Domain-Specific GenAI Platform Purpose-Built for Your Data and Mission

At the heart of Articul8's technology is ModelMesh, which goes beyond typical model orchestration frameworks to create what the company describes as "an agent of agents" for industrial applications.

The startup's latest offering aims to tackle real enterprise problems, in a reverse of the hype cycle which has seen the concept of agentic AI bandied about and shoved into applications, in what a recent Gartner report dubbed agent washing.

One year after being spun out from Intel, Articul8 AI is pulling out the big guns with its newest benchmarking cred. Specifically, it says its Verilog-capable DSM outperforms by 2x the best open source models and at least matches Google Flash 2.0 and Chat GPT-4o.

One of the most basic and yet difficult tasks that network admins have to do is network discovery. Modern network infrastructure can include thousands of switches and routers, and configuration changes occur dynamically. It's a challenge that Articul8 is aiming to solve with its Weave Network Topology Agent.

Unlike existing frameworks like LangChain or LlamaIndex that provide predefined workflows, ModelMesh combines Bayesian systems with specialized language models to dynamically determine whether outputs are correct, what actions to take next and how to maintain consistency across complex industrial processes.

That's the Articul8 AI essence: Companies don't need bigger models, they need better models tuned for their data.

Articul8's approach challenges the assumption that general-purpose models with RAG will suffice for all use cases for enterprises implementing AI in manufacturing and industrial contexts. The performance gap between specialized and general models suggests technical decision-makers should consider domain-specific approaches for mission-critical applications where precision is paramount.

Inconsistencies in the design of these parts pose a costly and time-consuming problem for the industry. To combat this, the platform identifies potential design issues and develops solutions using three specialized AI agents; a supplier agent that makes sure parts meet requirements, a modeling agent that interacts directly with 3D modeling environments to check the geometry of parts and a process agent that ensures the correct assembly sequence is followed.