How fast can you start?

A Discovery sprint runs 2 weeks and ends with architecture + execution plan. A pilot in real production lands in 4 to 8 weeks. Full systems in 3 to 6 months. We discuss timelines case by case before committing.

How do engagements work?

Discovery is a fixed 2-week scope. Pilot and Production are scoped to a specific outcome you sign off on. Fractional AI Lead is ongoing thinking-partner work with a 3-month minimum. No open-ended hours, no permanent dependency. Details on the call.

Does my data leave my infrastructure?

Not unless you want it to. On-prem deployments, dedicated instances in your VPC, or sovereign models running in Brazil are all on the table. LGPD / GDPR aware by default.

What stack do you work with?

Whatever your case actually needs. We're stack-agnostic: any leading LLM, any vector store, any orchestration layer, any frontend, any database. If you already have infrastructure, we integrate. If you're starting from zero, we help you decide. The right stack is the one that fits your case, not the one we prefer.

And shipping to production?

Depends on your infrastructure. We work with your existing cloud, CI/CD, and observability. If you don't have those set up, we help build them. The agent you see at /demo is a worked example of a full stack from scratch, ready to reuse or adapt.

What happens after delivery?

Your call: full handoff (documented and we walk away), ongoing support (SLA + on-call), or Fractional AI Lead continuing as a senior thinking partner. No lock-in.

Software Zechim builds for marketing agencies

Every agency that has been running for 3+ years has the same problem: 40 percent of the team spends 40 percent of the time doing the same manual work. Monthly reports. Campaign setup. Briefs for creative. Account audits. Competitor monitoring. None of it scales.

Here are the five kinds of software Zechim delivers well for Brazilian agencies. Each attacks one of these repetitions without replacing the team - just frees them to do the work the agency was hired to do.

1. Automated media-account auditor

Meta Business, Google Ads, TikTok Ads Manager. Every month, someone goes into each platform, exports data, cross-references CAC, ROAS, share of investment by objective, flags anomalies. The agent does that every day. Connects via the official API to the client accounts, runs checks you define (broken audiences, creative fatigue, campaign with no conversion, underused budget), fires an alert on Slack or email.

Specialist stops spending 2 hours per account per week doing it manually. Becomes 20 minutes per week reviewing what the agent flagged.

2. Creative-briefing generator

Client approves the campaign brief. Someone has to translate that into video pitches, post scripts, image prompts, ad headlines, A/B/C variations. Every week. For every client. The agent reads the brief, cross-references the campaign history for that client (what worked, what didn't), generates a first draft of these pieces in the correct tone of voice. The creative reviews and adapts instead of writing from scratch.

It's not "AI does creative for you". It's "AI does the draft, the human does what only a human can do".

3. Conversational panel for the client

Client asks for a monthly report. Someone on the data team exports it, builds slides, comments, delivers. The agent can be the panel: the client goes to a link, types "how did my campaign do this month?" and gets an answer with numbers, chart, insight. Every day if they want, not just on the 5th of the following month.

Critical difference: the agent knows what to ask about THAT client's business. It's trained on the context (sector, seasonality, relevant KPIs), it's not a generic dashboard chatbot.

4. Monthly-report generator with narrative

What consumes more hours than you admit: writing the monthly report. Extracting numbers, building context, writing commentary, generating recommendations. The agent assembles the report automatically from the same data sources the specialist would use. Not just numbers - narrative. "Campaign X dropped 20 percent in CTR because it started to fatigue in week 3, we suggest rotating creative Y". Account manager reads it, adjusts, sends.

Client receives a better-than-average report because the agent doesn't forget to look at any metric.

5. Competitor monitor

Client's competitor launched a new campaign, changed positioning, updated the site, appeared in a press outlet. Today nobody sees it. The agent monitors defined competitors' social accounts, sites, Meta ad library, press mentions, and generates a weekly summary per client. The account manager walks into the monthly meeting already knowing what happened in the market.

That turns into a perceived-seniority differential for the client. They feel the agency is watching the game, not just executing.

The common pattern

All five:

Integrate with official APIs (Meta, Google, TikTok, GA4, etc.) - not fragile scraping
Run continuously, generate alerts on Slack or email when something matters
Never post, change budget, or swap creative alone. They escalate to a human.
Leave a log for the specialist to review
Run on the stack the agency already has or on a new stack we set up and transfer

What we don't do

We don't replace project-management tools the agency already pays for (Basecamp, ClickUp, Asana)
We don't replace analytics platforms (GA4, Adobe, whatever)
We don't sell "AI for creative" in the sense of video/image generators. Specialized SaaS exist. We integrate, we don't recreate.

What we do is connect all of this into an agent that does the continuous mechanical work nobody enjoys doing.

If you run an agency in Brazil and one of these scenarios hits your day-to-day, worth 30 minutes for us to understand which fits and how we'd scope it.