Image & Video Annotation
For image or video data that needs structured labels. Define objects, classes and sequence rules, then review an annotated pilot sample.
Explore service ↗SPECIALIST-LED AI DATA SERVICES
AI data services.
Human expertise.
Annotation, evaluation and quality review for international teams building AI systems. A focused service with direct founder involvement and clearly agreed deliverables.
12+ years of relevant professional experience · Direct founder involvement
SERVICES AT A GLANCE
Choose the work
your data needs.
Choose annotation for new visual labels, evaluation for model responses, or QA for existing annotations. A combined brief is welcome; scope and feasibility are reviewed directly with the founder.
LLM Evaluation
For AI responses that need human assessment. Agree on the evidence and rubric, then receive judgments with supporting rationales.
Explore service ↗Dataset Quality Assurance
For existing labels that need review. Agree on a sample and error categories, then receive findings linked to rules and next actions.
Explore service ↗EXPLORE THE WORK
Concrete examples.
Clear boundaries.
Every demonstration uses original synthetic content. Explore annotation, fictional response evaluation and a reasoned annotation correction.
See visual annotation
Object boundaries, semantic classes and consistent tracking identities.
Explore the workspace →“Do not add facts.”Compare two fictional responses against the same source.
Inspect a response comparison
Factuality, instructions and relevance with an explicit rationale.
Explore the assessment →Class mismatchFlag → Rule → CorrectionBoundary error
Follow an audit finding
Connect a flagged label to a guideline and a proposed correction.
Explore the review →WHAT YOU RECEIVE
Outputs with context.
Final scope, tools and export requirements are confirmed before work starts. The items below describe proposed deliverable types, not a promise of every format or integration.
Annotation & evaluation records
Task-specific labels or judgments, with the working structure and compatibility agreed before the pilot.
Review findings
Flagged ambiguities, quality observations and contextual notes appropriate to the service.
Documented decisions
Clarifications that make the agreed specification easier to apply and review.
QUALITY BY DESIGN
Agree on quality.
Then evaluate the work.
A focused pilot helps establish the task rules, review method and acceptance criteria. No generic accuracy promise replaces a task-specific agreement.
Discuss
Describe the data, intended use, existing workflow and constraints.
Pilot
Select a representative sample and define what the pilot should establish.
Calibrate
Resolve edge cases and align the quality criteria before extending scope.
Deliver
Complete the agreed work and review the outputs together.
PROJECT QUESTIONS
Clarity before
commitment.
Scope and suitability are reviewed directly with the founder.
Can we combine annotation, evaluation and QA?
Yes, a combined scope can be discussed. Each component needs clear inputs, outputs and acceptance criteria; availability and timing are assessed before commitment.
Is Altema a large annotation agency?
Altema is an independent, founder-led business. The service is built around direct involvement and transparent project scope, without claims of a large in-house workforce.
What is needed to estimate a pilot?
A high-level brief covering data type, intended task, approximate volume, guideline availability and timing is a useful starting point. Do not share confidential datasets in the initial form.
Are there fixed prices or guaranteed turnaround times?
Pricing and timing depend on task complexity, review needs and current capacity. They are discussed after the scope is understood; no universal rate or delivery promise is made.
START WITH A CLEAR SCOPE
Bring the challenge.
Let’s define the pilot.
Independent, founder-led delivery. Capacity, timing and requirements are assessed for each project.