The first LLM-powered platform to help chip architects design precise and high-quality specification documents.
Visibl Platform is an AI-driven solution designed for system architects, streamlining the system-level design and specification phase of semiconductor architecture.
As AI tools that act autonomously (agentic AI) become more advanced, they serve as independent problem-solvers, given an end goal and capable of figuring out how to accomplish it on their own at the implementation level. These AI agents effectively multiply the engineering workforce, boosting productivity as if the team had grown many times over. This increase in capacity allows companies to take on far more complex design projects than ever before.
However, as designs grow in complexity, there is a rising need for better planning and coordination in the early stages of development. Currently, system architects — the engineers responsible for defining how all parts of a chip fit together — still rely on outdated methods like Excel sheets, scattered documents, and informal, tribal knowledge. This fragmented approach makes it difficult to create accurate, efficient plans, especially as designs become more sophisticated.
In the coming years, we expect a fundamental shift in how engineering teams allocate their time and resources. As AI agents handle more implementation tasks (such as coding, verification, and testing), engineers will increasingly focus on high-level planning, system architecture, and precise specification work. This shift from implementation-level engineering to architecture and specification emphasizes defining what the system needs to do and how it should be structured, rather than handling the low-level execution details.
This transition highlights the importance of well-defined architecture and specifications from the start, as they become the guiding blueprint for AI agents executing the design. Yet, despite this new focus, there are virtually no AI tools designed to support this critical phase. This gap presents a significant opportunity for us to create a platform that helps engineers define, refine, and validate high-level specifications, driving more efficient, scalable, and innovative semiconductor design.
We are building the first LLM-powered platform to help chip architects design precise and high-quality specification documents.
Crafting chip specifications is a detailed and time-consuming process that involves combining inputs like spreadsheet models, research papers, and existing chip designs from within the company. The outcome is a lengthy document, often hundreds of pages, that serves as a blueprint for the engineering team to follow during development.
This is the perfect task for LLMs to revolutionize, and we're building the first LLM-powered platform to streamline this process. Here's how we're executing this vision:
We start by addressing a core pain point—extracting insights from existing RTL code and design documents. This builds trust in AI workflows by demonstrating how LLMs can securely and effectively streamline semiconductor documentation, setting the foundation for broader adoption. This has been built and is production-ready →
Next, we expand to a dynamic tool that centralizes inputs—such as past chip designs, research, and models—into a living specification. This allows architects to easily create, revise, and refine specifications, ensuring they stay current as projects evolve.
Once the specification workflow is established, our platform will provide real-time feedback. It will identify gaps, suggest optimizations, and reduce errors, making specifications not just complete but also performance-driven.
As engineering workflows evolve, AI agents are expected to take over implementation tasks like coding, verification, and testing. This shift will free engineers to focus on high-level planning, system architecture, and precise specification work—where the foundation of chip innovation is laid. Our platform will be a critical tool at this architectural level, empowering architects to explore novel designs, iterate faster, and develop next-generation architectures. By streamlining and optimizing workflows, we enable teams to reimagine how chips are designed, ensuring they stay ahead in a rapidly advancing industry.
With Moore's Law slowing and demand for specialized ASICs surging, modern chip designs have outgrown the traditional tools silicon architects rely on. Architects primarily use Excel for modeling and estimating system requirements, research papers and reports for insights, and manually compile information from past chip designs. While familiar, these tools lack the precision, collaboration, and agility needed to manage the increasing complexity, tighter integration, and advanced use cases of today's semiconductor architectures—demands that outdated workflows cannot meet.
Our platform is the inevitable solution, revolutionizing specification creation and management to help architects navigate complexity, explore innovative designs, and deliver cutting-edge chips faster. As chips become more specialized and central to the AI-driven future, this tool will be indispensable, setting a new standard for semiconductor design. Without it, engineers risk falling behind the demands of tomorrow's technology.
The first LLM-powered platform to help chip architects design precise and high-quality specification documents.
Visibl Platform is an AI-driven solution designed for system architects, streamlining the system-level design and specification phase of semiconductor architecture.
As AI tools that act autonomously (agentic AI) become more advanced, they serve as independent problem-solvers, given an end goal and capable of figuring out how to accomplish it on their own at the implementation level. These AI agents effectively multiply the engineering workforce, boosting productivity as if the team had grown many times over. This increase in capacity allows companies to take on far more complex design projects than ever before.
However, as designs grow in complexity, there is a rising need for better planning and coordination in the early stages of development. Currently, system architects — the engineers responsible for defining how all parts of a chip fit together — still rely on outdated methods like Excel sheets, scattered documents, and informal, tribal knowledge. This fragmented approach makes it difficult to create accurate, efficient plans, especially as designs become more sophisticated.
In the coming years, we expect a fundamental shift in how engineering teams allocate their time and resources. As AI agents handle more implementation tasks (such as coding, verification, and testing), engineers will increasingly focus on high-level planning, system architecture, and precise specification work. This shift from implementation-level engineering to architecture and specification emphasizes defining what the system needs to do and how it should be structured, rather than handling the low-level execution details.
This transition highlights the importance of well-defined architecture and specifications from the start, as they become the guiding blueprint for AI agents executing the design. Yet, despite this new focus, there are virtually no AI tools designed to support this critical phase. This gap presents a significant opportunity for us to create a platform that helps engineers define, refine, and validate high-level specifications, driving more efficient, scalable, and innovative semiconductor design.
We are building the first LLM-powered platform to help chip architects design precise and high-quality specification documents.
Crafting chip specifications is a detailed and time-consuming process that involves combining inputs like spreadsheet models, research papers, and existing chip designs from within the company. The outcome is a lengthy document, often hundreds of pages, that serves as a blueprint for the engineering team to follow during development.
This is the perfect task for LLMs to revolutionize, and we're building the first LLM-powered platform to streamline this process. Here's how we're executing this vision:
We start by addressing a core pain point—extracting insights from existing RTL code and design documents. This builds trust in AI workflows by demonstrating how LLMs can securely and effectively streamline semiconductor documentation, setting the foundation for broader adoption. This has been built and is production-ready →
Next, we expand to a dynamic tool that centralizes inputs—such as past chip designs, research, and models—into a living specification. This allows architects to easily create, revise, and refine specifications, ensuring they stay current as projects evolve.
Once the specification workflow is established, our platform will provide real-time feedback. It will identify gaps, suggest optimizations, and reduce errors, making specifications not just complete but also performance-driven.
As engineering workflows evolve, AI agents are expected to take over implementation tasks like coding, verification, and testing. This shift will free engineers to focus on high-level planning, system architecture, and precise specification work—where the foundation of chip innovation is laid. Our platform will be a critical tool at this architectural level, empowering architects to explore novel designs, iterate faster, and develop next-generation architectures. By streamlining and optimizing workflows, we enable teams to reimagine how chips are designed, ensuring they stay ahead in a rapidly advancing industry.
With Moore's Law slowing and demand for specialized ASICs surging, modern chip designs have outgrown the traditional tools silicon architects rely on. Architects primarily use Excel for modeling and estimating system requirements, research papers and reports for insights, and manually compile information from past chip designs. While familiar, these tools lack the precision, collaboration, and agility needed to manage the increasing complexity, tighter integration, and advanced use cases of today's semiconductor architectures—demands that outdated workflows cannot meet.
Our platform is the inevitable solution, revolutionizing specification creation and management to help architects navigate complexity, explore innovative designs, and deliver cutting-edge chips faster. As chips become more specialized and central to the AI-driven future, this tool will be indispensable, setting a new standard for semiconductor design. Without it, engineers risk falling behind the demands of tomorrow's technology.