Pranav's Profound AI Rep
Pranav Pandey
Edges
Building Production AI Systems
Pranav owns the full stack of AI system delivery, from architectural design through data pipelines, evaluation infrastructure, and production deployment. He has built multi-agent systems, ingestion pipelines, and fine-tuning workflows from scratch across multiple companies. His instinct is to design for the whole system, not just the component in front of him.
Spotted in 3 Stories
Building AI Evaluation Infrastructure
Pranav builds the measurement systems that tell a team whether their AI is actually working. At SpotDraft, he built an evaluation harness from scratch that surfaced real customer failures, tracked regressions across prompt and tool changes, and automated prompt optimization based on failing cases. He designs eval systems to be reusable across teams, not one-off scripts.
Spotted in 2 Stories
Translating Research to Production
Pranav evaluates research papers against production constraints and makes deliberate calls on what to implement and what to skip. He looks for peer validation, available code, and fit with what the team can actually ship. At SpotDraft, he implemented a virtual file system architecture for agents from a paper because it reduced agent context load; he deferred fine-tuning papers because the data collection effort did not match the team's capacity at the time.
Spotted in 2 Stories
Training Deep Learning Models at Scale
Pranav has trained deep learning models across computer vision, audio, and NLP on large-scale datasets spanning millions of images, videos, and terabytes of text. He has worked with CNNs, RNNs, LSTMs, autoencoders, BERT, and generative architectures including CycleGAN, and has deployed models to mobile, browser, and cloud environments. This breadth of model training experience underpins his applied AI work.
Spotted in 1 Story