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RIA RAN brings machine-learning inference into software-defined radio and open 5G radio-access functions. Rather than supplying an entire 5G network, it provides software and integration work that operates alongside the radio stack. ESA's RIA RAN NTN project documents a modified srsRAN plug-in on the distributed-unit processor, USRP radio hardware, an ARM or x86 host, open5GS and Qoherent's inference engine for adaptive radio-resource assignment.
RIA Toolkit supports the surrounding engineering process: creating and curating datasets, training and evaluating models, benchmarking an application, and integrating and deploying it. RIA Hub describes synthetic data from Python, GNU Radio and MATLAB alongside live SDR recordings. SigMF pairs retain signal data with recording metadata, while Git LFS and package versioning support collaboration around large RF datasets and software dependencies.
ESA's published June 2025 status records design, benchmarking and early field work informing requirements, with scheduler and testbed development continuing. The architecture is therefore useful as a concrete integration reference. Current performance and delivery maturity depend on the selected hardware, radio-stack versions and model. NATO DIANA's separately described adaptive 5G mobile-ad-hoc payload should not be assumed to be this same configuration.
These describe the reviewed application scope, not confirmed deployments, released requirements or procurement eligibility.
An integration and engineering offering with an ESA-documented development programme. ESA's June 2025 status records continuing scheduler and testbed work. RIA Toolkit OSS 0.1.7 was published in May 2026 with an Alpha classifier; that software release does not establish completed RIA RAN deployment.
RIA RAN is available for demonstration and project integration. RIA Toolkit OSS has a public release; RIA Hub applications and tools are advertised as a private beta. Confirm supported radio and driver versions, licensing and maintenance within the proposed project.
A technology readiness level is not established by the reviewed public sources.
Deploying RF inference directly into radio-access equipment could support low-latency spectrum awareness and network adaptation at the edge; this mapping is derived.
Radio Intelligence Applications for 5G RAN may help teams working on Major-event and critical-infrastructure cyber defence by contributing to detection and situational awareness, resilient communications and command, and cyber and digital operations.
This is a reviewed public-source assessment. It is not procurement eligibility, endorsement, customer interest, or classified demand.
These records support this capability and its published Mission area and Defence need connections. A source count is not a count of independent confirmations.
Source type: official company product
Supports: Capability · defence applications
RIA RAN pairs a radio application and gNodeB with local ML inference and redeployable models for sensing, communications and NTN resilience. Demo/integration engagement is offered; low-latency claims do not specify a generally guaranteed certified timing budget.
Supports: Capability · technical tags
RIA RAN pairs a radio application and gNodeB with local ML inference and redeployable models for sensing, communications and NTN resilience. Demo/integration engagement is offered; low-latency claims do not specify a generally guaranteed certified timing budget.
Supports: Capability · core features
RIA RAN pairs a radio application and gNodeB with local ML inference and redeployable models for sensing, communications and NTN resilience. Demo/integration engagement is offered; low-latency claims do not specify a generally guaranteed certified timing budget.
Supports: Capability · technicaldomainslugs
RIA RAN pairs a radio application and gNodeB with local ML inference and redeployable models for sensing, communications and NTN resilience. Demo/integration engagement is offered; low-latency claims do not specify a generally guaranteed certified timing budget.
Supports: Capability · technical tags
RIA RAN pairs a radio application and gNodeB with local ML inference and redeployable models for sensing, communications and NTN resilience. Demo/integration engagement is offered; low-latency claims do not specify a generally guaranteed certified timing budget.
Supports: Capability · technology readiness level
RIA RAN pairs a radio application and gNodeB with local ML inference and redeployable models for sensing, communications and NTN resilience. Demo/integration engagement is offered; low-latency claims do not specify a generally guaranteed certified timing budget.
Supports: Capability · technical tags
RIA RAN pairs a radio application and gNodeB with local ML inference and redeployable models for sensing, communications and NTN resilience. Demo/integration engagement is offered; low-latency claims do not specify a generally guaranteed certified timing budget.
Supports: Capability · technical tags
RIA RAN pairs a radio application and gNodeB with local ML inference and redeployable models for sensing, communications and NTN resilience. Demo/integration engagement is offered; low-latency claims do not specify a generally guaranteed certified timing budget.
Supports: Capability · technical tags
RIA RAN pairs a radio application and gNodeB with local ML inference and redeployable models for sensing, communications and NTN resilience. Demo/integration engagement is offered; low-latency claims do not specify a generally guaranteed certified timing budget.
Supports: Capability · technicaldomainslugs
RIA RAN pairs a radio application and gNodeB with local ML inference and redeployable models for sensing, communications and NTN resilience. Demo/integration engagement is offered; low-latency claims do not specify a generally guaranteed certified timing budget.
Supports: Capability · defence applications
RIA RAN pairs a radio application and gNodeB with local ML inference and redeployable models for sensing, communications and NTN resilience. Demo/integration engagement is offered; low-latency claims do not specify a generally guaranteed certified timing budget.
Supports: Capability · defence applications
RIA RAN pairs a radio application and gNodeB with local ML inference and redeployable models for sensing, communications and NTN resilience. Demo/integration engagement is offered; low-latency claims do not specify a generally guaranteed certified timing budget.
Supports: Capability · name
RIA RAN pairs a radio application and gNodeB with local ML inference and redeployable models for sensing, communications and NTN resilience. Demo/integration engagement is offered; low-latency claims do not specify a generally guaranteed certified timing budget.
Supports: Capability · capability type
RIA RAN pairs a radio application and gNodeB with local ML inference and redeployable models for sensing, communications and NTN resilience. Demo/integration engagement is offered; low-latency claims do not specify a generally guaranteed certified timing budget.
Supports: Capability · commercial availability
RIA RAN pairs a radio application and gNodeB with local ML inference and redeployable models for sensing, communications and NTN resilience. Demo/integration engagement is offered; low-latency claims do not specify a generally guaranteed certified timing budget.
Supports: Capability · defence applications
RIA RAN pairs a radio application and gNodeB with local ML inference and redeployable models for sensing, communications and NTN resilience. Demo/integration engagement is offered; low-latency claims do not specify a generally guaranteed certified timing budget.
Supports: Capability · summary
RIA RAN pairs a radio application and gNodeB with local ML inference and redeployable models for sensing, communications and NTN resilience. Demo/integration engagement is offered; low-latency claims do not specify a generally guaranteed certified timing budget.
Supports: Capability · summary
Qoherent's radio-intelligence tooling brings machine-learning model development, data management and low-latency inference into software-defined radio and open 5G radio-access-network environments.
Supports: Capability · maturity
RIA RAN pairs a radio application and gNodeB with local ML inference and redeployable models for sensing, communications and NTN resilience. Demo/integration engagement is offered; low-latency claims do not specify a generally guaranteed certified timing budget.
Supports: Capability · technicaldomainslugs
RIA RAN pairs a radio application and gNodeB with local ML inference and redeployable models for sensing, communications and NTN resilience. Demo/integration engagement is offered; low-latency claims do not specify a generally guaranteed certified timing budget.
Supports: Mission area · Edge Data Processing
RIA RAN pairs a radio application and gNodeB with local ML inference and redeployable models for sensing, communications and NTN resilience. Demo/integration engagement is offered; low-latency claims do not specify a generally guaranteed certified timing budget.
Supports: Mission area · Edge Data Processing
RIA RAN pairs a radio application and gNodeB with local ML inference and redeployable models for sensing, communications and NTN resilience. Demo/integration engagement is offered; low-latency claims do not specify a generally guaranteed certified timing budget.
Supports: Mission area · Edge Data Processing
Deploying RF inference directly into radio-access equipment could support low-latency spectrum awareness and network adaptation at the edge; this mapping is derived.
Supports: Mission area · Edge Data Processing
RIA RAN pairs a radio application and gNodeB with local ML inference and redeployable models for sensing, communications and NTN resilience. Demo/integration engagement is offered; low-latency claims do not specify a generally guaranteed certified timing budget.
Supports: Mission area · Edge Data Processing
RIA RAN pairs a radio application and gNodeB with local ML inference and redeployable models for sensing, communications and NTN resilience. Demo/integration engagement is offered; low-latency claims do not specify a generally guaranteed certified timing budget.
Supports: Defence need · Major-event and critical-infrastructure cyber defence
Qoherent's radio-intelligence tooling brings machine-learning model development, data management and low-latency inference into software-defined radio and open 5G radio-access-network environments.
European Space Agency
Source type: official report
Supports: Capability · capability type
ESA describes RIA RAN NTN as a modified srsRAN plug-in on the distributed-unit processor, using USRP radios, ARM or x86 compute, open5GS and Qoherent's inference engine for adaptive resource assignment. Its June 10, 2025 update marked the project ongoing: preliminary design, hardware benchmarking and field tests informed requirements while scheduler development and testbed construction continued. It is not a September 2026 completion record.
Supports: Capability · name
ESA describes RIA RAN NTN as a modified srsRAN plug-in on the distributed-unit processor, using USRP radios, ARM or x86 compute, open5GS and Qoherent's inference engine for adaptive resource assignment. Its June 10, 2025 update marked the project ongoing: preliminary design, hardware benchmarking and field tests informed requirements while scheduler development and testbed construction continued. It is not a September 2026 completion record.
Source type: official company product
Supports: Capability · core features
RIA Toolkit supports dataset generation, curation and testing; building, training and evaluating models; and application integration, benchmarking and deployment. It is available as Python libraries and through RIA Hub. The OSS foundation uses AGPLv3; alternative permissive or commercial licensing is available on request. Toolkit licensing does not establish RIA RAN delivery terms.
Supports: Capability · commercial availability
RIA Toolkit spans datasets, model evaluation and integration as a Python library or RIA Hub; the OSS version is AGPLv3 with alternative terms on request and Conda/RadioConda support. Toolkit licensing is distinct from RIA RAN delivery terms.
Supports: Capability · core features
Source type: official company product
Supports: Capability · summary
Qoherent's recording tutorial describes reproducible synthetic signal generation and live SDR IQ recording, producing SigMF metadata/data pairs and retaining recordings through RIA Hub and Git LFS. This documents a development workflow, not a validation result for any particular radio-AI model.
Supports: Capability · core features
Qoherent's recording tutorial describes reproducible synthetic signal generation and live SDR IQ recording, producing SigMF metadata/data pairs and retaining recordings through RIA Hub and Git LFS. This documents a development workflow, not a validation result for any particular radio-AI model.
Qoherent via PyPI · May 26, 2026
Source type: official company product
Supports: Capability · commercial availability
PyPI directly lists Qoherent RIA Toolkit OSS version 0.1.7, uploaded May 26, 2026, with AGPL-3.0-only licensing, Python 3.10 or newer and Alpha development status. The archived ria-core repository directs users to the renamed project. Current public README and indexed release notes differ about SDR-driver support, so the latest package date does not establish a definitive supported-device list.
Supports: Capability · maturity
Public sources cited · Facts and assessments kept separate · Human review
Loading related records…
Supports: Capability · technical tags
ESA describes RIA RAN NTN as a modified srsRAN plug-in on the distributed-unit processor, using USRP radios, ARM or x86 compute, open5GS and Qoherent's inference engine for adaptive resource assignment. Its June 10, 2025 update marked the project ongoing: preliminary design, hardware benchmarking and field tests informed requirements while scheduler development and testbed construction continued. It is not a September 2026 completion record.
Supports: Capability · technicaldomainslugs
ESA describes RIA RAN NTN as a modified srsRAN plug-in on the distributed-unit processor, using USRP radios, ARM or x86 compute, open5GS and Qoherent's inference engine for adaptive resource assignment. Its June 10, 2025 update marked the project ongoing: preliminary design, hardware benchmarking and field tests informed requirements while scheduler development and testbed construction continued. It is not a September 2026 completion record.
Supports: Capability · technology readiness level
ESA describes RIA RAN NTN as a modified srsRAN plug-in on the distributed-unit processor, using USRP radios, ARM or x86 compute, open5GS and Qoherent's inference engine for adaptive resource assignment. Its June 10, 2025 update marked the project ongoing: preliminary design, hardware benchmarking and field tests informed requirements while scheduler development and testbed construction continued. It is not a September 2026 completion record.
Supports: Capability · commercial availability
ESA describes RIA RAN NTN as a modified srsRAN plug-in on the distributed-unit processor, using USRP radios, ARM or x86 compute, open5GS and Qoherent's inference engine for adaptive resource assignment. Its June 10, 2025 update marked the project ongoing: preliminary design, hardware benchmarking and field tests informed requirements while scheduler development and testbed construction continued. It is not a September 2026 completion record.
Supports: Capability · core features
ESA describes RIA RAN NTN as a modified srsRAN plug-in on the distributed-unit processor, using USRP radios, ARM or x86 compute, open5GS and Qoherent's inference engine for adaptive resource assignment. Its June 10, 2025 update marked the project ongoing: preliminary design, hardware benchmarking and field tests informed requirements while scheduler development and testbed construction continued. It is not a September 2026 completion record.
Supports: Capability · technical tags
ESA describes RIA RAN NTN as a modified srsRAN plug-in on the distributed-unit processor, using USRP radios, ARM or x86 compute, open5GS and Qoherent's inference engine for adaptive resource assignment. Its June 10, 2025 update marked the project ongoing: preliminary design, hardware benchmarking and field tests informed requirements while scheduler development and testbed construction continued. It is not a September 2026 completion record.
Supports: Capability · summary
ESA RIA RAN NTN project 3F.047 describes a modified srsRAN plug-in on the distributed-unit processor, USRP hardware on ARM/x86, open5GS core and Qoherent inference engine for low-SWaP adaptive resource assignment. Its June 10, 2025 status is ongoing with scheduler/testbed work, not a September 2026 completion record.
Supports: Capability · technical tags
ESA describes RIA RAN NTN as a modified srsRAN plug-in on the distributed-unit processor, using USRP radios, ARM or x86 compute, open5GS and Qoherent's inference engine for adaptive resource assignment. Its June 10, 2025 update marked the project ongoing: preliminary design, hardware benchmarking and field tests informed requirements while scheduler development and testbed construction continued. It is not a September 2026 completion record.
Supports: Capability · maturity
ESA describes RIA RAN NTN as a modified srsRAN plug-in on the distributed-unit processor, using USRP radios, ARM or x86 compute, open5GS and Qoherent's inference engine for adaptive resource assignment. Its June 10, 2025 update marked the project ongoing: preliminary design, hardware benchmarking and field tests informed requirements while scheduler development and testbed construction continued. It is not a September 2026 completion record.
Supports: Capability · maturity
ESA RIA RAN NTN project 3F.047 describes a modified srsRAN plug-in on the distributed-unit processor, USRP hardware on ARM/x86, open5GS core and Qoherent inference engine for low-SWaP adaptive resource assignment. Its June 10, 2025 status is ongoing with scheduler/testbed work, not a September 2026 completion record.
Supports: Capability · technicaldomainslugs
ESA describes RIA RAN NTN as a modified srsRAN plug-in on the distributed-unit processor, using USRP radios, ARM or x86 compute, open5GS and Qoherent's inference engine for adaptive resource assignment. Its June 10, 2025 update marked the project ongoing: preliminary design, hardware benchmarking and field tests informed requirements while scheduler development and testbed construction continued. It is not a September 2026 completion record.
Supports: Capability · core features
ESA RIA RAN NTN project 3F.047 describes a modified srsRAN plug-in on the distributed-unit processor, USRP hardware on ARM/x86, open5GS core and Qoherent inference engine for low-SWaP adaptive resource assignment. Its June 10, 2025 status is ongoing with scheduler/testbed work, not a September 2026 completion record.
Supports: Capability · summary
ESA describes RIA RAN NTN as a modified srsRAN plug-in on the distributed-unit processor, using USRP radios, ARM or x86 compute, open5GS and Qoherent's inference engine for adaptive resource assignment. Its June 10, 2025 update marked the project ongoing: preliminary design, hardware benchmarking and field tests informed requirements while scheduler development and testbed construction continued. It is not a September 2026 completion record.
Supports: Capability · defence applications
ESA describes RIA RAN NTN as a modified srsRAN plug-in on the distributed-unit processor, using USRP radios, ARM or x86 compute, open5GS and Qoherent's inference engine for adaptive resource assignment. Its June 10, 2025 update marked the project ongoing: preliminary design, hardware benchmarking and field tests informed requirements while scheduler development and testbed construction continued. It is not a September 2026 completion record.
Supports: Capability · core features
ESA describes RIA RAN NTN as a modified srsRAN plug-in on the distributed-unit processor, using USRP radios, ARM or x86 compute, open5GS and Qoherent's inference engine for adaptive resource assignment. Its June 10, 2025 update marked the project ongoing: preliminary design, hardware benchmarking and field tests informed requirements while scheduler development and testbed construction continued. It is not a September 2026 completion record.
Supports: Capability · technicaldomainslugs
ESA describes RIA RAN NTN as a modified srsRAN plug-in on the distributed-unit processor, using USRP radios, ARM or x86 compute, open5GS and Qoherent's inference engine for adaptive resource assignment. Its June 10, 2025 update marked the project ongoing: preliminary design, hardware benchmarking and field tests informed requirements while scheduler development and testbed construction continued. It is not a September 2026 completion record.
Supports: Capability · defence applications
ESA describes RIA RAN NTN as a modified srsRAN plug-in on the distributed-unit processor, using USRP radios, ARM or x86 compute, open5GS and Qoherent's inference engine for adaptive resource assignment. Its June 10, 2025 update marked the project ongoing: preliminary design, hardware benchmarking and field tests informed requirements while scheduler development and testbed construction continued. It is not a September 2026 completion record.
Supports: Capability · technical tags
ESA describes RIA RAN NTN as a modified srsRAN plug-in on the distributed-unit processor, using USRP radios, ARM or x86 compute, open5GS and Qoherent's inference engine for adaptive resource assignment. Its June 10, 2025 update marked the project ongoing: preliminary design, hardware benchmarking and field tests informed requirements while scheduler development and testbed construction continued. It is not a September 2026 completion record.
Supports: Capability · defence applications
ESA describes RIA RAN NTN as a modified srsRAN plug-in on the distributed-unit processor, using USRP radios, ARM or x86 compute, open5GS and Qoherent's inference engine for adaptive resource assignment. Its June 10, 2025 update marked the project ongoing: preliminary design, hardware benchmarking and field tests informed requirements while scheduler development and testbed construction continued. It is not a September 2026 completion record.
Supports: Capability · defence applications
ESA describes RIA RAN NTN as a modified srsRAN plug-in on the distributed-unit processor, using USRP radios, ARM or x86 compute, open5GS and Qoherent's inference engine for adaptive resource assignment. Its June 10, 2025 update marked the project ongoing: preliminary design, hardware benchmarking and field tests informed requirements while scheduler development and testbed construction continued. It is not a September 2026 completion record.
Supports: Capability · core features
ESA RIA RAN NTN project 3F.047 describes a modified srsRAN plug-in on the distributed-unit processor, USRP hardware on ARM/x86, open5GS core and Qoherent inference engine for low-SWaP adaptive resource assignment. Its June 10, 2025 status is ongoing with scheduler/testbed work, not a September 2026 completion record.
Supports: Capability · core features
ESA describes RIA RAN NTN as a modified srsRAN plug-in on the distributed-unit processor, using USRP radios, ARM or x86 compute, open5GS and Qoherent's inference engine for adaptive resource assignment. Its June 10, 2025 update marked the project ongoing: preliminary design, hardware benchmarking and field tests informed requirements while scheduler development and testbed construction continued. It is not a September 2026 completion record.
Supports: Capability · technical tags
ESA describes RIA RAN NTN as a modified srsRAN plug-in on the distributed-unit processor, using USRP radios, ARM or x86 compute, open5GS and Qoherent's inference engine for adaptive resource assignment. Its June 10, 2025 update marked the project ongoing: preliminary design, hardware benchmarking and field tests informed requirements while scheduler development and testbed construction continued. It is not a September 2026 completion record.
Supports: Mission area · Edge Data Processing
ESA describes RIA RAN NTN as a modified srsRAN plug-in on the distributed-unit processor, using USRP radios, ARM or x86 compute, open5GS and Qoherent's inference engine for adaptive resource assignment. Its June 10, 2025 update marked the project ongoing: preliminary design, hardware benchmarking and field tests informed requirements while scheduler development and testbed construction continued. It is not a September 2026 completion record.
Supports: Mission area · Edge Data Processing
ESA describes RIA RAN NTN as a modified srsRAN plug-in on the distributed-unit processor, using USRP radios, ARM or x86 compute, open5GS and Qoherent's inference engine for adaptive resource assignment. Its June 10, 2025 update marked the project ongoing: preliminary design, hardware benchmarking and field tests informed requirements while scheduler development and testbed construction continued. It is not a September 2026 completion record.
Supports: Mission area · Edge Data Processing
ESA describes RIA RAN NTN as a modified srsRAN plug-in on the distributed-unit processor, using USRP radios, ARM or x86 compute, open5GS and Qoherent's inference engine for adaptive resource assignment. Its June 10, 2025 update marked the project ongoing: preliminary design, hardware benchmarking and field tests informed requirements while scheduler development and testbed construction continued. It is not a September 2026 completion record.
Supports: Mission area · Edge Data Processing
ESA describes RIA RAN NTN as a modified srsRAN plug-in on the distributed-unit processor, using USRP radios, ARM or x86 compute, open5GS and Qoherent's inference engine for adaptive resource assignment. Its June 10, 2025 update marked the project ongoing: preliminary design, hardware benchmarking and field tests informed requirements while scheduler development and testbed construction continued. It is not a September 2026 completion record.
RIA Toolkit spans datasets, model evaluation and integration as a Python library or RIA Hub; the OSS version is AGPLv3 with alternative terms on request and Conda/RadioConda support. Toolkit licensing is distinct from RIA RAN delivery terms.
Supports: Capability · summary
RIA Toolkit supports dataset generation, curation and testing; building, training and evaluating models; and application integration, benchmarking and deployment. It is available as Python libraries and through RIA Hub. The OSS foundation uses AGPLv3; alternative permissive or commercial licensing is available on request. Toolkit licensing does not establish RIA RAN delivery terms.
Supports: Capability · summary
RIA Toolkit spans datasets, model evaluation and integration as a Python library or RIA Hub; the OSS version is AGPLv3 with alternative terms on request and Conda/RadioConda support. Toolkit licensing is distinct from RIA RAN delivery terms.
Supports: Capability · core features
RIA Toolkit supports dataset generation, curation and testing; building, training and evaluating models; and application integration, benchmarking and deployment. It is available as Python libraries and through RIA Hub. The OSS foundation uses AGPLv3; alternative permissive or commercial licensing is available on request. Toolkit licensing does not establish RIA RAN delivery terms.
Supports: Capability · core features
RIA Toolkit spans datasets, model evaluation and integration as a Python library or RIA Hub; the OSS version is AGPLv3 with alternative terms on request and Conda/RadioConda support. Toolkit licensing is distinct from RIA RAN delivery terms.
PyPI directly lists Qoherent RIA Toolkit OSS version 0.1.7, uploaded May 26, 2026, with AGPL-3.0-only licensing, Python 3.10 or newer and Alpha development status. The archived ria-core repository directs users to the renamed project. Current public README and indexed release notes differ about SDR-driver support, so the latest package date does not establish a definitive supported-device list.
Supports: Capability · summary
PyPI directly lists Qoherent RIA Toolkit OSS version 0.1.7, uploaded May 26, 2026, with AGPL-3.0-only licensing, Python 3.10 or newer and Alpha development status. The archived ria-core repository directs users to the renamed project. Current public README and indexed release notes differ about SDR-driver support, so the latest package date does not establish a definitive supported-device list.
NATO DIANA
Source type: accelerator cohort directory
Supports: Capability · summary
NATO DIANA lists Qoherent in its 2026 cohort for an intelligent, adaptive and resilient 5G payload for mobile ad hoc networking. The listing establishes accelerator participation and the described development direction, not a NATO procurement award, independent product qualification or operational deployment.
Source type: official company product
Supports: Capability · maturity
Qoherent describes RIA Hub as combining Python/GNU Radio/MATLAB signal generation, SDR testbed control and over-the-air emulation, processing and deep-learning plugins, model development, testing and deployment. Gitea, Git LFS and package registries support shared versioned artifacts. Hub applications and tools are in private beta; public OSS repositories and packages have separate access.
Supports: Capability · summary
Qoherent describes RIA Hub as combining Python/GNU Radio/MATLAB signal generation, SDR testbed control and over-the-air emulation, processing and deep-learning plugins, model development, testing and deployment. Gitea, Git LFS and package registries support shared versioned artifacts. Hub applications and tools are in private beta; public OSS repositories and packages have separate access.
Supports: Capability · commercial availability
Qoherent describes RIA Hub as combining Python/GNU Radio/MATLAB signal generation, SDR testbed control and over-the-air emulation, processing and deep-learning plugins, model development, testing and deployment. Gitea, Git LFS and package registries support shared versioned artifacts. Hub applications and tools are in private beta; public OSS repositories and packages have separate access.
Source type: official company product
Supports: Capability · commercial availability
The official qoherent/ria-core repository is marked archived September 11, 2025 and read-only. The current company site still offers RIA Toolkit access, so support and maintained release selection need confirmation; the repository archive does not prove company or product closure.
Communications Security Establishment Canada
Source type: official report
Supports: Defence need · Major-event and critical-infrastructure cyber defence
High-profile events and their host organizations create concentrated cyber-risk and require coordinated planning, monitoring, incident response, exercises and secure information sharing across federal, provincial, municipal and private partners.
Supports: Defence need · Major-event and critical-infrastructure cyber defence
Reviewer synthesis of the public end state in the cited material: Event partners should be able to prepare for, detect and respond to cyber incidents through integrated threat intelligence, technical support, exercises and operational coordination before and during major events.
