≈90% / 37%
regular AI use somewhere / reported enterprise-level EBIT impact
AI is nearly ubiquitous in organizations. Enterprise financial impact is still much less common.
FIT AI INTO HOW YOU ALREADY WORK.
AI only creates valuewhen it fits how your company works.
We find the exact place AI fits into the way your company already works, redesign the workflow around it, and scale only what pays for itself.
YOUR COMPANYOPERATING ARCHITECTURE
AI
This structure cannot carry that outcome yet.
2 weak blocks — AI has nowhere to land
Select a weak block to intervene
THE MARKET IS ALREADY MOVING
AI adoption is spreading faster than most companies are learning to turn it into value.
Three signals worth paying attention to — especially if you are still treating AI as a future initiative.
15% → 50%
AI adoption in Brazilian small → large enterprises
Small enterprises: 15%. Medium: 32%. Large: 50%.
Source: Cetic.br · TIC Empresas 202571%
of Brazilian workers used AI in their role in the last 12 months
Only 26% report using generative AI every day — adoption is broad, habitual use is not.
Source: PwC · Hopes & Fears 2025 — BrazilDifferent studies and populations. Read each number as a separate market signal, not as one shared funnel or denominator.
AI in the right place, with known cost and measured return.
PRODUCTIVITY
More useful output from the people you already have.
ECONOMICS
Know what AI costs and whether it earns its keep.
CAPABILITY
Teach your teams to build with AI on their own.
How we can work together
Diagnose. Learn. Build. Prove.
Start with the business and the work. Then decide whether the answer is a better process, a copilot, an AI workflow, a bounded agent — or no AI at all.
AI Assessment & Roadmap
Find where AI belongs across the company, compare leadership perception with employee reality, prioritize real workflows by value, readiness and risk, and leave with a practical 90-day plan.
Hands-on AI Workshop
Learn by building around real company work. The team brings actual workflows, gives models the right context and tools, tests quality, and leaves with useful first prototypes. The competitive risk is not AI replacing the team — it is another team learning to use it better.
AI Talks
A practical session for leaders or broader teams on what AI does well, where it fails, what changes when agents get tools and authority, and why difficulty is a bad proxy for reliability.
AI Build Sprint
Take one prioritized workflow into a measured pilot: baseline the current work, build the simplest useful intervention, test it, and prove the gain before scaling.
The Blocchi platform
Advisory where the problem starts. A business app where the work runs. One governed data foundation under both.
Advisory is the engagement path for understanding the work, prioritizing opportunities and deciding what should be built or changed. Revenue is the business-facing application. Data+ is the shared layer for sources, raw records, mapping, quality, mastering and lineage.
Advisory path
Blocchi Advisory
A guided engagement to understand workflows, evidence and opportunities before deciding whether the answer is process change, AI, a Blocchi product or something custom.
See Advisory servicesBusiness app
Blocchi Revenue
Understand revenue performance, customer signals and commercial outcomes with governed metrics and evidence.
Explore RevenueInside the platform
Shared foundation
Blocchi Data+
The shared workspace behind enabled products: connect sources, inspect governed/raw records, map fields, fix quality issues, master identities and trace provenance.
Build capability inside your team.
We work with your team so the knowledge stays inside the company.
1
Find the fit
Start with the work. Identify where AI, automation or better technology can materially change speed, quality, cost or capacity.
2
Redesign the work
Simplify the workflow before automating. Define the human role and decide what should be automated, assisted or left alone.
3
Build together
Teach the patterns, select the tools and build the first useful workflows with your people so they can keep improving them.
4
Scale what pays
Measure productivity and economics. Expand what creates value, govern what carries risk and stop experiments that do not earn their keep.
ONE PRINCIPLE WE TEACH
AI doesn't fail in order of difficulty.
A model can solve something that looks extremely hard and then make a ridiculous mistake on something that looks easy. Good AI adoption is about fit, context, tools, verification and authority — not blindly increasing autonomy.
The site stops here on purpose. In the talk and workshop we turn this into practical rules for copilots, workflows and agents.
See talks and workshopsOur product
Blocchi Revenue
Find your revenue gaps before they cost you the result.
The same reading we do in a consulting engagement, running on its own: connect your CRM, see where revenue is leaking and what to do about it.
Find the gaps
Connect CRM and commercial data to see where pipeline, conversion and data quality are holding revenue back.
Maximize revenue
Prioritize fixes by impact, track how they move, and compare against benchmarks for your market.
AI on governed data
AI reads and explains the diagnosis on top of a governed semantic model, so every answer has a trace instead of being a guess.
Who is behind this
Track record
- Director of Enterprise Architecture · global CPaaS company
- Global IT Director · AB InBev
- DuPont
- Electrical Eng. · USP / University of Ottawa
- MBA Analytics & Big Data · FGV
André Progiante
Founder of Blocchi · Technology and AI
I spent the last decade leading technology and transformation at global companies. I watched AI initiatives fail up close, and others take whole processes to another level. I now use that experience to help growing companies make decisions that would normally take a far larger technology organisation.
I was Global IT Director at AB InBev and director of enterprise architecture at a global CPaaS company. I led cloud migrations, CRM platforms with more than 150,000 users, and programmes that cut costs by millions. Before that, DuPont. That is where I learned the least glamorous part of transformation: governance, adoption and execution.
I have designed and delivered AI at scale, from chatbots to autonomous agents, and learned how to keep AI cost under control so it actually pays for itself. That is why I do not treat AI as magic. It can change how the work gets done, but it also turns expensive and goes wrong fast when it lands in the wrong place. My job is to separate real opportunity from hype and help you do the part that is worth doing.
Follow on LinkedInNumbers from real transformations
150k+
users on platforms I led
10+
years leading technology at global scale
10x
productivity on processes redesigned with AI
−70%
support cost, using AI tools
Let's talk
What are you trying to make better?
Start with the business problem. We will help work out whether AI, technology or a broader transformation is the right answer.
Talk on WhatsApp
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