Mapping
Starting from the reported problem, we map business rules, data sources, and metrics, and define with your team the baseline against which results will be measured. An initial version of the platform is already up and running.
Artificial Intelligence and Knowledge Engineering, together.
Our commitment is to make your operation more efficient: reduce repetitive tasks, save working hours, and free your team for activities that require analysis, decisions, and business knowledge.
Starting from the reported problem, we map business rules, data sources, and metrics, and define with your team the baseline against which results will be measured. An initial version of the platform is already up and running.
Our engineers work alongside the people who know the operation, put the solution to use with real data, and measure results against the baseline.
We adjust rules, models, and workflows based on errors found and user feedback until the criteria defined in step 01 are met.
The platform becomes part of the organization’s daily routine, with human review of decisions that require accountability and continuously monitoring and evaluating its quantitative and qualitative impact.
Based on results and your team’s priorities, we decide where to go next: improve the solution, broaden its reach, or automate new processes. Each next step considers the potential to save hours, reduce repetitive tasks, and improve operations.
We follow recognized practices for personal data protection, cybersecurity, and data governance, aligned with ISO/IEC 27001 and the NIST Cybersecurity Framework 2.0, to protect the confidentiality, integrity, and availability of our services.
Data in transit is protected by TLS 1.2 or 1.3; stored data and backups are encrypted with AES-256, with keys managed separately from the data.
Multifactor authentication for all platform access, least privilege, and individually assigned credentials for people. Service accounts use secrets stored in a vault, with regular rotation and minimal scope.
Business continuity and disaster recovery plans, with automated, immutable backups. Recovery objectives (RPO and RTO) are defined by contract, and restoration is tested periodically.
Environments are segregated in private networks, with restrictive firewall rules, continuous monitoring, and intrusion detection.
Continuous security updates and only systems with active vendor support in the environments we manage.
Tamper-protected audit trails with synchronized timestamps record who accessed what, when, and with what outcome, supporting the accountability required by Brazil’s General Data Protection Law (LGPD).
Each new processing activity begins with an assessment of purpose and risk. We use only the data needed, pseudonymize whenever analysis does not require identification, and configure everything by default with the lowest possible visibility and retention. Data lineage enables us to respond to requests for access, correction, and deletion.
A tested response plan, with client notification within the contractual timeframe, enables clients to meet their obligation to notify Brazil’s data protection authority (ANPD) and data subjects.
Client data is not used to train third-party models or models for other clients. With external providers, we preferably contract for services with no data retention; whenever possible, models run within the organization’s own environment.
Data remains under the organization’s control and jurisdiction: stored in Brazil by default, or within the client’s own environment, and accessible only to those the client authorizes. No personal data is transferred abroad without a legal basis provided by the LGPD and the client’s authorization.
Data, domain models, and results belong to the client and can be exported at any time in open, interoperable formats.
Tell us about the problem you would like to solve. Our engineers will get in touch.