Retailers Need to Build Speed and Adaptability into their Company Workflows
Looking at startups like Omnithink AI, Ikigai Labs, Competera, and Profitmind to help retailers steer the ship with the consumer in mind at every step.
The thing with retailers is that the operational lift if extremely heavy handed and manual. The reality is you have legacy brands who are still sorting by attributes, determine mark downs by excel sheets, develop new clothing designs via intuition and sometimes miss the height of the trend. Ultimately they are not meeting their customers in an opportune time. In a day in age where leading Chinese apparel companies are bringing a product to market within days and capturing an American audience in great numbers away from the homegrown apparel brands means it’s time to look at the back end processes to see how to reduce the inefficiencies. In this segment, I’ll highlight 4 startups that are leading their category and based in the United States that I think need to be shared when it comes to bolstering retailers work efficiently.
The first company to mention is Omnithink AI, an agentic AI platform for predictive new product design and merchandising. It delivers accurate trend forecasting and interactive product innovation, combining historical and real-time social media trends with generative AI to empower data-backed decisions across design, merchandising, planning, and marketing.
What sets Omnithink apart is its ability to integrate not only with a retailer’s internal systems and social media but also directly integrates with the brand’s suppliers and manufacturers. By accessing real-time information about available fabrics, materials, production capabilities, and tariff costs, Omnithink ensures that its AI-generated product concepts and trend forecasts are grounded in manufacturing reality. This means that new product ideas aren’t just on-trend-they’re actually feasible to produce and we can understand the cost associated with it. This minimizes the risk of costly design missteps or supply chain bottlenecks.
Omnithink fundamentally shifts retailers’ approach and can rapidly identify emerging trends and bring the right products to market faster-minimizing missed opportunities and inventory risk. This means brands can finally match the speed and relevance of fast-fashion competitors, meeting customers with the right products at the right time and driving higher sell-through rates and profitability.
The next company to note is Ikigai Labs, an enterprise AI forecasting and planning platform built on MIT research and proven record with Fortune 100 customers. Through AI-powered simulations, the platform enhances existing forecasts in addition to specializing in scenarios with limited historical and unstructured data, such as new product launches. Ikigai enables what-if simulations, performs hierarchical reconciliation across categories, channels, geographies, and incorporates external signals like revenue, marketing spend, and macroeconomic —all while seamlessly integrating with existing planning processes and systems.
With Ikigai’s platform retail operators are able to determine why the trend is happening and how much inventory should one plan. Ikigai Labs empowers retailers to move beyond reactive planning and toward proactive, data-driven decision-making. With advanced forecasting and scenario modeling-even when historical data is sparse-retailers can confidently plan inventory, reduce overstock or stockouts, and respond to market shifts with agility. This results in more accurate buys, less markdown waste, and better alignment between supply and demand, leading directly to improved margins and customer satisfaction.
From a pricing perspective, gone are the day of spreadsheets, especially when they were never great to begin with. Founder Alex Galkin spent 6 years building an accurate AI-powered pricing platform called Competera. The platform empowers retailers and brands to optimize pricing decisions across online, offline, and omnichannel environments, using advanced contextual AI that analyzes over 20 pricing and non-pricing factors-including demand, elasticity, competitor actions, and seasonality-to deliver optimal, profit-generating prices in real time.
Competera’s technology continuously calculates and re-quantifies billions of possible price combinations, enabling dynamic pricing strategies that drive up to 6% increases in gross margin while building customer trust through fair and transparent pricing. Now not only can dynamic pricing be considered but also localized pricing to the factors that may pertain to a store in the midwest but not on the east coast. The personalization of pricing will have a huge impact meeting consumers where they are or making sure bundle pricing happen cohesively all within 10minutes.
By dynamically optimizing prices in real time based on dozens of contextual factors, retailers can maximize gross margins, respond instantly to market changes, and tailor pricing strategies to local conditions. The result is not only higher profitability but also increased customer trust and loyalty, as shoppers see fair, relevant pricing that matches their expectations and market realities.
Last but not least, the former expert merchandiser Mark Chrystal and AI investor Andrew Ng built Profitmind, an AI-powered retail analytics platform designed to help retailers optimize their pricing, inventory, assortment, and competitive analysis. The platform seamlessly integrates with existing business processes and systems, providing weekly prioritized action lists and daily impact tracking through an intuitive dashboard that requires less than one hour of training. Profitmind’s technology scans both internal data and external competitive intelligence to surface growth opportunities that drive measurable improvements in revenue, profit, and cash flow-helping customers achieve, on average, 21% revenue growth and 14% higher gross margins, with a one-month payback on annual cost.
Profitmind transforms retail decision-making from slow, intuition-based processes to fast, data-driven action. By delivering prioritized recommendations and real-time performance tracking, even non-technical teams can quickly identify and execute on revenue and profit opportunities. This democratizes advanced analytics, accelerates business impact, and ensures that every merchandising and pricing decision leading to rapid return on investment.
Bottom line, these four startups are not just modernizing legacy retail operations-they are enabling U.S. brands to compete on speed, precision, and customer relevance in a global market increasingly dominated by agile, tech-driven competitors. For retailers, embracing these solutions means less time spent on manual tasks and more time delivering value to customers, ultimately driving growth and long-term viability. The four startups are building in an archaic space and merchandisers are tired of the manual workflow processes and are excited for the new technology to be embedded in the brands’ DNA.