Process Supervision (PRM800K) Step-Level Scoring
📜 Domain-Expert Human Workforce Credentials
Unlike crowd-sourced platforms, Blue Projects deploys verified domain specialists to prevent hallucinations in frontier AI models:
Core RLHF & Reasoning Capability Lines
🧠 Process Supervision & Code Reasoning
Step-by-step verified reasoning trajectories, step-level rewards (+1/-1), and execution-checked code debugging.
View Specifications →⚖️ Domain-Expert Legal & Tax RLHF
Statutory legal reasoning and tax code compliance preference pairs annotated exclusively by Bar-certified lawyers & CAs.
View Specifications →🛡️ Adversarial Red Teaming & AI Safety
Multi-turn prompt injection, jailbreak resistance auditing, and safety benchmarking under EU AI Act guidelines.
View Specifications →🩺 Surgical & Medical Expert Grounding
DICOM 3D volumetric segmentation and laparoscopic surgical phase classification audited by radiologists.
View Specifications →🎙️ Indic Multilingual Voice & Speech RLHF
48kHz studio audio transcriptions and dialect preference datasets across all 22 officially scheduled Indian languages.
View Specifications →🤖 Agentic Trajectory & Robotics Reasoning
50Hz HDF5 kinematics trajectories and dual-arm manipulation control policies for humanoid physical AI models.
View Specifications →PyTorch DPO Preference & Process Supervision Loader
Python 3.10+# PyTorch Legal / Tax DPO Preference Pair & PRM Loader
import json
import torch
class ExpertRLHFDataset(torch.utils.data.Dataset):
def __init__(self, jsonl_filepath):
with open(jsonl_filepath, 'r', encoding='utf-8') as f:
self.records = [json.loads(line) for line in f]
def __getitem__(self, idx):
item = self.records[idx]
return {
"prompt": item["query"],
"chosen": item["chosen_cot_with_statutory_citations"],
"rejected": item["rejected_response"],
"fleiss_kappa": item["annotator_consensus_score"] # >0.91
}
Configure Your RLHF / Reasoning Alignment Dataset
Specify your target domain, preference tuple volume, and evaluator credential requirements. Our engineering team responds within 24 hours.