Celonis maps operations from enterprise system logs, while Ontora starts with employee interviews and tacit process knowledge.
Skan observes work across enterprise applications, while Ontora uses AI-led interviews to surface bottlenecks and handoffs.
Soroco maps human and agent workflows through work observation, while Ontora builds its graph from interviews, transcripts, and documents.
Qualtrics is broader employee experience software, while Ontora is focused on process knowledge, workflow mapping, and automation discovery.
The candidate moat is proprietary data: each campaign builds a customer-specific operational graph that gets harder to replace as more workflows, transcripts, and documents enter it.
Ontora uses LLM interviews plus GraphRAG over transcripts and a Neo4j knowledge graph, so outputs are grounded in employee accounts rather than only system logs.
Makes massive file transfers 10x faster so teams stop deleting data they can't afford to move.
Robotics teams delete 96% of their sensor data because they cannot move it fast enough. Byteport's DART protocol achieves 1500x faster transfer than TCP for large files, which turns a data bottleneck into a data asset for any team that generates more than it can ship.
Delivers 95%+ accurate knowledge search across unstructured enterprise data, beating standard RAG.
RAG accuracy plateaus around 80% for most implementations. Captain claims 95%+ by running parallel LLM queries across document chunks and aggregating results, which is a brute-force approach that works if the orchestration is fast enough. SOC 2 certified.
Automates enterprise document workflows with 93% straight-through processing from just 3-5 samples.
Most document AI requires hundreds of labeled examples. EigenPal reaches 93% straight-through automation from 3-5 samples, which means regulated enterprises (banks, insurers) can deploy on new document types in hours instead of months.
Captures 8,000 hours/day of multimodal human activity data to train the next generation of robots.
Robotics foundation models are data-starved. Human Archive has 50,000+ contributors wearing custom sensor rigs across homes, restaurants, hotels, and construction sites, capturing 8,000 hours/day of synchronized video, depth, and tactile data. Scale AI for embodied AI.