Anonymized applied system
Aerial Public Safety
Detection networks developed inside a drone-flight simulator, then prepared for deployment on real aircraft for earlier wildfire detection.
We build neural-network systems, AI agents and advanced analytics for decisions that have to be right.
Explore our published benchmark results and the evidence behind our systems.
View Research ResultsFind figures in financial documents, check the calculations and trace every answer to its sources.
Explore Model AccessAgents for financial documents and network policy, plus custom agents built and evaluated on your own tasks.
Browse the Agent CatalogCustom neural networks for vision, sensors and documents, from a scoped pilot to production.
Scope a ProjectDeep-learning infrastructure that finds the right evidence across dense financial documents and long-form source material.
Purpose-built analytical systems for quantitative research, model evaluation, and decision-critical intelligence.
Clear interfaces that turn sophisticated models, evidence, and analytics into usable research tools.
View DesignsRepresentative work is anonymized. Prospective deployment patterns are labeled as illustrative.
Anonymized applied system
Detection networks developed inside a drone-flight simulator, then prepared for deployment on real aircraft for earlier wildfire detection.
Anonymized validated model
A predictive model combined pathogen kinetics, room geometry, and exposure time to compare continuous disinfection with a static intervention, indicating about 80% lower cumulative exposure.
Research system
Find evidence across financial documents, interpret tables and complete multi-step calculations with sources for each answer.
Explore Financial Document ReasoningAnonymized applied system
A nightly improvement loop proposes one change, evaluates the results, and logs every keep-or-revert decision.
Illustrative use case
For a large e-commerce warehouse, combine scan histories, demand signals, equipment telemetry, and camera feeds to forecast SKU demand, detect inventory anomalies, optimize pick paths, and predict maintenance windows.
Illustrative use case
Use computer vision and sensor time-series to flag out-of-spec parts or motion, forecast equipment failure, and prioritize the inspections that reduce downtime.
Evaluate financial data, model behavior, benchmark results, and the evidence behind complex answers.
View RoleBuild model-serving, evaluation and advanced analytics systems for real-world financial research.
View RoleSupport AI licensing, data governance, commercial contracts, corporate filings, and compliance.
View RoleOpen the conversations that turn research and applied systems into customer projects, from first email to technical call.
View RoleCommunicate research milestones, benchmark results, model releases, and technical partnerships.
View RoleOne Jump Inc. builds deep-learning systems for decisions that have to be right. We define what correct means with you, test against it on your own data, and ship only what passes.
For model access, technical partnerships, research, or company inquiries, connect with the right person at One Jump.
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