Saturday, 12 July 2025
At the forefront of solving these issues is KnowDis.ai, a fast-scaling AI-first enterprise shaping the next generation of search, personalisation, and multilingual intelligence for e-commerce platforms. With a team of globally trained researchers, a modular suite of production-ready AI tools, and a relentless focus on real-time performance, KnowDis.ai is redefining how businesses navigate the complexity of consumer intent.
Before diving into KnowDis.ai's solutions, it's crucial to understand the magnitude of the problem they're solving. Research indicates that poor search experiences cost e-commerce platforms billions in lost revenue annually. When a customer types "samsnug mobil" instead of "Samsung mobile," or searches for "kurta for diwali function" in Hinglish, traditional search engines often fail to bridge the intent gap. These failures not only result in lost sales, but also erode customer trust and brand loyalty.
In India's diverse linguistic landscape, where code-mixing is the norm and regional variations abound, the challenge multiplies exponentially. A shopper in Mumbai might search for "vadapav maker," while someone in Chennai looks for "medhu vada machine"—both seeking similar kitchen appliances. KnowDis.ai recognised this complexity early and built its entire technology stack around solving real-world search challenges, not theoretical ones.
Designing for Scale: Modular AI for Real-World Commerce
KnowDis.ai's AI suite is not just another toolset—it is a plug-and-play ecosystem. Unlike monolithic systems that require heavy customisation or retraining to fit different industries, KnowDis.ai adopts a modular AI architecture that brings flexibility, performance, and scalability to the forefront.
The suite includes:
This composable architecture enables e-commerce platforms to tailor solutions to their unique needs, whether they are a retail giant grappling with millions of daily queries or a niche marketplace serving a multilingual audience in regional India.
Chat That Converts: Search as a Sales Conversation
ChatSearch is an LLM powered Intelligent Product Search ChatBot which acts like a shopping assistant to help customers learn about a category and find relevant products.
Unlike traditional search boxes that struggle with vague, misspelt, or multi-lingual queries, ChatSearch provides a dynamic, conversational interface that understands context, intent, and nuance. Whether a user is exploring options (“best generator for hostel use”), typing in code-mixed queries (“meetha paani ka filter chahiye”), or navigating in Tamil or Hindi, ChatSearch responds like a real sales assistant—explaining, recommending, and guiding. Designed for natural dialogue and integrated with product catalogues, ChatSearch is not just answering questions—it’s converting curiosity into commerce.
GenSearch is KnowDis.ai’s generative AI solution designed to deliver accurate search results for complex user queries. It leverages state-of-the-art LLMs to overcome the limitations of traditional keyword-based systems. Built for real-time commerce, GenSearch achieves inference latency under 300 milliseconds and scales effortlessly to handle over 150 million products. Its dynamic architecture enables updates to various aspects of product listings, ensuring up-to-date relevance. By combining high performance with real-time response and adaptability, GenSearch sets a new benchmark for intelligent product discovery in large-scale e-commerce environments.
Fix the Query, Fuel the Sale: Orto's Impact on Search Correction
Typographical errors and domain-specific phrasings often derail e-commerce search systems. Consumers search for "redmi phne cover" or "wireles mouse," and traditional keyword-based engines return empty or irrelevant results. Orto, KnowDis.ai's advanced query corrector, bridges this intent gap with precision.
Using domain-trained generative models, Orto transforms noisy queries into meaningful ones, accounting for contextual variations, regional spellings, transliterations, and even intent disambiguation. Orto understands domain-specific terminology in areas such as electronics, fashion, and grocery, making it an ideal fit for large-scale Indian e-commerce platforms.
Orto isn't just correcting queries—it's increasing session conversions, reducing bounce rates, and improving catalogue recall.
What sets Orto apart is its sophisticated approach to understanding context. Traditional spell-checkers rely on dictionary lookups and edit distance algorithms, which fail spectacularly with domain-specific terms, brand names, and multilingual queries. Orto leverages a multi-tiered approach:
First, it employs phonetic matching to handle transliteration variations, understanding that "colgate" and "kolgeit" refer to the same brand. Second, it utilises contextual embeddings to disambiguate queries where spelling correction alone is insufficient. For instance, "apple watch" shouldn't be corrected to "apple wash" despite the phonetic similarity. Third, Orto maintains dynamic vocabularies that update with trending products, new launches, and seasonal items, ensuring that "iPhone 15 Pro Max" isn't mistaken for a typo even on launch day.
Product discovery isn't limited to keywords. Increasingly, consumers upload a photo of a celebrity outfit or screenshot a friend's accessory to find similar items. Gazo, KnowDis.ai's image-based search module, powers "search by image" experiences across fashion, furniture, and lifestyle categories.
By extracting high-resolution embeddings using state-of-the-art vision transformers, Gazo enables:
For fashion platforms, Gazo is a game-changer. It enables intuitive exploration, even when users don't know what to type, democratising discovery for non-English speakers, Gen Z shoppers, and visually driven users.
India's next 500 million users are expected to come online in vernacular languages. While the content ecosystem is evolving, search and commerce interfaces have lagged behind in terms of multilingual inclusivity. Indifai, KnowDis.ai's multilingual NLP engine, changes that.
Indifai powers:
Its hybrid architecture, combining the latest AI model architecture and client-specific customisation, ensures accuracy, fluency, and catalogue alignment. E-commerce partners using Indifai have seen a 3x improvement in discovery for users searching in Indian languages such as Hindi.
In a recent rollout, Indifai enabled a major grocery retailer to serve users typing "aalu 2kg" or "milk sachet" in mixed Hindi-English seamlessly—automatically fetching SKU-matched listings with full unit and quantity disambiguation.
MeraJawab: Smart Hindi Q&A
MeraJawab lets users ask questions in Hindi—casual or formal—and get instant, accurate answers powered by English LLMs. It supports both Devanagari and Roman scripts, making AI truly accessible in the language people speak.
Real-World Impact: Deployment Excellence
The true measure of any AI solution lies in its real-world impact. KnowDis.ai's deployment across various e-commerce platforms demonstrates the transformative power of their modular approach. The company's solutions have been battle-tested across diverse scenarios—from handling flash sales that involve millions of concurrent queries to facilitating long-tail product discovery in regional markets.
What distinguishes KnowDis.ai's deployments is their seamless integration with existing infrastructure. Unlike solutions that require complete system overhauls, KnowDis.ai's modules can be adopted incrementally, allowing businesses to see immediate value while planning broader digital transformations. Their deployment methodology emphasises rapid prototyping, A/B testing capabilities, and continuous performance monitoring, ensuring that AI improvements translate directly to business metrics.
The company's client-first approach extends to post-deployment support, with dedicated teams monitoring query patterns, identifying edge cases, and pushing model updates without service interruption. This commitment to operational excellence has made KnowDis.ai a trusted partner for enterprises where search performance has a direct impact on revenue.
One of KnowDis.ai's foundational principles is that AI should fit the business, not the other way around. That's why their tools are not monolithic APIs but adaptive models fine-tuned to each client's catalogue, user behaviour, and UI constraints.
Take HiRo, for instance—a high-resolution product classifier that performs both hierarchical and flat categorisation. Or Lipi, a multilingual attribute extractor capable of understanding technical specifications across 20+ verticals. These models are not static—they evolve as the catalogue grows, the user base diversifies, or new products enter the market.
Moreover, all models are designed to work under production-grade constraints: inference latency under 300 ms, scalable across 150 million+ SKUs, and compatible with varied data pipelines, including Spark, Kafka, and REST APIs.
While e-commerce is the most visible use case, KnowDis.ai's solutions are applicable across various industries.
This cross-domain versatility is not an accident—it's by design, enabled by a shared AI backbone with interchangeable components and retrainable modules.
What makes KnowDis.ai's innovation sustainable is its world-class team. With experts from IITs, IISc, IIITs, DSTI Paris, and Carnegie Mellon, the team combines academic rigour with product intuition. Their strong research partnerships with IIT Delhi and IIT Bombay ensure that the latest advances in transformer models, contrastive learning, and generative architectures are rapidly applied in real-world settings.
CEO Saurabh Singal, a graduate of IIT Delhi and Carnegie Mellon and a former hedge fund manager, brings a rare blend of quantitative precision and product foresight. Co-founder and CTO Neeta Singal anchors the product engineering with enterprise-grade discipline.
Their open culture—where freshers participate in design reviews and Ph.D. researchers experiment with production code—has attracted and retained top-tier talent across India.
As e-commerce becomes more intelligent, user expectations will continue to evolve. Consumers will want voice queries, hyper-personalised results, real-time assistants, and frictionless UX across devices and languages. The question isn't whether AI will power this—it's whose AI will do it best.
KnowDis.ai is positioning itself as the engine of transformation. With a future-ready modular stack, real-time infrastructure, and a growing base of satisfied partners, KnowDis.ai isn't just building search pipelines. It's building the cognitive fabric of tomorrow's digital commerce.
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