Contents
Euman AI delivers enterprise-grade data operations for AI teams: consent-based data sourcing, meticulous human-in-the-loop labeling, rigorous model evaluations, and secure handover with complete provenance. We specialize in multilingual coverage and regulated industries. We bring new breadth and depth to training data and evaluations.
- Consent-first sourcing and licensed content partnerships
- Expert reviewers and calibrated rubrics for LLM evaluation
- Measured quality (gold tests, IAA, drift monitoring)
- Secure, auditable handover with datasheets and lineage
Models are reaching capability ceilings that can’t be solved with scale alone. Progress hinges on the quality of new human data—especially diverse languages, domains, and safety judgments. Africa provides an underrepresented richness of languages, contexts, and real-world tasks. Euman AI organizes this expertise with enterprise-grade process and governance.
Our data engine spans four managed stages, each with controls and evidence:
- Sourcing: consented collection programs, licensed content partners, and optional synthetic augmentation (clearly labeled).
- Labeling: calibrated annotators and SMEs, rubric-driven tasks, multi-pass review or consensus.
- Evaluation: task design, red-teaming, and safety test suites for LLMs and agents.
- Handover: encrypted delivery of structured data, datasheets, QC reports, and lineage attestations.
Euman AI runs consent-based programs and licensed content partnerships that align rights, compensation, and privacy with downstream AI usage. We avoid gray-area scraping and provide clear provenance for every asset.
- Documented consent and revocation paths
- PII minimization and data residency options
- Fair compensation and transparent terms
- Provider audits and periodic re-consent for long-lived programs
We support NLP (NER, classification, sentiment, translation QA), speech (transcription, diarization, accent coverage), and vision/OCR tasks (forms, boxes/polygons). For LLMs, we run preference data (RLHF/RLAIF), instruction-following checks, and safety evaluations via rubric-driven expert reviews.
- Expert-led calibration and pilot on small samples
- Two-pass review or consensus workflows
- Edge-case surfacing and continuous rubric refinement
Quality is measured and reported, not asserted. We track:
- Gold tests and reviewer calibration scores
- Inter-annotator agreement (IAA) and adjudication rates
- Error taxonomies and drift signals over time
- Turnaround time (TAT), throughput, and resolution latencies by task type
Handover includes a QC report, dataset datasheet, and lineage summary to ensure auditability.
We design for privacy and enterprise security:
- PII minimization and role-based access controls
- Encryption in transit and at rest; access logging
- DPAs, SOC-style controls, and confidentiality workflows
- Region-aware storage and data residency upon request
We uphold transparent labor standards: fair pay, training access, and wellness support. Reviewers can escalate concerns through independent channels. We avoid harmful tasks and provide safety briefings and debriefings as needed.
We recommend starting with a scoped pilot to de-risk assumptions and establish metrics.
- Define scope, success criteria, and constraints (NDA)
- Design tasks and rubrics; calibrate on a sample
- Execute with QA; report metrics and edge cases
- Review outcomes; propose production plan and scale targets
Engagements are structured for clarity and security:
- Pilot: fixed-scope, fixed-fee; clear deliverables and metrics
- Production: per-unit or per-hour pricing with quality SLAs and capacity plans
- Evaluations: per-task suite or subscription for continuous testing
- Banking: KYC/OCR datasets, fraud classification, multilingual chatbot evaluation
- Telecom: call intent/sentiment, spam/fraud detection, network log labeling
- AI labs: instruction-following checks, preference data (RLHF/RLAIF), red-teaming safety suites
- Evaluator marketplace with expert verifications
- Curated multilingual benchmark suites
- Deeper document-intelligence (OCR) programmatic QC
- Privacy-preserving annotation modes and secure enclaves
Ready to scope a pilot? We’ll sign an NDA and propose a 1–2 week plan with clear success metrics.
Euman AI • hello@eumanai.com