Rework
Processes and answers get rebuilt over and over for lack of a single source of truth.
Praxian AI Center
Enterprise Intelligence Engineering
Enterprise architecture for Artificial Intelligence, Knowledge Engineering, Intelligent Agents and Business Automation.
- Structured knowledge
- Agents under governance
- Explainable decisions
We turn business knowledge into Operational Intelligence — connecting people, processes, data and AI in architectures built to evolve continuously.
- Architecture Multi-agent, RAG and private AI
- Knowledge Corporate graphs and ontologies
- Operation End-to-end processes
- Governance Traceable decisions
Who we are
Praxian AI Center
Artificial Intelligence with method, engineering and responsibility.
Praxian AI Center was created to connect business consulting experience to the new generation of Artificial Intelligence solutions.
We bring together business knowledge, engineering, data, automation and AI to help companies that want to transform processes, build intelligent agents, integrate new technologies and build operations ready for a market increasingly driven by computational intelligence.
Our work builds on the experience of PRAXIAN, a company founded in 1999 by professors linked to the graduate and MBA programs of the University of São Paulo, with a track record of hundreds of consulting, research and market intelligence projects.
Human knowledge, method and governance, accelerated by Artificial Intelligence.
A new unit born from a history that already exists
Praxian AI Center comes to market in September 2026 as a new unit specialized in Artificial Intelligence.
We are not starting from scratch.
We were born inside a business environment that already works with consulting, research, strategy, training, market intelligence and project development.
That origin directly shapes our view of AI. We don't believe corporate projects should start with the tool.
We start with the questions:
- 01 What problem needs to be solved?
- 02 What process needs to be improved?
- 03 What data exists?
- 04 What risks need to be controlled?
- 05 How will this solution be operated, audited and evolved?
The technology comes after.
The problem
Most companies already have data. Few have structured knowledge.
Without context, governance, integration or organizational memory, accumulated data doesn't translate into better decisions — and Artificial Intelligence inherits that disorganization.
- Data without context
- Scattered knowledge
- Decisions without memory
Why doesn't having data mean having operational intelligence?
- Enterprise knowledge
- Context and memory
- Orchestration and agents
- Governance and oversight
- Operational decision
Slow decisions
Scattered information delays decisions that should be immediate.
Dependence on people
Critical business knowledge stays locked in the heads of a few specialists.
Scattered information
Systems, documents and teams operate in silos that don't talk to each other.
Low AI utilization
Without structured context, AI models deliver generic, unreliable answers.
Corporate discipline
Data & AI Engineering
We organize corporate knowledge so people and intelligent agents share the same understanding of the business.
We build a knowledge layer able to connect documents, processes, systems, business rules and specialists into an architecture ready for Artificial Intelligence.
PDF
DOCX
XLSX
API
knowledge layer
AI comes at the end of that chain. First we need to make sure it has access to the right knowledge.
Every Artificial Intelligence needs Architecture.
Technical foundation
Enterprise AI Architecture
Every enterprise Artificial Intelligence initiative needs architecture. Before any model or agent, we design the structure that guarantees performance, security and governance at scale.
Where does each architecture layer act on knowledge?
- Enterprise knowledge
- Context and memory
- Orchestration and agents
- Governance and oversight
- Operational decision
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INPUT / KNOWLEDGE
Enterprise knowledge
Documents, systems and processes enter as raw source material, with no hierarchy.
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CONTEXT / MEMORY
Context and memory
Information gains semantic structure and a retrievable history.
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ORCHESTRATION / AGENTS
Orchestration and agents
Tasks are distributed among specialized agents, under policy.
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GOVERNANCE / CONTROL
Governance and oversight
Every decision passes through control, an audit trail and approval.
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OUTPUT / DECISION
Operational decision
The result reaches the business with an end-to-end auditable trail.
Our methodology
An engineering discipline, not a one-off project
We don't start with the tool: we start with the business problem. Our own methodology combines strategy and project management, Requirements Engineering, architecture and Software Engineering, data and Artificial Intelligence, security and governance, change management and observability in one continuous cycle — from idea to POC, to MVP and to operation — with governance at every stage, turning corporate knowledge into faster, better decisions.
In what order does the engineering happen?
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Enterprise knowledge
Documents, systems and processes enter as raw source material, with no hierarchy.
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Context and memory
Information gains semantic structure and a retrievable history.
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Orchestration and agents
Tasks are distributed among specialized agents, under policy.
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Governance and oversight
Every decision passes through control, an audit trail and approval.
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Operational decision
The result reaches the business with an end-to-end auditable trail.
01
Strategic Diagnosis
We understand the business, objectives and executive priorities before any technical decision.
02
Knowledge and AI Architecture
We design the knowledge, data and AI foundation tailored to your business, with the rigor that sustains long-term decisions.
03
Development and Validation
We build every solution to the same standard of quality, security and testing before any delivery.
04
Deployment
We go into production with close support from the teams, ensuring real adoption.
05
Continuous Evolution
We track performance and evolve the solution continuously, alongside your business.
Practical application
Agentic AI
From a specialized assistant to a multi-agent architecture: agents that operate inside your business's real operation — sales, finance, legal, HR and customer service — multiplying specialists' capacity, with the governance that autonomy demands.
Practical application
Workflow Automation
End-to-end process automation, with human supervision where needed.
Customer Service
Intelligent support with full context on the customer and the business.
Document Intelligence
Automated understanding, classification and summarization of documents.
Sales Agents
Finance Agents
Legal Agents
Corporate Search
View more capabilities
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HR Agents
Support for recruitment, people management and development processes.
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Executive Agents
Summaries and analytical support for executive decision-making.
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Intelligent OCR
Extraction and structuring of data from physical and digital documents.
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Voice Agents
Voice interactions integrated with corporate processes and systems.
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Computer Vision
Image recognition and analysis applied to operational processes.
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Business Analytics
Indicators and analyses that support data-driven decisions.
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Process Mining
Discovery and analysis of real processes from company systems.
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Retail Data Mining
AI applied to sales data to increase conversion and average order value, in-store and in e-commerce.
Sustaining layer
Enterprise AI Operations
Few companies offer this layer. Putting an agent into production is only the beginning — we sustain the operation with monitoring, governance and continuous evolution.
AI Monitoring
Continuous tracking of model and agent behavior in production.
decisionauditable
- source retrieved
- policy applied
- human review
- decision logged
LLMOps
Language model lifecycle operated with engineering discipline.
active agents
- Sales running completed
- Finance awaiting approval approved
- Legal completed queued
- Support queued running
Trust and compliance
Security, Privacy and Governance
Enterprise AI demands control.
Agents can access documents, databases, internal systems and take actions. That completely changes the level of responsibility of the project.
OWASP
Best practices against the main security risks in applications and LLMs — including Prompt Injection.
LGPD
Compliance with Brazil's General Data Protection Law (LGPD).
GDPR
Compliance with the European Union's General Data Protection Regulation.
Application and API Security
Protecting the applications and integrations that support agents and models in production.
Prompt Injection
Specific defenses against instruction manipulation and improper agent behavior.
Authentication and Authorization
Identity control and access permissions for every system and agent.
Principle of Least Privilege
Every agent and integration accesses only what is strictly necessary.
Audit and Traceability
A complete record of decisions and actions, from start to finish.
Human-in-the-Loop
Human oversight on the highest-impact, highest-risk decisions.
Operational Continuity
Planning to keep the operation stable even in the face of failures or incidents.
Security isn't a step performed after development. It's part of the architecture.
Technical foundation
Enterprise AI Architecture
Long-term vision
AI Enterprise Consulting
Not every business problem can be solved with software alone. Many organizations first need to understand processes, organize information, structure data, review responsibilities and prepare their teams for a new way of working. Praxian AI provides direct support to leadership, from defining Artificial Intelligence strategy, priorities and governance — with the same discipline as a business consultancy.
01 Strategy & portfolio
AI Strategy
Defining AI priorities aligned with business objectives.
Roadmap
Prioritized evolution plan, with clear short- and long-term milestones.
ROI
Return-on-investment models applied to AI initiatives.
Innovation Programs
Structured programs to explore new AI applications in the business.
02 Architecture & governance
Governance
Decision and accountability structure for enterprise AI use.
AI Maturity Assessment
Assessment of the current maturity stage in data, process and AI.
03 Operation & adoption
Executive Workshops
Structured sessions to align leadership and AI strategic vision.
Training
Enabling teams to work alongside intelligent agents and systems.
Change Management
Managing organizational transition to AI-supported operations.
04 Risk & compliance
AI Readiness Assessment
Diagnosis of organizational readiness to adopt Artificial Intelligence.
AI Infrastructure
AI Cloud & Infrastructure
The infrastructure needed to take AI from POC to production.
Praxian AI Center is building a services layer for companies that want to consume Artificial Intelligence without having to assemble in-house all the infrastructure needed to operate their projects.
Cloud Computing and Hosting
Environments ready for agents, APIs, applications, databases and services associated with AI projects.
Managed Infrastructure
Provisioning, configuration, updates, monitoring and upkeep of the operation's components.
LLM and Model Consumption
Integration and management of access to different AI models and services.
Tokens and Computational Capacity
Management of consumption, processing, sizing and cost tracking.
APIs and AI Services
APIs to connect applications, agents, models, corporate systems and external services.
Vector Databases and Pipelines
Infrastructure for RAG, embeddings, document ingestion, processing and data pipelines.
Observability, Security and Governance
Monitoring of consumption, latency, errors, agents, integrations, costs and behavior.
Dev, Test and Prod Environments
Separation between development, testing, staging and production.
Managed Services and Support
Technical follow-up of the infrastructure, applications and services associated with the operation.
AI as a Service
Integrated packages bringing together infrastructure, models, tokens, APIs, data, agents, security, governance and support.
- Infrastructure
- LLMs
- Tokens
- APIs
- Vector Database
- Agents
- Observability
- Security
- Governance
- Support
Integrations
An architecture that connects to what the company already uses
No enterprise AI architecture starts from scratch. We integrate the knowledge layer with the systems, platforms and tools that already sustain the operation.
L1
Cloud & Infrastructure
Microsoft
Azure
Google Cloud
AWS
Docker
Kubernetes
L2
Artificial Intelligence
OpenAI
Anthropic
MCP
L3
Data
Neo4j
PostgreSQL
SQL Server
Oracle
L4
ERP & CRM
SAP
TOTVS
Salesforce
Hubspot
L5
Communication
Slack
Teams
WhatsApp
L6
Productivity
SharePoint
Google Drive
L7
Integration
REST APIs
N8N
Praxian integrates and organizes the existing ecosystem. The architecture doesn't require replacing the entire stack.
Differentiator
Consulting doesn't end at delivery
Most consultancies end the relationship once the project is delivered. Our architecture was designed to evolve together with the business.
Traditional consultancies
Project
Delivery
End
Praxian AI Center
Knowledge Assessment
Enterprise Architecture
Deployment
Monitoring
Knowledge Evolution
Continuous Improvement
Business Growth
Continuous cycle
Training and certification
PraxianAI Academy & Certification
Certification isn't just knowledge — it's operational authority.
We train and certify our professionals through our own three-belt system, combining theoretical exams, proven projects, hands-on assessment and methodology adherence.
Green Belt
Supervised Executor
Executes well-scoped technical tasks — POCs, integrations, testing — within an already defined architecture.
Blue Belt
Engineer / Technical Lead
End-to-end technical responsibility: architecture, security, deployment and continuous operation of AI agents.
Black Belt
Architect / Accountable Consultant
Leads the full client cycle — from business diagnosis to the business case and critical architecture.
September 2026
Brazil Management Week 2026
Praxian AI Center comes to market discussing before selling.
Brazil Management Week 2026 will bring together experts from the United States, Europe, and Brazil for three days of discussions on the impacts and advanced applications of Artificial Intelligence in careers and businesses.
In addition to discussions with international professors and experts, the event will showcase case studies from companies already applying AI in their businesses, bringing concepts, experiences, and practical applications closer together.
- Agentic AI and the future of business operations
- AI and organizational transformation
- Artificial Intelligence governance
- Security and privacy in agents
- Data as AI infrastructure
- Human-in-the-Loop
- AI applied to business strategy
- Robotic AI
- Infrastructure and AI as a Service
- How to go from POC to production
Grupo Praxian
A Highly Qualified Team
Behind Praxian AI Center stands Grupo Praxian: a team that combines academic rigor, executive market experience, and delivery discipline across real-world AI projects.
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General DirectorRicardo Britto
PhD in Business Administration from FEA/USP, he is one of the most experienced Brazilian professors in International Business, serving as a representative of foreign institutions and foundations. At Praxian AI Center, he leads the unit's strategic vision, connecting that international experience to defining priorities, methodology and the continuous evolution of the AI solutions offered to clients.
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Financial DirectorDaniel Pitelli de Britto
PhD in Finance from POLI/USP, he devoted his career to financial and institutional management in higher education, in Brazil and abroad. At Praxian AI Center, he is responsible for the financial governance of AI projects — cost models, ROI and feasibility — and for structuring training programs to develop new AI talent.
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Director of Operations and ProjectsAldo José Brunhara
PhD in Business Administration from ESPM, he has more than 20 years of executive experience at multinational companies. At Praxian AI Center, he coordinates the integrated work between the architecture, engineering and governance teams, and directly guides client teams in leading their AI innovation and transformation projects.
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Associate Consultant in StrategyMaria Cecília Galante Porto
PhD in Business Administration from FEA/USP, she built a 25-year career in marketing and strategy, working across retail, consumer goods, educational services and business consulting. At Praxian AI Center, she serves as an associate consultant in Strategy and Decision-Making, applying that market experience to diagnosing and prioritizing AI initiatives for client companies.
01
PhDs from USP
A team with doctoral degrees from the University of São Paulo, pairing scientific rigor with hands-on AI project experience.
02
Market Executives in AI
Executives specialized in Artificial Intelligence, with extensive experience leading projects across Brazil, LATAM, and Europe.
03
Synergy and Real Delivery
A team with strong synergy and transparency, committed to measurable results — beyond the powerpoint.
FAQ
Frequently asked questions
How does the engagement process with Praxian AI Center work?
Five stages, governed end to end: diagnosis, architecture, development, deployment and continuous evolution. See the Methodology section.
How does Praxian handle the security and privacy of corporate data?
We design with governance, access control and private AI options — data and models stay under your company's control.
Do we need to replace the systems we already use?
No. Our architecture connects to what you already use — cloud, ERPs, CRMs and communication tools.
How long does a corporate AI architecture project take?
It depends on data maturity and operational complexity. Your timeline comes right after the strategic diagnosis.
Who leads the projects?
Grupo Praxian: specialists with academic training and executive experience in AI. See the Team section.
Ready to structure your company's Artificial Intelligence?
Schedule a strategic diagnosis with the Praxian AI Center team and discover the architecture path for your business.
Schedule a Strategic Diagnosis