Rajeev Reddy @ReddyrajeevD - Twitter Profile

23 days ago

We have a solution to what every DTC founder out there is looking for: becoming AI-native. Brands are racing to adopt AI and stay ahead of the curve. But almost none have found a path to leverage AI for real DTC growth. - is it a bit of AI bolted onto the software you already run? - an LLM plugged in to your store? - a separate AI tool for every small job? None of that is it. That's the same store with more chaos and no upside. We believe being AI-native means having one system to run your store on its own, and do three things every store actually needs to grow. 1. The everyday work of running the store on autopliot. The store ops, content refresh, merchandising, analytics; all the work that takes more of your time than it should. 2. Experimenting across every touchpoint of your store. Tests worth running brought to you, so you find what works and compound it, day after day. 3. An intelligent & personalized experience for every shopper who lands on the store. Put these three together and you get the only things a brand ever wanted from any of this. - higher conversion - a leaner setup - better user experience And a lot less of the day spent holding it together. That's the point. Not AI for the sake of it. But one that acts as your growth operator. It's what we've been building at @spectrumaiHQ We're onboarding select brands to Spectrum. Would love to hear your thoughts. Join the waitlist using the link in the first comment.

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ReddyrajeevD retweeted

Neelesh Kumar Soni

@neeleshksoni

about 2 months ago

We scaled Tectonic to $1M ARR, then walked away from it. Tectonic was an AI-driven storefront for Shopify brands. The bet was that commerce would stop being manually operated: not a founder babysitting disconnected apps, not a team digging through dashboards and guessing what to change, but a storefront that understood the brand, customer, catalog, campaigns, and results, and kept improving itself. For the brands that made it all the way onto Tectonic, it worked. But the path to get there was too much. A brand had to move its whole storefront to us. There was migration risk, agency coordination, internal approvals, and fear that something would break. So the work we started the company to do, helping brands grow, kept getting buried under the work of selling teams on taking the leap. Our destination of taking brands from manual commerce to fully agentic commerce was right, but the ramp was wrong. So we changed the company. We turned away brands that were ready to buy Tectonic. Revenue was sitting there. The harder path was explaining to our team, investors, and customers why we were rebuilding something that was already working. The honest answer was simple: the shape no longer fit the bet. So we built Spectrum. @spectrumaiHQ gives brands a gradual ramp to the same destination: agentic commerce, inside the store they already run. A brand should not have to rebuild everything to make one workflow intelligent. It should be able to start with the PDP, or discovery, or merchandising, or retention, or CRO. Make one part of the growth system learn and act. Then another. Then another. Brands do not pay for more software. They pay for the intelligence running the work: the agents, workflows, experiments, and improvements that move the business. Our mission has not changed: self-optimizing storefronts. What changed is our path. Tectonic said: move your storefront to get the intelligence. Spectrum says: bring intelligence to the storefront you already run. We have spent the last five months building the core platform and harness for agentic commerce. Now we are going to build the next layer in public: the applications, workflows, and use cases that slow brands down every week. This is not a polished launch. It is a build, alongside the brands and agency partners closest to the work. When the shape stops fitting the bet, you change the shape. Not the bet. It's Day 1 all over again.

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ReddyrajeevD retweeted

Google AI

@GoogleAI

almost 8 years ago

Need a tool that automatically searches over neural architectures, learning to combine the best ones into a high-quality model? Check out AdaNet, a lightweight @TensorFlow-based framework for automatically learning models with minimal expert intervention. https://t.co/s7K0sYOdS3

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Rajeev Reddy @ReddyrajeevD

over 8 years ago

https://t.co/wnR8bk0mlp

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Who to follow

Abir Dubey

@abir_dubey

Football freak.....!!!! likes gadgets and robotics

Atul Mittal

@AtulMittal179

IIT Kgp, Ex Ola, Ex Meta

Mohit Verma

@mohit10verma

Building Data Infra @Linkedin. Other half to the awesome @AayushiSriv

Rajeev Reddy @ReddyrajeevD

over 8 years ago

Pandas on Ray https://t.co/OBvRQvA0jZ

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ReddyrajeevD retweeted

LinkedIn Engineering @LinkedInEng

over 8 years ago

Learn how we built a scalable ecosystem around our Couchbase deployment, which handles caching for more than 200 clusters @ over 10M qps: https://t.co/7OgcxebZsL by @matrixtek

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