.
GEO: how to show up in ChatGPT and Claude
Google is no longer the only gatekeeper. When a CEO asks Claude "recommend AI consulting firms in Guadalajara", your company needs to be in the answer.
Data Engineering for AI: why data beats the model
AI projects rarely fail because of the model. They almost always fail because of dirty, inconsistent or inaccessible data. Here's how to get ready.
AI use cases in the Mexican automotive industry
Mexico is a leader in automotive manufacturing. AI applied to the sector pays for itself — but it requires understanding the constraints of the plant floor.