Acadify provides the curated, human-verified datasets needed to train models that excel in real-world scenarios. We specialize in high-fidelity SFT and RLHF data for San Francisco AI labs and global developers.
We deliver highly-curated datasets designed to solve specific reasoning bottlenecks in LLMs.
High-density repository-level data including complex pull request discussions, multi-file context tracking, and execution traces. Designed to train agents for autonomous bug fixing.
Subject-matter expert (SME) verified chains of thought for advanced physics, chemistry, and graduate-level mathematics.
Curated response pairs focusing on complex alignment constraints, safety guardrails, and instructional compliance.
Screenshot-to-action sequences and OCR-grounded layout analysis to train visually-aware GUI agents.
Synthetic data is a start, but production-grade models require grounding in reality. We bridge the gap by sourcing and synthesizing datasets based on real-world operational pressure.
Production-Grounded Traces: SFT data captured from high-stakes engineering and reasoning workflows.
Edge-Case Focus: We identify and simulate the "long tail" of real-world failures that lead to model drift.
SF-Standard Compliance: Data handling protocols that meet the security requirements of San Francisco's top AI labs.
We prioritize precision. Every Acadify dataset undergoes a multi-stage verification process by domain experts to ensure zero hallucinations in the training corpus.
Models trained on our expert-verified real-world traces reach performance milestones 30% faster than those using crowd-sourced data.
Common questions about our boutique data collection and quality assurance methods.