And it’s already in use at global manufacturers like Techtronic Industries (TTI), the $14 billion parent company of RYOBI, and wind turbine blade manufacturer TPI Composites in beta. Both companies are testing its capabilities with the aim to catch design issues earlier and ensure every review meets a consistent standard.
“We didn’t plan to launch AutoReview this early, but the progress from our team – and the response from customers – made it clear the time is now,” says Adam Keating, Co-Founder and CEO of CoLab. “According to our survey of 250 engineering leaders, 23% of engineering time is currently spent on non-value-added work,” he continues. “Even if AutoReview only replaces that portion, teams could reclaim nearly a quarter of their time.”
AutoReview works by scanning documents and immediately identifying common issues, including errors in drawings and design for manufacturing (DFM) optimisations. For example, it will flag if there are missing or incorrect countersinks within drawings, the measurements responsible for ensuring the head of a screw sits flush or just below a surface. It also checks moulding measurements in designs to make sure wall thickness dimensions will work and that moulds are easy to remove for manufacturing.
The software can also automatically surface lessons learned from past programs during reviews of in-work designs that use similar geometry or the same parts, helping avoid costly mistakes being replicated across different designs This can create significant savings by reducing scrap rates and warranty claims. In 2024, the US car and cycles industry alone paid over $12 billion in warranty claims, a 17% increase from 2023 according to Warranty Week.
“If a sharp internal corner previously caused fatigue failures and warranty claims, AutoReview can flag similar geometry in a new design and surface that past feedback for the current design team to use,” explains Adam. “As product complexity increases, it’s easy for these types of errors to slip through the cracks. But ultimately these are preventable costs.”
In complex manufacturing industries such as Aerospace and MedTech, missing one dimensional check can mean reworking a drawing or delaying a critical product milestone. AutoReview can replace redundant manual checks and deliver greater consistency and adherence to company-specific design rules by validating 2D drawings and 3D models across different programmes including Creo, NX, SolidWorks, and CATIA.
“Validators within these design teams currently spend hours checking every surface for proper dimensions but AutoReview can perform these checks within minutes,” continues Adam. “This gives engineers more time to focus on value-add work, like bills of materials (BOM) cost reduction – savings that are critical to help offset the tariff and supply chain pressures these companies are exposed to right now.”
Beyond adherence to standards, AutoReview can also automatically identify design for manufacturing (DFM) optimisations. This capability has caught the attention of automotive OEMs and tier 1 suppliers, who see an opportunity to reduce scrap, prototyping, and tooling costs.
The solution also ensures design IP is protected across manufacturing sectors, as AutoReview runs inside CoLab’s secure environment and works with existing PLM infrastructure. This means teams can move files into review without taking them out of their governed systems.
CoLab’s core Design Engagement System (DES) is already delivering measurable results for engineering teams at Schaeffler, Johnson Controls and Mainspring Energy. These teams have cut BOM costs by up to 50% and accelerated design cycles by 100%, launching products months earlier.
“AI won’t replace engineering teams. But it will take on the repetitive decisions that slow engineers down, so they can spend more time solving hard problems and pushing the product forward. It will also protect engineering organisations from the wave of retirements and the threat of losing institutional knowledge.,” concludes Adam. “Fast forward a few years, engineering companies that don’t leverage AI to automate administrative tasks, prevent errors, and reduce costs won’t stand a chance.”
