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Eagle Vision Embedded TM is a modular, safety-certifiable graphics driver supporting industry-standard Khronos APIs, designed to run across Linux and RTOS platforms, and modern CPU/GPU hardware including Tiger Lake and Panther Lake. Ideal for glass cockpits, synthetic vision, and any safety-critical display system, it helps you deliver high-fidelity visual systems faster, with less risk, and with full support for certification to standards like DO-178C and ISO 26262.
Current Solutions and Limitations which drive our need to provide an exceptional alternative
Traditional graphics drivers often are monolithic, hardware-locked, OS-specific, and costly or slow to certify to standards like DO-178C, ISO 26262, IEC 61508.
Legacy drivers may lack support for newer industry-standard APIs (e.g. Vulkan SC, OpenGL SC, etc.), making it difficult to benefit from advances in GPU hardware or multi-vendor platforms.
Eagle Vision Embedded TM
modular, safety-certifiable embedded graphics driver that:
Conforms to Industry-Standard Khronos APIs
- e.g. supports safety-critical subsets / extensions (Vulkan SC / OpenGL SC) to give you interoperability, future-proofing, and broad industry acceptance. (Khronos’ Vulkan SC 1.0 is now available as a standard for safety-critical accelerated graphics & compute.
High Performance + Rich Feature Support
- Can handle advanced graphics (shader programmable pipelines,
multi-layer overlays, etc.) needed by synthetic vision, terrain
rendering, HD maps, etc. - Optimized for hardware acceleration on modern GPUs, while
providing safe fallbacks or isolation in less powerful hardware. - Good support for compositing video or sensor data in graphics
pipelines, as glass cockpits often need.
Highly Modular & Portable
- Clear separation of hardware abstraction, OS interface, and graphics API layers.
- Allows reuse across multiple operating systems: Linux (and safety-hardened or real-time Linux variants), RTOSes, potentially even bare-metal in some cases.
- Supports a wide range of CPU geometries and GPU hardware; including newer Intel platforms like Tiger Lake, Panther Lake, etc.
Lower Total Cost of Ownership & Future Proofing
- Because it supports many OSs and hardware platforms, reuse is high and porting time minimal.
- Modular nature allows incremental updates / upgrades (e.g. when
moving to new GPU hardware) without full rewrite. - Helps reduce risk in supply chain / obsolescence by being able to switch to alternate GPU vendors/platforms with minimal re-engineering.
Safety & Certificatiotn Ready
- Designed from the ground up with functional safety in mind. Supports certification levels up to e.g. DO-178C Level A (avionics), ISO 26262 ASIL D (automotive), IEC 61508 (industrial).
- Deterministic behavior: bounded latency, predictable resource usage, worst-case execution times defined and measurable.
- Fault detection, error handling, isolation of failure modes.
ROI / Business Impact
Faster time-to-market: reduced porting/certification overhead.
Reduced maintenance cost: hardware or OS changes can be accommodated with less effort.
Reduced risk: in safety audits, system integration, supplier changes.
Differentiation: being able to advertise safety-critical certification, industry standard API compliance, hardware flexibility is a strong competitive advantage.
Differentiators / Why Us
Deep experience or existing evidence/case studies in safety-critical domains.
Broad hardware support including cutting edge Intel platforms like Tiger Lake / Panther Lake.
Modular OS abstraction layer that makes porting to different RTOSes or Linux variants straightforward.
API support that aligns with the latest safety-critical standards (you don’t force proprietary or obsolescent APIs).
Robust toolchain support: conformance testing, static analysis, performance tools, certification evidence.
Use Case: Synthetic Vision / Glass Cockpits
In synthetic vision, latency, rendering correctness, and determinism are safety-critical.
Errors or unpredictable delays can lead to misinterpretation, pilot error.
High resolution terrain, obstacle depiction, weather overlay, night vision etc. demand high fidelity, but you can’t afford crashes or unpredictable behavior.
With our driver, you get smooth rendering, correct layering, sensor fusion, all under a certified stack. If using multiple hardware GPUs or fallback, safe degradation is possible.
Request a Demonstration
Let’s set up a proof-of-concept running synthetic vision / glass cockpit rendering on your target CPU / GPU, under your RTOS or Linux variant, show performance, latency, certifability, and see how it fits into your safety case.
Key Features
Eagle Vision EmbeddedTM is a modular, safety-certifiable embedded graphics driver designed specifically for
safety-critical visual systems. Its architecture and feature set enable you to ship high-assurance graphically
rich displays faster, safer, and more flexibly.
Industry-Standard API Support
Full support for Khronos APIs including Vulkan SC, OpenGL SC (and possibly safety-critical subsets/extensions) so you conform to emerging safety standards and leverage common toolchains.
Modular Architecture
Clear layering: hardware abstraction layer, OS interface, graphics API core. Enables portability across OSs (Linux, real-time OSes, possibly even bare-metal or mixed criticality environments).
Wide CPU & GPU Compatibility
Supports modern Intel architectures (Tiger Lake, Panther Lake, etc.) plus a broad set of GPU vendors. Ensures hardware flexibility and helps avoid lock-in.
Safety & Certification-Ready Design
Built to support certification to DO-178C (avionics), ISO 26262 (automotive), IEC 61508, etc. Includes features like deterministic scheduling, bounded latency, error/fault detection & handling, worst-case execution time metrics, traceability.
Performance, Quality & Advanced Rendering
Capable of rendering synthetic vision, terrain, weather overlays, transparent/composited layers, high-resolution displays, shaders where permitted, etc., while maintaining safety guarantees.
Scalability & Maintainability
OS abstraction, modular drivers means porting to new platforms or OSs takes minimal effort. Upgrades to new hardware require limited changes. Robust toolchain support (testing, verification, performance profiling, safety case evidence).
Benefits
Reduced Time to Market: Because of reuse, modular porting, safety pre-certification artifacts, and support for standard APIs.
Lower Total Cost of Ownership: Easier maintenance, fewer platform-specific re-writes, better supplier flexibility.
Risk Mitigation: Clear path to certification, predictable behavior, safer failure modes.
Future-proofing: Ability to support new CPUs/GPUs, modern standards, and evolving safety regulations without rewriting from scratch.
Competitive Differentiation: OEMs and integrators can bring up certified safety visuals faster, with higher confidence; strong positioning in safety-critical markets.
Use Cases
Glass Cockpits & Avionics Displays: High-resolution synthetic terrain, obstacle depiction, integrated weather overlays and sensor data; deterministic behavior for pilot safety.
HUDs / Enhanced Vision Systems: Real-time compositing, low latency, safety monitoring even under adverse conditions.
Automotive Instrument Clusters / ADAS Displays: Where safety-critical display of warning, instrumentation, path projections require high reliability.
Industrial / Rail / Unmanned Systems: Any domain that demands both reliability (safety) and high fidelity visualization.
Differentiators vs Alternatives
Contract vs proprietary drivers: Eagle Vision Embedded isn’t tied to just one hardware vendor; wide support across CPUs/GPUs.
Modern API compliance (Khronos standard) vs legacy or proprietary graphics stacks.
Built-in safety certification readiness vs bolt-on safety.
Greater OS flexibility: supports Linux and RTOSes; many competitors focus on one or the other.
Modular architecture that isolates critical components, enabling safety verification and possibly reuse of modules across multiple products.
Let’s schedule a demo of Eagle Vision Embedded on your target platform (e.g. your choice of Intel Tiger Lake or Panther Lake, under your RTOS / safety Linux variant).
We’ll walk through:
- Rendering synthetic vision in a live scenario, measuring latency and throughput
- Safety / error handling behavior under abnormal conditions
- Certification evidence, toolchain support, and how integration fits into your safety case
Would you prefer we prepare a tailored proof-of-concept for your vertical (aviation / automotive / etc.)?