AI changes the world. We make sure it’s for the better.
Sigma was founded on a belief that artificial intelligence must serve people — not replace or misrepresent them. We build human-centric AI by sourcing, annotating, and evaluating training data that reflects human values, behaviors, and cultural contexts.
We care about the how as much as the what — how models make decisions, how they interpret emotion, and how their training data influences real-world impact. With every project, we balance machine efficiency with human judgment, because GenAI doesn’t just automate — it communicates.
What human-centric AI means in practice
We don’t treat “human in the loop” as a buzzword. It’s a design principle that shapes how we hire, annotate, validate, and deliver.
Human understanding drives better model behavior
Our annotators do more than label data — they teach machines how to communicate clearly, respectfully, and contextually. We guide LLMs to understand user intent, respond with empathy, and handle ambiguity that machines alone can’t decode.
→ Learn more: Conversational AI for customer service
Automation supports, but doesn’t replace, judgment
We use pre- and post-processing tools to boost throughput — then deploy human reviewers at the critical points where nuance matters. From summarization to tone labeling to complex reasoning, our teams correct where models fall short.
→ Learn more: The fundamentals of audio annotation
We reject one-size-fits-all crowdsourcing
Crowdsourcing introduces inconsistency, rework, and bias. At Sigma, every annotator is vetted, trained, and matched by project needs, from linguists and educators to clinicians and creatives. Our long-term workforce model ensures quality, reliability, and deep contextual knowledge.→ Learn more: Named Entity Recognition (NER): an introductory guide
Bias isn’t just technical — it’s human
We address bias at the source: dataset design, demographic coverage, and annotation diversity. Our inclusive hiring ensures the people who shape AI reflect the people AI will serve.
- Our annotators come from 100+ countries
- We speak 300+ languages and dialects
- 72% of our annotators are women
We work with local orgs to include people in rural, disabled, and underrepresented communities
Balanced data is essential. So is balanced perspective in the people who interpret it. We believe inclusion isn’t just ethical — it’s the foundation of quality.
→ Learn more: Addressing data challenges with AI-powered solutions
Striking the right balance: humans + machines
In generative AI, the best results come from smart automation plus expert human review. Here’s how Sigma gets it right:
- We automate what machines do well
(e.g. formatting, filtering, first-pass tagging) - We escalate what machines miss
(e.g. sarcasm, intent, cultural context, tone drift) - We optimize throughput without sacrificing meaning
By supporting annotators with pre-labeled suggestions and intelligent QA, we reduce rework and improve consistency
→ Learn more: Synthetic data: types, challenges, and benefits
The future of AI is collaborative
As models become more agentic — planning, conversing, learning across time — human-in-the-loop systems become even more essential. Machines need help understanding not just what to say, but how and why to say it.
That’s why we don’t just annotate. We edit, evaluate, and guide the voice, values, and experience of tomorrow’s AI.
Our human-centered mission is this:
To ensure the next generation of AI is not only capable, but also more compassionate, responsible, and relatable.