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AI Search Module ⚠️ WARNING: A Cautionary TaleHello all 😁We have long wanted to enable the AI Search module within our portal, and earlier this year we were excited to begin the process.Our DAM currently holds approximately 1.1 million assets, primarily consisting of:Imagery (key art and still photography) Logo graphics Content spanning both Sports and EntertainmentBynder initiated the setup process, which required the AI to read and evaluate every file within the portal. This took close to two weeks to complete. Once finished, the module was ready to be switched on.Where Things Went WrongUnfortunately, this is where things started to go sideways.In our environment, we make heavy use of APIs for:Metadata synchronisation and updating Asset identification and publishing to downstream productsAs soon as the AI module was enabled, we experienced a critical surge in API activity and webhook (SNS) notifications.Approximately 800,000 update events were immediately queued (against our 1.1 mil

Teams investing in AI are feeling the pressure to prove value faster than ever. In this short clip, Phyllis Davidson, VP Principal Analyst, Forrester breaks down how expectations for AI ROI have shifted from traditional 3–5 year timelines to a new reality where organizations expect positive returns in just 1–3 years.If you’re navigating AI adoption, budget justification, or leadership pressure to demonstrate impact quickly, this insight helps frame the challenge and the opportunity.Learn why the timeline is shrinking, what it means for teams, and how it affects planning across content, marketing, and operations.  

 In this clip, Chewy shares how they tackled the overwhelming challenge of managing 2.5 million digital assets, a workload that once required six media managers working full time just to keep up. They explain how content growth, personalization needs, and the rise of generative AI made manual processes impossible to scale.By leaning into AI-driven metadata tagging and smarter organization, they transformed years of manual clean-up into an automated process, ensuring every asset is now accurately tagged and searchable.It’s a great example of how AI can simplify complexity and help teams keep up with massive content demands.

Quick heads-up for anyone using Natural Language Search (NLS) in the Asset Library: You’ll get the best results by toggling between NLS and regular search depending on what you’re looking for.Here’s why:Regular SearchUse this when you’re searching for something specific, like a SKU, file name, or tag.Our standard search and NLS actually use different query methods/backends, so structured metadata (like a product number) is matched more reliably with regular search.Natural Language Search (NLS)Turn this on when you want to search by description or concept, like:“men wearing hat” “winter office scene” “modern healthcare workspace”For Natural Language Search (NLS), we use a multi-modal embedding model to retrieve results. This type of machine learning model can translate both images and text into multi-dimensional numerical vectors. Each dimension represents a feature the model has learned during training. Now, replicate that across hundreds of dimensions and you get a model capable of ca

We heard from Electra at Syngenta, who shared how AI Search helped her global team reduce the time it takes to find and localize assets from weeks to minutes to saving time, money, and headaches. And Klaas from Bynder gave us a look into what’s next for AI Search: smarter results, broader coverage, and even video similarity search!From simplifying search with natural language to automatically detecting duplicates, AI Search is clearly transforming how teams manage content and achieve business goals more efficiently. You can watch the full video here. 

As the Community’s Manager, I get to see so many creative ways our customers are solving common challenges. ​@Nicolas the DAM Librarian at Oatly (ya the oat milk brand my son drinks everyday and I use in every recipe that calls for milk) recently shared how he’s been tackling unused and hard-to-find content in their DAM, and it really stuck with me.He told us, “Bynder's AI-powered DAM has transformed how we manage our digital assets, leading to a 23% reduction in unused content and significantly improving our content ROI.”With a cleaner DAM and AI search in place, his team is finding assets faster, getting content to market more quickly, and seeing stronger performance overall.Has anyone else dealt with a cluttered DAM or struggled to get the right assets in front of the right people? What changes made the biggest difference for your team? 

The U.S. just introduced new guidelines around AI safety — and it got me thinking: how do we keep our marketing not just smart, but responsible?With more brands using AI to personalize experiences and scale content, there’s increasing pressure to show that we’re doing it the right way. That means being transparent, minimizing bias, and staying accountable for what our tools are creating and recommending.At Bynder, we believe in practical and responsible AI. We’re not here for the hype — we’re focused on solving real-world problems in a customer-centric way, with innovations inspired by the people actually using our products.Think:GenAI that scales content by creating approved, on-brand asset derivatives   Operational gains in how teams discover, manage, and activate content   Ensuring we uphold ethics, compliance, and transparencySo if you’re using AI in your DAM or marketing tech stack…Are you thinking about compliance yet? How are you preparing for AI regulation in your workflows?Let

In a customer workshop this week, someone asked: “Would you let AI publish a campaign asset on its own?”We all laughed—then paused.Because the truth is, AI is getting seriously good. From auto-tagging and smart cropping to tone matching and content suggestions, it’s making our workflows faster, smarter, and more scalable.Personally, I love the idea of AI doing the heavy lifting—clearing the runway so we can focus on strategy and creativity. But when it comes to hitting “publish” with zero human eyes? That still feels like a stretch for most of us.That said… the gap is closing. And fast.What DAM or content tasks would you feel comfortable handing off to AI today? And what’s still firmly in the “not yet” zone for you?Let’s talk about where the line is now—and where it might move next. 

Hi everyone,Join me and ​@Cliff Crosbie on March 6 at 15:00 GMT / 16:00 CET for an exclusive preview of Bynder AI! We’ll showcase how AI-powered features like Natural Language Search, Face Recognition, and Duplicate Manager are transforming content management.Plus, hear from Will Ponissi (Sauber F1 Team) on how the brand is leveraging Bynder AI to save invaluable time and get content to market faster!Don’t miss it! Register now: https://www.bynder.com/en/webinars/exclusive-preview-bynder-ai/Murat AkyolVP of Product, Bynder 

Bynder’s AI Search Experience offers your users powerful tools to find assets in the DAM. It also simplifies administration, leading to a less-cluttered DAM (and fewer requests about “missing” and “unfindable” assets). Trialing it is a great way to understand value for your users and how to integrate it into your creative operations. But a trial is only as effective as the planning that supports it: how you communicate expectations, test key use cases, and quickly demonstrate value. We’ve outlined tips for an effective trial here. A few takeaways Spread the word. Let your users know a new search experience is coming. Share an overview of the capabilities, benefits, and what they can expect. An email or homepage update - with a quicklink, news slider, or collection - is a great start.  Select a “Champion Tester” user group. All users can have access during the trial, but identify 10-20 Light or Regular users you can rely on for honest and more robust feedback. Communicate expectations