Five years, sixty-thousand experts, one mission

Reflecting on how Indika evolved from an annotation vendor into a data infrastructure partner for frontier AI programs.

We started in 2021 doing what most annotation vendors did: basic text and image labeling, priced by the task, delivered as a spreadsheet. It was useful work, and it built the foundation — a workforce, a QA process, a client base — but it wasn't a differentiated position. Any of a dozen vendors could do roughly the same thing.

2022–2023: scaling the workforce, not just the headcount

We grew to a 60,000-plus network over these two years, but the more important change was structural: we started building dedicated cohorts by domain instead of one undifferentiated labor pool. A clinical-annotation client and a retail-catalog client stopped drawing from the same queue.

2024: the RLHF pivot

As frontier labs' needs shifted from "label this data" to "tell us which of these two responses is better, and why," we built dedicated preference-ranking, red-teaming and rubric-design capabilities rather than trying to force RLHF work through our existing annotation tooling. That decision — treating RLHF as a distinct discipline, not a variant of labeling — is the one we'd point to as the inflection point.

2025–2026: becoming a data infrastructure company

Today the work spans data collection and curation, annotation, human feedback and evaluation, delivery infrastructure, and continuous quality monitoring — plus a specialist network for the domains that need real judgment, not just attention. We stopped thinking of ourselves as a labeling vendor once it became clear that the actual value we provide is making enterprise and frontier-lab data trustworthy enough to build on, at every stage from ingestion to production.