About Rencewise
What we do, how we do it, and why it matters.
Our Story
AI Handles the Volume, Humans Ensure the Quality
Technical conferences produce hundreds of presentations. Research papers accumulate faster than anyone can read them. Industry reports pile up across dozens of sources. The volume of useful technical content is growing exponentially — but the time to consume it isn't.
Rencewise was built to solve this without cutting corners. AI agents systematically ingest, transcribe, and extract technical content at scale. Then domain experts review every article — verifying claims against primary sources, correcting errors, and refining the output before anything gets published. The result is a knowledge base with the throughput of automation and the reliability of human judgment.
Principles
How We Think About Research
Source Fidelity
Every finding traces back to its original source — a specific slide, transcript passage, or paper section. Human reviewers verify citations against the primary material. No hallucinated claims, no unsourced assertions.
Depth Over Breadth
We process fewer collections with greater thoroughness. Every presentation gets frame extraction, transcript alignment, and entity-level analysis — not just a summary.
Compounding Knowledge
Each new collection enriches the existing knowledge base. Entities are cross-referenced, trends are tracked across events, and the corpus grows more valuable with every ingestion.
Research Process
Automation First, Human Review Always
Our pipeline starts with raw content — YouTube playlists, conference session recordings, poster PDFs, research papers. AI agents download, transcribe, extract frames, deduplicate slides, and align transcripts with visual content automatically.
From there, agents draft structured wiki pages and extract entities across the corpus. But nothing ships without a human in the loop. Domain experts review every article for accuracy, flag anything that reads like AI filler, and refine the output until it meets the standard of work they'd put their name on. The knowledge base you see is the result of that curation — not raw model output.
Our Team
Small Team, High Standards
Rencewise is deliberately lean. AI agents handle the high-volume processing — transcription, extraction, initial drafts — while human experts drive the questions worth asking, review every published article, and refuse to ship anything that doesn't meet their standard. The combination lets a small team cover ground that would otherwise require dozens of analysts, without sacrificing the quality that makes the output worth reading.