AI automation built around the workflow you already use · Recruitment · QA & Compliance · Business Operations
TRUST · SECURITY · RESPONSIBLE AI

Your confidential data should stay confidential.

AI automation often touches the information businesses care about most: candidate records, customer data, commercial documents, SOPs, audit evidence and internal communications. Vorlo designs every production workflow around controlled access, minimum necessary data and visible human accountability.

Our default design position

Your data is there to run your workflow — not to become someone else’s asset.

CLIENT DATA REMAINS CLIENT DATAMINIMUM ACCESSHUMAN CONTROLTRANSPARENT DATA FLOW
No shared-model training by Vorlo

Vorlo does not use client confidential information to train a shared Vorlo AI model. If a project ever required a different arrangement, it would require explicit agreement.

Minimum necessary data

We design workflows to process only the data needed for the defined task and avoid unnecessary copying, broad access or indefinite retention.

Least-privilege connections

Integrations should use the minimum permissions supported by the client’s systems, with access scoped to the workflow wherever practical.

Third parties are visible

If a workflow uses an AI model, automation platform, cloud service or other subprocessor, that dependency should be identified as part of the solution design.

Human approval where it matters

Hiring decisions, compliance conclusions, external communications and other consequential actions can include approval gates and exception routing.

Retention is intentional

We agree what must be retained, what can be deleted and where records should live instead of allowing temporary workflow data to accumulate indefinitely.

See the data path

We should be able to show you where your information goes.

Before a sensitive workflow goes into production, the architecture should be understandable enough for the customer to review. A typical design is deliberately simple:

01 · YOUR SYSTEMApproved source

ATS, SharePoint, Drive, CRM, inbox or another client-approved source.

02 · MINIMUM DATAOnly what the task needs

Limit fields, documents and permissions where technically possible.

03 · PROCESSINGAgreed tools/providers

The services involved are identified rather than hidden behind “AI”.

04 · CONTROLReview & audit trail

Important actions are approved, logged or escalated as required.

05 · SYSTEM OF RECORDBack to your environment

Outputs return to the appropriate client-controlled business system.

What customers can ask for

Trust should be reviewable before deployment.

For production workflows handling confidential or personal data, we can document the controls and dependencies so you know what is being connected before access is granted.

DATA FLOW

Architecture & data-flow map

Systems connected, data moving between them, where AI is invoked and where outputs are stored.

PROCESSORS

Provider / subprocessor list

Identify third-party services required by the proposed workflow so customers can review them.

ACCESS

Permissions & credentials plan

Define how access is granted, who controls credentials and what minimum privileges are required.

RETENTION

Retention & deletion approach

Agree which records need to persist and where temporary processing data should be removed.

Recruitment

Candidates are people, not rows in a database.

Recruitment automation can involve personal data and, in some use cases, AI systems used to analyse or filter applications may fall into the EU AI Act’s high-risk category. Our default commercial position is therefore to automate coordination and administration while preserving meaningful human oversight over consequential recruitment decisions.

Human decision ownershipRecruiters retain accountability for submission, rejection and hiring decisions.
Purpose-limited useCandidate data is used for the agreed recruitment workflow, not unrelated reuse.
Reviewable outputsAI suggestions are presented as assistance, not unquestionable decisions.
Escalation pathsAmbiguous, sensitive or low-confidence situations can be routed to a person.
Standards & regulation

Designed with recognised privacy and AI governance principles in mind.

Our approach is informed by GDPR principles such as purpose limitation, data minimisation, storage limitation, integrity/confidentiality and privacy by design, together with human-oversight concepts relevant to the EU AI Act.

Vorlo does not claim ISO 27001, SOC 2, ISO/IEC 42001 or other certifications unless and until those certifications are formally obtained. Design alignment is not the same as certification.

Design references
  • GDPR privacy by design / default
  • GDPR data minimisation & security
  • EU AI Act human oversight awareness
  • ISO/IEC 42001 governance principles
  • Client-specific security requirements