Train Safer, Smarter Models with Human Feedback
Align your AI with real-world expectations using Reinforcement Learning with Human Feedback (RLHF). Indika AI provides access to domain-trained reviewers at scale enabling precise labeling, evaluation, and refinement of model outputs with unmatched accuracy and context.
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60,000+
Annotators
100+
Model Types
50,000+
Training Hours
98%
Accuracy
Train
Smarter Models with Human insights
01
Expert Annotation at Scale
Your data is routed to a global network of 60,000+ trained annotators. These domain-specific professionals label complex data from clinical notes to financial records ensuring accuracy, consistency, and contextual relevance.
02
Preference-Based Ranking
Human reviewers rank model outputs on clarity, correctness, tone, and intent. These rankings feed RLHF pipelines to fine-tune AI models, aligning them with real-world expectations.
03
Real-Time Evaluation Loops
Models continuously undergo human evaluation to flag hallucinations, bias, factual errors, and compliance risks. This ongoing QA loop keeps AI outputs safe, accurate, and reliable.
04
Feedback-to-Fine-Tuning Pipeline
Collected human feedback is automatically structured into training signals, traceable and ready for iterative fine-tuning ensuring models improve continuously with every review cycle.
Why
Choose Indika for RLHF
Human-Guided Accuracy
Expert reviewers deliver precise, high-quality feedback.
Context-Aware Training
Integrate domain knowledge for nuanced, relevant outputs.
Bias & Error Reduction
Continuously detect and minimize inaccuracies.
Deployment-Ready Models
Fine-tuned for production-level performance and real-world use.
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