Back-office, content moderation and AI data
Back-office, content moderation and AI data — Synergy Growth, Belvédère, Tunis.

Three families of activity

Back-office management

Everything handled asynchronously, without direct contact with the end customer, yet determining the perceived quality of your service.

  • Entry, verification and updating of customer records
  • Processing of orders, invoices and delivery notes
  • Document verification and compliance checks
  • Data reconciliation across systems
  • Shared inbox and ticket queue management

Content moderation

Applying your editorial rules to user-generated content, with the consistency this kind of work demands.

  • Moderation of comments, reviews and posts
  • Product listing verification on marketplaces
  • Compliance checks on ads and advertising content
  • Report handling and appeals queue management

Data annotation for AI

Model quality depends directly on training data quality. This is methodical human work that should not be outsourced casually.

  • Image and video labelling, bounding boxes, segmentation
  • Text annotation: named entities, intents, sentiment
  • Audio transcription and annotation
  • Evaluation and ranking of generative model outputs
  • Quality control and adjudication of annotator disagreements

Quality control is the core skill

On these activities the difficulty is not producing volume: it is holding quality steady across tens of thousands of processed units. Our approach rests on three mechanisms.

MechanismPrincipleUsed for
Blind double processingTwo operators handle the same unit without seeing each otherCritical data, AI annotation
Inter-annotator agreementStatistical measure of judgement convergenceAnnotation, moderation
Control samplingReview of a defined percentage by a senior validatorBack-office, routine volume
Disagreement adjudicationA third level decides and enriches the guidelinesAll scopes
A methodological point: a low inter-annotator agreement rate does not always indicate a team problem. Very often it signals that the guidelines themselves are ambiguous. We systematically escalate these cases rather than absorbing them silently — that is what improves your reference framework.

Moderation: our position on sensitive content

Moderation exposes people to content that can be difficult. We treat this as an employer responsibility, not an operational detail.

  • Explicit prior disclosure to candidates about the actual nature of the content handled
  • Task rotation to limit continuous exposure to the hardest queues
  • Psychological support available to the teams concerned
  • Declining certain scopes. We turn down extreme content moderation work where we could not guarantee adequate support.

Security and compliance

These activities almost always involve personal data. The framework mirrors our other services: Standard Contractual Clauses, a detailed processing agreement, encryption in transit and at rest, access segregation, locked workstations without local storage, and logging.

For the most sensitive scopes we set up restricted-access dedicated rooms, physically separated from the main floor, with named access control and a ban on personal devices.

Billing models

ModelSuited toWatch out for
Per dedicated positionRegular, predictable volumeSimplest to manage budget-wise
Per processed unitHomogeneous, well-defined tasksRequires a precise definition of the unit
Capacity with volume commitmentSeasonal activityDefine overage terms upfront

We steer you towards the model that fits your activity, including when it is not the most advantageous for us short term. Per-unit billing on heterogeneous tasks always ends in dispute.