Opportunity and feasibility assessment
Use cases ranked by value, data readiness, process fit, risk, adoption effort and measurable success criteria.
Solutions
AI and automation applied to measurable work.
Practical AI, document intelligence, copilots, agents and workflows designed around authorised data, human review and clear metrics.
Move from AI experimentation to a controlled use case with measurable operational value.
29 yearsof professional experience
300+projects delivered
Global deliveryfrom Brazil
Confidentialityand security
Continuoussupport
What is included
Concrete deliverables connected to the operating outcome.
Document AI and OCR
Classification, extraction, validation and workflow integration for technical and corporate documents.
Knowledge copilots and RAG
Controlled access to organisational knowledge with retrieval, citations, permissions and evaluation.
Integrated AI agents
Task execution across approved systems with explicit tools, limits, logs and human escalation.
Process automation
Rules, workflows, APIs and AI combined to reduce repetitive work and cycle time.
Responsible AI operations
Evaluation, monitoring, security, cost control, model lifecycle and incident response.
Delivery approach01 02 03 04
From business context to reliable operation.
Use-case and data assessment
Goals, users, constraints and risks are made explicit.
Prototype with evaluation criteria
Priorities, interfaces and success criteria become an executable plan.
Controlled integration and adoption
Small, testable releases reduce risk and make progress visible.
Monitoring and continuous improvement
Operational data and feedback guide the next investment.
Technologies and practicesGenerative AIRAGAI agentsOCRComputer visionWorkflow automationLLMOpsResponsible AI
Complete perspective
AI and automation applied to measurable work: strategy, implementation and measurable results.
When this work is relevant
Practical artificial intelligence and automation designed around authorised data, human oversight, operational integration and measurable business value. It is especially relevant when critical work depends on disconnected tools, manual controls, delayed information or technology that can no longer support growth.
ZERO-D assesses users, data, integrations, security, infrastructure, continuity and total cost before recommending a technology path. Existing systems that still create value can be preserved and integrated.
How results are measured
Success criteria are tied to the operating goal: cycle time, availability, adoption, quality, rework, cost, security or decision speed. The baseline, evidence source and target are agreed before implementation.
Documentation, observability, training and knowledge transfer support long-term ownership across locations and time zones. English-language collaboration is combined with delivery expertise from Brazil.
In-depth operation
From the everyday challenge to a sustainable platform.
Begin with the decision or task
A useful AI initiative starts with a specific task, decision or operating loss. The expected user, authorised data, human review and success measure are defined before technology selection.
This prevents prototypes that appear impressive but cannot be integrated, governed or trusted in daily work.
Data, integration and evaluation
Models require reliable context and access rules. Retrieval, prompts, tools and outputs are tested against representative scenarios, including failure and uncertainty.
Integration with documents, APIs and existing workflows turns a model into an operational capability rather than another isolated interface.
Operate AI responsibly
Production AI requires monitoring, evaluation, traceability, security, cost control and a clear escalation path for people.
Policies and technical controls evolve together as models, data and operating requirements change.
Practical application
Geological Drilling Platform
Operational data and specialist knowledge organised in a real-time platform, creating a reliable foundation for advanced analytics and intelligent assistance.
- Centralised geological data
- Concurrent wells and users
- Real-time operational dashboard
- History for analysis and traceability
Frequently asked questions
What international clients need to know.
How does ZERO-D select an AI use case?
We compare expected value, data readiness, integration complexity, risk, adoption and whether success can be measured in the operating process.
Can AI use private company information?
Yes, when authorised architecture, access control, retention, provider terms and privacy requirements are defined for the specific data.
Does an AI agent act without human review?
Only within explicitly approved tools and limits. High-impact or uncertain actions can require confirmation or escalation.
How are model quality and hallucinations managed?
Representative evaluations, retrieval quality, citations, structured outputs, monitoring and human review are combined according to risk.
Can ZERO-D integrate AI with existing systems?
Yes. APIs, events, document repositories and business applications are connected with observability and controlled permissions.
Next step
Start a conversation →Turn your scenario into a practical roadmap.
Share the context, initial scope and priorities with our team.