Edition of October 26, 2026Use cases · with prompt · with sourcePTEN

Nº 062 · Companies

Real cases of AI and AI agents at Brazilian companies

Illustrative photo: city and economy sector
São Paulo, SP22 economic sectors
Illustrative photo: Agribusiness sector
Illustrative photo: Health sector
Illustrative photo: Industry sector

What companies are doing with AI, with which tool and with what result. Every case has a public source, a verification date and the numbers as published, with no estimates.

Cases
62
Sectors
22
Sourced
100%
Updates
Daily

Sectors

22 sectors · tap to filter

Case index

62 of 62 cases

Illustrative photo: Finance sector01
Finance
Itaú Unibanco

Itaú Unibanco

20%–80%

ia.i reached about 300,000 customers in its first phase; the legal solution runs more than 2 million tasks per month with efficiency gains of 20% to 80%

ia.i conversational assistant for customers and the IARA governance platform; legal solution covering 90 million documents

OpenAIOpenAI (GPT-5.x)Read →
Illustrative photo: Finance sector02
Finance
Nubank

Nubank

55%

The assistant resolves 55% of Tier 1 requests, handles more than 2 million chats per month, and cuts response time by 70%

AI customer service assistant, call center copilot, internal search and fraud QA with computer vision

OpenAIOpenAI (GPT-4o)Read →
Illustrative photo: Finance sector03
Finance
Bradesco

Bradesco

82%

82% first-level resolution rate and 89% first-week retention; BIA usage grew 8x

BIA, a virtual assistant, integrated with generative AI for customers and managers

MicrosoftAzure OpenAIRead →
Illustrative photo: Finance sector04
Finance
Bradesco

Bradesco

10%–20%

10% to 20% gains in credit recovery capacity

AI collections agent that transcribes and analyzes agent conversations and suggests improvements

Other / not statedPlataforma Bridge (própria)Read →
Illustrative photo: Finance sector05
Finance
Bradesco

Bradesco

65%

65% more efficient audit planning

AILA, an AI assistant built by the internal audit team itself

MicrosoftAzure OpenAIRead →
Illustrative photo: Retail sector06
Retail
Magalu

Magalu

More than 20 agents in production; results detailed in the Bain case

Lu assistant on WhatsApp with more than 20 orchestrated AI agents for search, recommendation, customer service and purchasing

Other / not statedModelos próprios e de terceirosRead →
Illustrative photo: Services/Technology sector07
Services/Technology
BB

BDM (Big Data Mining)

85%

85% faster analyses, 98% accuracy, 40% less operational effort

LOUIS, a generative AI model for document processing used by a financial institution

AWSAmazon BedrockRead →
Illustrative photo: Industry sector08
Industry
Condor

Condor

Prototype built in weeks; greater efficiency in ticket search (no figure published)

Generative AI prototype for IT support and help desk, built on a knowledge base and ticket history

AWSAmazon BedrockRead →
Illustrative photo: Retail sector09
Retail
Gimba

Gimba

50%

Time to register each item dropped from 13 to 2 minutes; solution cost 50% lower

Platform that generates descriptions for a catalog of 30,000 products

AWSAmazon Bedrock (Claude 2)Read →
Illustrative photo: Health sector10
Health
GE

Grupo Elfa

100 million

Quoting time dropped from 40 to 2-3 minutes; more than R$ 100 million in new revenue in 8 months

CotAI, an AI that reads and answers thousands of quote requests received by email

AWSAmazon Bedrock, TextractRead →
Illustrative photo: Delivery sector11
Delivery
iFood

iFood

Every order goes through more than 100 AI models (no result metric for GenAI)

Generative AI for experience personalization and developer productivity

AWSAmazon Bedrock, SageMakerRead →
Illustrative photo: Finance sector12
Finance
Banco Inter

Banco Inter

108%

Investigation capacity increased by 108%

Penélope, an agent that automates financial crime investigations

AWSAmazon BedrockRead →
Illustrative photo: Finance sector13
Finance
S

Sinosserra

12 thousand

12,000 bonds per month; validation dropped from 24 hours to 1 minute

Automatic document validation for capitalization bonds

AWSAmazon BedrockRead →
Illustrative photo: Automotive sector14
Automotive
Webmotors

Webmotors

8.5x

8.5x higher engagement

Agents that respond to vehicle negotiations instantly and in a personalized way

AWSAmazon BedrockRead →
Illustrative photo: SMB sector15
SMB
LP

Lina Prades (joalheria)

Two management apps created; one supports daily operations

An entrepreneur used ChatGPT for content, ads, pricing and inventory, and built two management apps with no technical background

OpenAIChatGPTRead →
Illustrative photo: SMB sector16
SMB
TD

Tapioca da Ari

A more organized and visible business (qualitative account)

Using ChatGPT to develop recipes, the menu and customer communication

OpenAIChatGPTRead →
Illustrative photo: Energy sector17
Energy
Copel

Copel

Queries went from a day to near real time

AI agent that answers natural-language questions about SAP ERP data

GoogleGemini 1.5 Pro, Vertex AI, BigQueryRead →
Illustrative photo: Market Research sector18
Market Research
G

Galaxies

97%

Research time 97% shorter; cost per study from R$ 1 million to R$ 150,000

AI-generated synthetic personas for market research

GoogleVertex AI, Gemini 2.0Read →
Illustrative photo: Health sector19
Health
Genial Care

Genial Care

About 2 hours

Documentation dropped from about 2 hours a day to 3 minutes per session

LIAM, which generates clinical session records from audio

GoogleVertex AIRead →
Illustrative photo: Health sector20
Health
Sami Saúde

Sami Saúde

81%

81% of records approved without edits; more than 900 hours saved per month

Medical records generated by AI from text, images and audio

GoogleGemini para Google Workspace, Vertex AIRead →
Illustrative photo: Food sector21
Food
3 Corações

3 Corações

98%

299 agents created; 390.5 hours saved; 98% adoption

Adoption of Gemini Enterprise with agents built by the teams themselves, such as the Stalled Orders Auditor

GoogleGemini EnterpriseRead →
Illustrative photo: Mobility sector22
Mobility
Sem Parar

Sem Parar

9.3%

Average handling time 9.3% shorter; accuracy above 92%

Customer Service Copilot for call center operators using RAG

MicrosoftAzure OpenAI, Azure AI SearchRead →
Illustrative photo: Telecom sector23
Telecom
Vivo

Vivo

9%

Average handling time 9% shorter (consumers) and 4% shorter (businesses)

I.Ajuda, a generative AI assistant for 11,000 call center agents

MicrosoftAzure OpenAIRead →
Illustrative photo: Finance sector24
Finance
CAIXA

CAIXA

70%–80%

Processes that took 10 to 12 days now take about 30 minutes; 70% to 80% gains in back office

Copilot and agents in Copilot Studio for back office, legal, compliance and customer service

MicrosoftMicrosoft 365 Copilot, Copilot StudioRead →
Illustrative photo: Finance sector25
Finance
Tecban

Tecban

Up to 35%

Up to 35% productivity gain

Agents for pre-sales, compliance, audit, HR and field operations

MicrosoftCopilot StudioRead →
Illustrative photo: Finance sector26
Finance
C

Cielo

52.2%

Tickets reduced by 52.2%

AI agent for internal IT support

MicrosoftCopilot StudioRead →
Illustrative photo: Tourism sector27
Tourism
AI

A1 Inteligência em Viagens

55%

55% increase in travel coordination efficiency

Fifi, an agent for customer service and travel policies

MicrosoftCopilot Studio, Power AutomateRead →
Illustrative photo: Industry sector28
Industry
Marcopolo

Marcopolo

Six agents built in four days

Training teams to build AI agents

Other / not statedAgentes de IA (Prosperi)Read →
Illustrative photo: Education sector29
Education
YDUQS

YDUQS

More than 90%

Over 90% accuracy, average response time of 4 seconds

Automatic classification of enrollment letters

GoogleVertex AI (PaLM 2)Read →
Illustrative photo: Public Sector sector30
Public Sector
P

Prodam

See case (development and testing automation)

Automation of development, code validation and testing

GoogleGemini Code Assist, Vertex AIRead →
Illustrative photo: Health sector31
Health
P

ProBrain

89%

AI costs 89% lower

Migration of AI workloads to Vertex AI

GoogleVertex AIRead →
Illustrative photo: Insurance sector32
Insurance
1S

180 Seguros

BigQuery queries three times faster

Experimental conversational base for partner developers, integrated with the API

GoogleGoogle Cloud (IA generativa)Read →
Illustrative photo: Construction sector33
Construction
Direcional Engenharia

Direcional Engenharia

20%

Analysis time 20% shorter

Generative AI to analyze customer relationship calls

AWSAWS (IA generativa)Read →
Illustrative photo: Services/Technology sector34
Services/Technology
T

Totaldocs

70%

Search and analysis time 70% shorter

Document search and analysis with generative AI

AWSAmazon BedrockRead →
Illustrative photo: Legal sector35
Legal
A

Alfaneo

94.45%

Petition drafting time 94.45% shorter

Drafting legal petitions with generative AI

AWSAWS (IA generativa)Read →
Illustrative photo: Services/Technology sector36
Services/Technology
Hotmart

Hotmart

Up to 50%

Support workload reduced by up to 50%; 1.6 million questions answered

Generative AI in support for digital entrepreneurs

AWSAWS (IA generativa)Read →
Illustrative photo: Finance sector37
Finance
PicPay

PicPay

45%

NPS up 45%; understands 95% of conversations

Customer service assistant with generative AI

MicrosoftAzure OpenAIRead →
Illustrative photo: Finance sector38
Finance
Stone

Stone

93%

93% positive rating

Customer service with generative AI

Other / not statedNão informadoRead →
Illustrative photo: Finance sector39
Finance
will bank

will bank

37%

Satisfaction 37% higher; human workload 26% lower

Customer service with generative AI

AWSAmazon BedrockRead →
Illustrative photo: Health sector40
Health
Hospital Israelita Albert Einstein

Hospital Israelita Albert Einstein

98.9%

2,350 consultations; in testing, more than 200 hours saved and 98.9% acceptance of suggestions

AI that transcribes consultations in urgent care and generates a draft of the medical record

Other / not statedNão informadoRead →
Illustrative photo: HR sector41
HR
B

Bondy

About 85%

Around 85% of cases resolved (according to the company)

AI assistant on WhatsApp that answers HR questions for clients such as Ambev, Raízen and Mercado Livre

Other / not statedNão informadoRead →
Illustrative photo: Automotive sector42
Automotive
Localiza&Co

Localiza&Co

See the article

AI for assessing vehicle damage and analyzing the fleet

Other / not statedNão informadoRead →
Illustrative photo: Agribusiness sector43
Agribusiness
S

Smartcoop

20.000 hours

20,000 hours saved per year on searches for farmers and cooperatives

Ana, a generative AI virtual assistant for farmers and cooperatives in Rio Grande do Sul

AWSAmazon BedrockRead →
Illustrative photo: Agribusiness sector44
Agribusiness
IC

Integrada Cooperativa Agroindustrial

30 days

An analysis that used to take 30 days now takes 20 minutes

Farmable Areas Project: satellites and AI to analyze farmable land

Other / not statedIA com imagens de satéliteRead →
Illustrative photo: Finance sector45
Finance
Base39

Base39

96%

Credit analysis cost 96% lower; decision time cut from three days to under an hour; infrastructure 84% cheaper

Credit analysis with generative AI, vector search and Claude

AWSAmazon Bedrock, Claude, MongoDB AtlasRead →
Illustrative photo: Services/Technology sector46
Services/Technology
Bora Brasil

Bora Brasil

4 hours

62 employees using it; an average of at least 4 hours saved per week; about 120 hours per week given back to the group

An AI office powered by Claude, built on the group's own data

Other / not statedClaudeRead →
Illustrative photo: Logistics sector47
Logistics
AT

Alfa Transportes

1%

About 4,000 work hours saved per month; only 1% of documents go to manual review

Real-time validation of delivery receipts with AI

Other / not stateduMov.me AIRead →
Illustrative photo: Logistics sector48
Logistics
MBRF

MBRF

5%

Pilot with 16,000 deliveries: 5% fewer delays en route and routes completed about 7% faster

AI for resequencing delivery routes

Other / not statedNão informadoRead →
Illustrative photo: Logistics sector49
Logistics
Prestex

Prestex

30%

30% resolved without human intervention; response time cut from hours to under 15 minutes in six months

AI agent for customer service

Other / not statedHubSpot (agente de IA)Read →
Illustrative photo: Public Sector sector50
Public Sector
PD

Prefeitura de Rio Verde (GO)

40%

64,975 requests handled since January 2026; 40% of requests resolved without human intervention

Unified AI chatbot service covering 24 municipal departments

Other / not statedNão informadoRead →
Illustrative photo: Public Sector sector51
Public Sector
PD

Prefeitura de Belo Horizonte

More than 57 thousand

More than 57,000 chats handled in three months

Bel, an AI-powered citizen service tool

Other / not statedNão informadoRead →
Illustrative photo: Finance sector52
Finance
Verocard

Verocard

95%

Analysis time cut from 12 hours to 30 minutes (95% faster); operating costs 30% lower

Analysis of public procurement notices with generative AI and RAG

AWSAmazon Bedrock, SageMakerRead →
Illustrative photo: Retail sector53
Retail
Pernambucanas

Pernambucanas

80%

80% less manual review in fraud identification; more than 10,000 documents per day

AI for data extraction and document fraud detection

GoogleVertex AI, Vision AIRead →
Illustrative photo: Finance sector54
Finance
O

OpenCo

About 95%

About 95% of alerts resolved autonomously; average resolution time 75% shorter (from 12 to about 3 minutes)

AI agents that resolve infrastructure alerts (Amazon EBS) by following runbooks

AWSAmazon BedrockRead →
Illustrative photo: SMB sector55
SMB
MC

Maribel Clean

80%

Daily sales 5x higher; 80% of conversations resolved without a human; about 6 hours saved per day (company data)

WhatsApp agent that handles quotes, scheduling and late-night inquiries for an upholstery cleaning company in Brasília

Other / not statedMeta Business Agent (WhatsApp)Read →
Illustrative photo: Retail sector56
Retail
Osklen

Osklen

3.39%

Abandoned cart conversion up from 3.39% to 18.18%; R$ 453,000 in incremental revenue in 30 days

AI agents on WhatsApp for support, post-sale service and cart recovery

Other / not statedVTEX CX Platform (AI Agents)Read →
Illustrative photo: Retail sector57
Retail
Pit Bull Jeans

Pit Bull Jeans

WhatsApp's share of e-commerce sales doubled; customer service team reduced from 50 to 9 people

WhatsApp AI agent that handles triage, order status and cart recovery

Other / not statedOmniChat (Whizz Agent)Read →
Illustrative photo: Construction sector58
Construction
JC

Jotanunes Construtora

90%

Time to find a procedure cut from 5 minutes to 30 seconds (90% less)

Oráculo, a Teams agent that answers questions about technical procedures and construction standards

MicrosoftCopilot StudioRead →
Illustrative photo: Retail sector59
Retail
Grupo Boticário

Grupo Boticário

Up to 80%

Up to 80% autonomous resolution of operational requests; 90% of direct sales leads qualified by AI

In-house platform with more than 30 agents across the reseller journey

OpenAIOpenAIRead →
Illustrative photo: SMB sector60
SMB
NC

Nexo Contabilidade

About 40 hours

Monthly close brought forward by two days; about 40 hours per month given back to the team

AI for accounting close, customer service and document collection

Other / not statedMetaware (IA)Read →
Illustrative photo: SMB sector61
SMB
SC

São Caetano Assessoria Contábil

50%

50% higher service capacity

AI for WhatsApp customer service at an accounting firm

Other / not statedSleekFlow (IA)Read →
Illustrative photo: SMB sector62
SMB
S

Syhus

25%

660 hours per month freed up; 25% growth without expanding the team

AI to automate invoice checking and accounting routines

Other / not statedNão informadoRead →

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