Our Hybrid Approach™ to enterprise AI changes everything. We pair elite human experts with a purpose-built agentic platform to create custom solutions that are human-led, agent-executed, and deliver outcomes from day one. We don’t just consult. We collaborate as your partner, from first engagement to lasting transformation. While others get stuck in pilot purgatory, we take businesses from concept to production to scale by solving key problems of context and execution. It’s not capability that today’s AI lacks, but understanding. Without deep, structured knowledge of your business, your workflows, and what your data actually means, pilots look promising but break when stretched. We solve this on day one. Every engagement starts with your own Enterprise Context Engine™: a living intelligence at the heart of your business. It unifies your data, maps your workflows, and learns from every use case. The more you build, the smarter it gets. Every iteration feeds the engine, and the intelligence compounds. That makes the second problem, execution, no longer a roadblock. When your AI architecture understands your business, problems, and workflows, it works with you, making iterative improvements easy and execution at an enterprise scale possible. We work with industry leaders in manufacturing, retail and consumer goods, financial services, supply chain, and infrastructure. Future-proofed by design. Outcome-led by default. Recognized as a top 5 Data Science and Machine Learning platform by G2 for customer satisfaction.
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Austin, Texas, US
A heart rate reading on its own tells you nothing. Combine it with altitude, effort, and recovery and you can actually train. Zak Zakour says plant floors work the same way. The data is already there, sitting in systems that don't talk to each other. Thirty years in the industry taught him why most pilots die on the plant floor. He explains it in under two minutes. Press play. #IndustrialAI #Manufacturing #EnterpriseAI #OperationalExcellence #RealAITransformation
What are you doing with AI?
Search AI and retail and you get the same handful of giants running multi-year programs nobody else can fund. Shatay Trigère, CMO at RapidCanvas, on why that is no longer the whole story. Smaller retailers now compete on agility, speed, and precision, without an army of data scientists behind them. David does not get bigger. He gets a better slingshot. Full conversation and deep dive: links in the comments. 👇 #RetailAI #AgenticAI #EnterpriseAI #RetailTech #AIStrategy #RealAITransformation
Bain's 2026 PE Report affirms that returns now hinge on EBITDA growth from operational efficiencies. Ian Venerable, AI Engagement Manager at RapidCanvas, has been partnering with PE firms looking to create value, and has observed that technology-driven operational alpha is the quickest and most cost-effective way to get there. Here's how RapidCanvas works with PE operators to produce better exits: 1. Targeted Scope, High Impact Large, horizontal rollouts of fancy new “AI Native” ERPs, standalone data platforms, or a suite of disparate SaaS tools, and standing it up yourself or with consultants, means slow implementation and paying for features you never use. A targeted custom build against the actual bottleneck moves a number faster and carries less risk, which matters when value creation is measured in the first 100 days. 2. Create Enterprise Value Anything built during the hold period should be an asset a future acquirer pays for. A black-box tool or vendor lock-in becomes a liability that gets discounted during due diligence. RapidCanvas builds solutions that are your IP and survive the transaction, adding to the sale price. 3. Experts Who Know What to Build AI is expensive, and despite the headlines, building a complex multi-agent system for a problem that traditional code can solve is waste. At RapidCanvas we know what AI is and is not good at. We apply emerging technologies like AI and machine learning where they earn their place, but our primary focus is on delivering real financial impact, not cool proof of concepts. If you're curious how we've been putting these principles to work across PE-owned businesses, or how it might translate to your portfolio, feel free to reach out to Ian — meeting link in the comments. #PrivateEquity #OperationalExcellence #PE #AI #RealAITransformation
People. Mission. Opportunity. That's what our CTO Uttam Phalnikar says keeps him excited about building at RapidCanvas, and why he thinks the timing has never been better for people who want to do meaningful work in AI. If that sounds like the kind of place you'd want to build, we should talk. #RapidCanvas #RealAITransformation #AgenticAI #EnterpriseAI #LifeAtRapidCanvas #TechCareers
We asked what business outcome would create the greatest value from AI. Nobody said chatbots. They said EBITDA, labor productivity, and better decisions. Thanks to Neal McNamara for a sharp recap of our July session together. And to Brian Heckler, Jared Kelso and Virtas Partners team for a great conversation.
One poll result jumped off the page from the Virtas Partners and RapidCanvas webinar in July. When asked what business outcome would create the greatest value, respondents overwhelmingly pointed toward: EBITDA improvement Labor productivity Better decision-making Not chatbots. Not AI agents. Not model comparisons. Business outcomes. The most successful AI initiatives start with a P&L conversation, not a technology conversation. If an AI initiative cannot ultimately influence growth, efficiency, forecasting, margins, or working capital, it becomes difficult to justify scaling it. That's where many organizations are stuck today. They have pilots. What they need is impact. #PrivateEquity #AI #EBITDA #ValueCreation #Operations
You will not solve the whole problem in four to six weeks. You will solve enough of it to know you are on the right track. Rahul Pangam, CEO and Co-founder, RapidCanvas, on scoping AI work to validate fast. Pick the business outcome. Pick a slice small enough to test. Get to a real result, and the confidence to keep going comes with it. There is enough science fiction around AI that proving the approach matters more than the size of the first win. Full conversation and deep dive: links in the comments. ⬇️ #EnterpriseAI #AgenticAI #AIStrategy #AIROI #DigitalTransformation #RealAITransformation
Your sales team already knows next quarter's demand. Your forecast doesn't. Most distributors plan inventory in a spreadsheet stitched together from sources that never talk to each other: ERP history, a CRM pipeline full of forward-looking signal that no process reads, and the experience living in one planner's head. It holds up in a normal month. It comes apart at exactly the moments that matter: when the market turns, when a project pipeline fills up or dries up, when your most experienced planner retires. In the latest post in our Architects Behind AI series, Fuge Zou, Head of AI Innovation, writes about the work with an industrial distributor. Why a time-series model is structurally blind to demand that has not closed yet. Why wiring the CRM straight into the forecast makes it whipsaw at every quarter end. And what it takes to route each SKU to the method that fits how it actually sells. Read the full blog. Link in the comments. 👇 #DemandForecasting #SupplyChain #EnterpriseAI #IndustrialDistribution #RealAITransformation
Our team has range. Meet Ryan Cohen: sales leader by day, Austin house DJ by night, and AI builder in between. This is the kind of curiosity we love at RapidCanvas. 🎧 #RapidCanvas #LifeAtRapidCanvas
Most of my LinkedIn network knows me as just another Account Executive/Sales Leader. Only about 5% know what happens after the laptop closes every night. I've been living a double life... By day, I'm Ryan Cohen...not the billionaire CEO Ryan Cohen of GameStop (wish I could stop getting all his phone calls) rather, the Ryan Cohen who helps lead sales at RapidCanvas, a global AI startup based here in Austin. We build bespoke AI solutions for companies in record time, at a fraction of the cost of the competition. By night, I'm Ryan Zeldin- a house DJ/ Producer. It started long before any of that — first chair trumpet in middle school, self-taught guitar player off YouTube tutorials in high school, my first set of decks in college spinning at house parties. Then 2021 happened. Stuck at home during Covid, I used my company Dropbox's employee stipend benefit to enroll in a DJ Academy based out of South Florida. I learned from a touring artist who took me from bedroom mixes to real club sets- all virtually over Zoom. Since then, I've worked my way into nearly every major club in Austin. Tech House music is my main genre, however I love anything House/EDM. With my background in playing guitar, I mix in classic rock from some of my favorite bands. What keeps me going: watching Drew Taggart and Alex Pall build The Chainsmokers, (one of my favorite artists) into a global act while staying entrepreneurs at heart. They don't just headline festivals — they back startups through Mantis VC. I've been to over 20 Chainsmokers shows at my favorite club, XS, in Vegas. Seeing how they balance touring with corporate success is incredibly motivating. Turns out the guy chasing your signature on a Friday afternoon might be chasing a different kind of drop by midnight. Check out my website site below in the comments that I built using Claude. Grateful for the skills I'm learning with AI here at RapidCanvas. What's the side of you that most of LinkedIn never sees? #SideHustle #DJLife #WorkLifeBalance #Austin #Entrepreneurship #RAPIDCANVAS
Enterprise AI does not get solved by picking the right model. It gets solved by understanding the business problem well enough to know what to build around it. That idea runs through our conversation with Uttam Phalnikar, Co-founder and CTO at RapidCanvas, on how the work actually happens here. What he covers: • Why the variety is the point. Fraud detection for a financial services customer one day, manufacturing process automation the next, healthcare after that. Different data, different goals, no single LLM that handles all three. • How the skills engine we are building alongside our context engine acts as guardrails, keeping AI inside defined boundaries so solutions come out reliable instead of improvised. • Why product, engineering, and delivery work as one team here rather than handing work down a line, and what that does to how fast solutions get built. His line that stuck with us: understanding the business need is what makes the difference, not the technology alone. Watch the full conversation with Uttam — link in the comments. ⬇️ #InsideRapidCanvas #EnterpriseAI #RealAITransformation #LifeAtRapidCanvas
AI adoption fails when it arrives as a boulder rolling downhill. Jim Wells, VP and GM, Enterprise AI Solutions at RapidCanvas, on building it as a grassroots effort instead: a champion in each functional area, sourcing use cases from the people who live with the problems. When teams own the use case, the fear drops. Full conversation and deep dive: links in the comments. ⬇️ #EnterpriseAI #AIAdoption #ChangeManagement #AgenticAI #DigitalTransformation #RealAITransformation