Data and AI
Turn your company data into decisions and AI that work for you
We integrate your data sources, build reliable dashboards and apply artificial intelligence to support, sales and operations, with governance and privacy built in from the start. Less guesswork, more evidence-based decisions.
BI and dashboardsData integrationApplied AIAutomationPrivacy and governance
Integrated data
Applied AI
Insight to decide
4layersCollection, base, analysis and AI
12workstreamsFrom assessment to AI in production
6stepsFrom assessment to continuous evolution
Privacyfrom the startGovernance built into the project
Concepts and practices we apply
Data warehouseETL / ELTBIKPIs and OKRsData lakeMachine learningGenerative AIRAGPrivacy complianceData governanceAttributionDashboardsAPIsData quality
What it is
What Data and AI means for businesses
Data and AI is the set of practices that turns information scattered across spreadsheets, systems and platforms into reliable indicators and intelligent automations. It means integrating sources, organizing the data base, analyzing with BI dashboards and applying artificial intelligence, such as assistants and predictive models, to real processes. The goal is not to have more data, but to decide better and save time.
Data that becomes decisions
Clear sales, marketing and operations indicators in one place, with the same definition for every team.
AI applied to the business
Assistants, classification, summaries and forecasts tied to your processes, not a loose tool with no context.
Governance and privacy
Who accesses what, where the numbers come from and how personal data is protected, defined from the start.
Deliverables
12 workstreams of a Data and AI project
From strategy to operations, we handle the data base, dashboards, AI and governance, so information works for your business every day.
01
Data assessment
We map sources, indicators, pain points and maturity to define where to start and what returns value fastest.
Assessment02
Source integration
We connect CRM, ERP, website, ads, spreadsheets and support channels through APIs or automatic routines.
ETL / ELT03
Data warehouse and data lake
A central, organized base, in our cloud environment or yours, ready for analysis.
Storage04
Modeling and quality
Standardization, deduplication and business rules so everyone looks at the same number.
Quality05
Dashboards and BI
Sales, marketing, finance and operations dashboards that update automatically and are easy to read.
BI06
Marketing and sales analytics
Funnel, cost per lead, sales source and campaign return, with GA4 and attribution properly set up.
Analytics07
First-party data and segmentation
A single customer view from your own data, to segment, nurture and personalize with consent.
CDP08
Applied generative AI
Assistants that answer based on company documents and data, summarize, draft and support customer service.
Generative AI09
AI automation
Flows that read, classify and route messages, documents and leads, connected to your systems.
Automation10
Predictive models
Demand forecasting, purchase propensity and churn risk, when the data allows it.
Machine learning11
Governance, security and privacy
Access control, legal bases, consent, retention and audit trail for responsible use of data.
Governance12
Operations and evolution
Routine monitoring, cloud cost control and continuous improvement based on real usage.
OperationsLayers
Four layers of a data-driven operation
Each layer depends on the previous one. That is why we start with the base and only then apply AI, not the other way around.
01
Collection
Connect the sources: systems, website, ads, support and spreadsheets, with tracking properly configured.
02
Base
Centralize, standardize and protect data in a single environment, with clear rules and verified quality.
03
Analysis
Turn the base into dashboards, indicators and reports that answer the business questions.
04
AI
Apply assistants, automations and predictive models on reliable data, with human oversight.
Without a reliable base, AI only speeds up mistakes. With one, it becomes a competitive advantage.
Comparison
Loose spreadsheets, a standalone BI tool or a complete Data and AI project?
| Spreadsheets and manual reports | Alliances Data and AI | Just a BI tool | |
|---|---|---|---|
| Data sources | Manual typing and exports | Integrated and updated automatically | Depend on whoever feeds them |
| Trust in the numbers | Different versions per person | One definition per indicator | Depends on the modeling done |
| Artificial intelligence | Out of reach | Assistants and automations tied to your data | Usually not included |
| Privacy and compliance | Loose files, no control | Role-based access and defined governance | Setup left to the customer |
| Marketing and sales | Isolated, late analysis | Funnel, source and return connected to the CRM | Dashboard with no action plan |
| Operation after the project | Monthly rework | Continuous monitoring and evolution | License with no follow-up |
Does your data already answer your business questions?
Tell us how it looks today. We show where the BI and AI opportunities are.
From source to decision
How information travels through the project
Each step has an owner and a verifiable deliverable. That way you know where each number comes from and what the AI is using to answer.
Sources
→Integration
→Base
→Analysis
→AI
→Decision
Reliable data
Base
Quality rules and a single, documented definition for each indicator, available to the team.
Live dashboards
View
Dashboards updated automatically, by area and by role, instead of reports built by hand.
AI with context
Application
Assistants that use company documents and data to answer, with sources cited and human review.
Privacy by design
Governance
Role-based access, minimized personal data and usage logs from day one.
AI delivers value when it knows your business. The data base is what makes that possible.
Quick assessment
Find out where to start in 4 questions
Answer quickly and send the answers straight to our team via WhatsApp or the form. Nothing is stored at this step.
Question 1/4
What is your main goal?
Question 2/4
How is your data today?
Question 3/4
Which area starts first?
Question 4/4
When do you want to start?
Summary
Done! Just send it
Send your answers to our team and get a personalized recommendation.
How it works
6 steps from assessment to continuous evolution
Assessment and goals
We understand the business, the questions that need answers, the data sources and the current maturity level.
Architecture and governance
We design the base, integrations, role-based access and privacy rules before building.
Integration and base
We connect the sources, standardize the data and validate quality with the responsible teams.
Dashboards and analysis
We build the agreed dashboards and indicators, with a clear definition of each number.
AI and automation
We apply assistants, automations and, when it makes sense, predictive models, always with human oversight.
Operation and evolution
We monitor routines, measure usage and prioritize the next deliverables based on return.
We start small, with one indicator or one AI use case, prove the value and only then expand.
What you get
Reliable data and AI applied to real processes.
- Assessment with priorities and delivery plan
- Integrated, documented data sources
- BI dashboards by area and access role
- Indicator dictionary defining each number
- Correct GA4 and tracking setup
- AI use cases with human oversight
- Access policy and privacy best practices
- Training so your team can use the dashboards
Who it is for
Alliances Data and AI serves:
- Companies with data in spreadsheets and several unconnected systems
- Marketing and sales teams that want to measure real return
- Managers who need reliable dashboards to decide
- Businesses that want to use AI in support, sales or internal routines
- Educational institutions tracking enrollment, conversion and retention
- Anyone who needs to organize data to meet privacy rules
Glossary
10 data and AI terms explained simply
The vocabulary that shows up in any project in the field.
BI
Business Intelligence: tools and practices that turn data into dashboards and reports for decision-making.
Data warehouse
A central, organized base that gathers data from several sources for analysis.
Data lake
A repository that stores raw data in many formats for later use.
ETL / ELT
Routines that extract, transform and load data between systems.
KPI
Key performance indicator: the measure that shows whether a goal is being met.
CDP
Customer data platform: gathers each person's history into a single view.
Attribution
A method to identify which channels and campaigns contributed to a sale.
Generative AI
Models that generate text, images or code from instructions.
RAG
A technique where AI consults company documents before answering, reducing errors.
Data governance
Rules about who accesses, changes and is accountable for each piece of data.
To bring in campaign data, see Paid Traffic and SEO and Site Optimization. To combine attraction and sales with automation, see Inbound and Outbound.
Ready to decide with data and AI?
Request an assessment and receive a plan with priorities, steps and timelines.
Market references
The platforms that lead in data and AI
We work with the leading platforms in each layer, chosen for your project, budget, team and privacy requirements, without locking you into one brand.
BI and visualization
Storage and processing
Artificial intelligence
Brands mentioned belong to their owners and are shown as a market reference. The technology is defined in each project.
Frequently asked questions
Questions about Data and AI
Where do you start a data project?
With an assessment: we define the questions the business needs answered, map the sources and choose a first indicator or use case. Starting small lowers risk and shows value quickly.
Do I need a lot of data to use AI?
Not always. Assistants based on your documents work with far less data than predictive models. We assess what your data allows and recommend what makes sense, without promising what is not feasible.
Is my data safe?
We apply role-based access, personal data minimization and usage logs. When the project requires it, we use a private environment and models that do not train on your data. Details are set in the contract.
Which tools do you use?
We choose by need and budget: tools such as Looker Studio, Power BI, Tableau or Metabase for dashboards, and BigQuery, Snowflake or dedicated databases for the base. We explain the choice in the proposal.
Will AI replace my team?
Our focus is removing repetitive tasks and supporting decisions, with human oversight at critical points. The goal is for your team to achieve more, not to be replaced.
Do you handle privacy compliance?
We apply best practices in data projects, such as legal bases, consent, retention and access control. Full compliance depends on company processes, and we can support it with our IT consulting.
Do data and accounts stay in my company's name?
Yes. We recommend, and agree in the contract, that accounts, databases and dashboards stay in your company's name, so you keep control of what was built.
Do you follow up after delivery?
Yes. We offer routine monitoring, dashboard maintenance and continuous evolution, so the data stays reliable and the AI stays useful.
Page updated in November 2026.
Contact us
Request your data and AI assessment
Tell us what you want to measure or automate. A specialist will get back to you with priorities, steps and a recommendation for the best path.
- Priorities and first use cases
- Scope, steps and timelines
- Proposal tailored to your business
atendimento@alliances.com.br+55 11 98603-7462