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Open Call for Innovative Defense-Related Dual-Purpose Technologies/Solutions with a Clear Air Force Stakeholder Need

Award Information
Agency: Department of Defense
Branch: Air Force
Contract: FA8649-19-P-A062
Agency Tracking Number: F192-001-0095
Amount: $50,000.00
Phase: Phase I
Program: SBIR
Solicitation Topic Code: AF192-001
Solicitation Number: 19.2
Timeline
Solicitation Year: 2019
Award Year: 2019
Award Start Date (Proposal Award Date): 2019-08-09
Award End Date (Contract End Date): 2020-08-09
Small Business Information
85 Broad Street Street 18th Floor
New York, NY 10004
United States
DUNS: 080706249
HUBZone Owned: No
Woman Owned: No
Socially and Economically Disadvantaged: No
Principal Investigator
 Seth Potter
 Head of Federal
 (917) 697-7005
 seth@aireverie.com
Business Contact
 Seth Potter
Phone: (917) 697-7005
Email: seth@aireverie.com
Research Institution
N/A
Abstract

AI.Reverie is a synthetic data simulation platform which generates an entirely new class of data that successfully trains and improves computer vision algorithms at scale. In order to train mission critical computer vision applications, there is a significant need for large amounts of diverse data that mimics real world locations and objects. Our company specializes in computer vision challenges - object detection and activity recognition - where data is highly sparse or non existent. AI.Reverie’s sophisticated computer vision platform integrates machine learning and AI by generating synthetic data to help offset the costs of labeled real world data and images that are highly rare and unforeseen to mitigate risks associated with real world data biases. The company’s technology trains the latest state of the art computer vision algorithms, which empowers drone warfare and keeps soldiers safe. AI.Reverie’s platform automatically generates fully annotated synthetic data at scale (i.e., in the millions). The ability to synthetically generate data around scenarios that are highly dangerous, but are often difficult to find in the real world helps train algorithms that are better able to empower analysts in making life saving decisions.

* Information listed above is at the time of submission. *

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