AllSpice is the collaboration platform for modern hardware teams, bringing software-style workflows to electronics development so schematics, reviews, and decisions are easy to share, track, and scale.

DRCY is our AI design review agent, running automated, auditable first-pass checks directly inside your existing review flow.
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Together, AllSpice and DRCY catch real issues early, when fixes are fast and inexpensive, and make hardware development repeatable, traceable, and resilient so teams can build with confidence.
Questions and slides available here: https://hubs.li/Q0429TKH0

AllSpice.io

**Live webinar with Valentina Ratner, Co-Founder and CEO of AllSpice**

**Date:** Thursday, May 14, 2026  

**Time:** 1 PM ET, 12 PM CT, 10 AM PT

**CTA:** Register now

AI is getting easier to access. Making it useful inside hardware engineering is the harder part.

Hardware teams are facing increased pressure to achieve the types of efficiencies and scale that software developers have been experiencing with AI for the last 2-3 years. Join this webinar to learn how AllSpice customers are building the backbone of their AI infrastructure with AllSpice.

In this session, AllSpice CEO Valentina Ratner will share what we are learning on the ground from leading hardware organizations as they adapt their engineering workflows for AI. All of our highest performing teams tell us one thing: they want better control and utility of their design data.

The focus will be practical and product-agnostic: how the most innovative hardware teams are thinking about AI, automation, and data infrastructure for their hardware development processes.

## What you will learn

*   How leading hardware teams are thinking about AI as part of the engineering workflow, not a standalone experiment.
*   Why structured design data and review context matter before AI can produce useful results.
*   How to decide which problems should be solved with deterministic automation, AI agents, or human judgment.
*   Why adoption and workflow fit matter as much as model capability.
*   How teams can start with one workflow, one team, and one measurable outcome.

## Why this matters now

Hardware teams are under pressure to move faster, reduce late-stage issues, and get more leverage from the engineering talent they already have. AI can help, but only when it is connected to the right data, instructions, standards, and review process.

The teams getting the most value are not trying to use AI for everything. They are choosing the right tool for the right job:

*   Deterministic systems for known, repeatable checks.
*   AI agents for ambiguous review work, context synthesis, and blind-spot detection.
*   Engineers for tradeoffs, exceptions, validation, and final decisions.

## Who should attend

This session is built for:

*   Hardware engineering directors
*   VPs of engineering
*   CTOs and technical executives
*   Product and program leaders working with hardware teams
*   Engineering managers evaluating AI for hardware workflows
*   Teams looking for a practical framework before scaling AI adoption
