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REAL-TIME INNOVATIONS, INC.

Address

232 E JAVA DR
SUNNYVALE, CA, 94089-1318
USA

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UEI: H293LTV8R2U3

Number of Employees: 272

HUBZone Owned: No

Woman Owned: No

Socially and Economically Disadvantaged: No

SBIR/STTR Involvement

Year of first award: 1995

Phase I Awards

Phase II Awards

58.18%

Conversion Rate

$6,299,619

Phase I Dollars

$29,814,267

Phase II Dollars

$36,113,885

Total Awarded

Awards

Up to 10 of the most recent awards are being displayed. To view all of this company's awards, visit the Award Data search page.

The GENESIS Agent Toolkit for Simulink

Amount: $179,998 Topic: AF242-0002

DAF PEO Digital has also recognized that generative AI agents will be transformative in nearly all parts of military operations beginning with Simulation. ĀThis SBIR topic will help to inform the DAF about the potential of next-generation distributed agent frameworks to deliver compounded returns by enabling tens to hundreds of collaborative agents to collectively work together.ĀToday, while industry has produced many agent frameworks to extend the capabilities of generative AI, the focus has been on conceptual demonstrations to evaluate interacting agent capabilities in a single process.Ā While some of these are becoming quite elaborate and capable, they focus on single process / single code base frameworks that inherently lack the distributed agent/human collaboration that is a primary component to the vision of generative AI agents in the enterprise.Ā Further, these systems leave it up to individual developers to integrate these agents with relevant systems.ĀĀIn order to reap the substantial benefits of generative AI (Gen AI), industrial and academic research has shown the significant leap in performance from multiple collaborating agents.Ā Today, no such framework exists that will facilitate the development, testing, integration, and execution of large-scale heterogeneous agent-based systems.Ā We are proposing the first framework of its kind to deliver this capability to the DAF.

SBIR

Phase I

2025

DOD

USAF

Next-Gen MOSA-Based Real-Time Sensor Data Processing Architecture for Big Iron

Amount: $1,249,969 Topic: AFX237-PCSO1

The project aims to enhance the key avionics program's capabilities by integrating IEEE TSN and OMG DDS for high-performance, real-time data communication. It addresses the limitations of traditional network standards, offering dynamic rescheduling and reconfiguration for flexible mission adaptation. The solution promotes modularity and interoperability, reducing costs by leveraging low-cost Ethernet hardware and enhancing security through data-centric measures. Additionally, it accelerates capability deployment with MBSE tools and improves operational efficiency with converged networking, ensuring seamless data exchange across diverse systems.

SBIR

Phase II

2024

DOD

USAF

A Data-Centric Distributed Agentic Framework for DAF Simulation

Amount: $1,249,976 Topic: AFX246-DPCSO1

GENESIS (Gen-AI Network for Enhanced Simulation Integration and Security) aims to integrate AI agents into simulation environments safely, securely, and reliably. Utilizing the OMG DDS standard, particularly RTI’s Connext DDS, GENESIS completes the stack for a multi-agent simulation integration.Key Objectives1. Safety: Ensure safe AI agent operation through comprehensive state monitoring and semantic-level interaction, including tools for semantic analysis, logging, and real-time monitoring.2. Security: Implement a multi-faceted security environment leveraging Connext DDS’s existing mechanisms with additional semantic controls, including fine-grained access control, encryption, and content monitoring.3. Reliability: Provide a standardized communication layer using DDS for inter-agent communication, facilitating real-time data exchange and supporting integration with MATLAB/Simulink and future integration with AFSIM. This includes communication libraries for widely used agent frameworks like Semantic Kernel and LangChain.Technical Approach- Discovery: Enable endpoints to discover each other without network configuration.- Security: Provide built-in access control, authentication, encryption, and semantic oversight.- Data Delivery: Ensure data is presented as known structures, eliminating integration issues with additional agents/services- Content Filtering and Keying: Allow endpoints to send data only when needed by others.- Comprehensive monitoring: Enable oversight, model training, and in context agent improvement through agent input/output state data.Phase II Technical Objectives and Key Results1. Develop Comprehensive State Monitoring and Interaction - Implement tools for semantic analysis and logging. - Demonstrate real-time monitoring in a test environment.2. Develop Multi-faceted Security Environment - Implement fine-grained access control policies. - Integrate semantic controls for monitoring communications.3. Develop Seamless Integration with MATLAB/Simulink - Implement and test the MATLAB/Simulink plug-in. - Develop an initial integration plan for AFSIM.4. Develop a Collaborative AI Environment - Implement DDS-based communication for real-time data exchange. - Develop tools for collaborative task planning and execution.5. Develop and Demonstrate Inter-agent Library - Develop communication libraries for Python, C#, and JavaScript. - Conduct multiple demonstrations to stakeholders and gather feedback.

SBIR

Phase II

2024

DOD

USAF

Next-Gen MOSA-Based Real-Time Sensor Data Processing Architecture

Amount: $74,677 Topic: AFX237-PCSO1

We are focused on exploring advancements in resilient real-time networking using open standards (time-sensitive networking [TSN]) to substantially improve the DAF's ability to process sensor data in real-time.

SBIR

Phase I

2024

DOD

USAF

Accelerating Threat and Risk Detection within Data Centric Networks

Amount: $74,816 Topic: X224-OCSO1

Continuous monitoring of critical distributed systems is essential for the early detection of risks and security threats. However, traditional networks are opaque and do not provide the transparency needed for advanced data monitoring. Existing monitoring tools can identify network-layer information but cannot observe data semantics. Next-generation data-centric networks present an opportunity to revolutionize network monitoring. In data-centric networks, data semantics are decoupled from the specifics of the application stack, so a trusted observer can not only identify data flows but also understand the semantics of the communications. Monitoring and visualizing data streams and their semantics can accelerate threat detection by identifying undesired communication flows caused by misconfigurations, bugs, or an intruder, and answer questions such as who is talking to who, and what are they talking about? RTI’s product is the world’s leading implementation of the OMG DDS standard and military-grade data-centric connectivity software. We propose to design, implement and test a revolutionary monitoring framework for Air Force’s next-gen data-centric networks. If fully funded, the framework will accelerate threat detection by visualizing data streams and extending AI/ML-based monitoring and data analytic tools. The framework will also enable automatic system validation against UAF models and other security standards. In Phase I, we will collect stakeholders' requirements and derisk Phase II.

SBIR

Phase I

2023

DOD

USAF

Accelerating Threat and Risk Detection within Data Centric Networks

Amount: $1,249,951 Topic: X224-OCSO1

Threat detection and response are critical components of the United States Air Force's (USAF) mission to protect national security and maintain air superiority by outpacing enemy threats. The Air Force Life Cycle Management Center (AFLCMC) defines continu

SBIR

Phase II

2023

DOD

USAF

Outpacing Threats By Enabling Rapid Integration of Autonomous Capabilities

Amount: $64,918 Topic: AFX235-CSO1

In autonomous systems warfare, stepping inside the enemies’ OODA loop will require automated on-the-fly kill web construction from capabilities offered across disparate systems/domains/forces not fully designed for interoperation. Dynamically assembling a

SBIR

Phase I

2023

DOD

USAF

Standardizing OMG DDS simulation enhancements for modern USAF training & simulation systems

Amount: $49,827 Topic: AF212-CSO1

The majority of current/legacy modeling and simulation technologies were developed two decades ago. They cannot provide the scalability, performance, and multi-level security cybersecurity required for MDO use cases. These features hinder forward evoluti

SBIR

Phase I

2022

DOD

USAF

Enhancing Performance and Cybersecure Operation for DoD Systems

Amount: $1,249,914 Topic: AF221-DCSO1

Our goal is to explore how to adapt the OMG DDS standard to a DevSecOps system development paradigm. DevSecOps spans modeling, development, operations, and cybersecurity. It is intended to drive down development costs and time to deployment by creating

SBIR

Phase II

2022

DOD

USAF

Modernizing USAF Training & Simulation Capabilities

Amount: $49,827 Topic: AF212-CSO1

The USAF has invested heavily in developing training and simulation solutions. These systems have been developed and depend upon technologies that are limiting. Yet, modernization hurts – it is costly, and takes a long time. The modernization of USAF

SBIR

Phase I

2022

DOD

USAF