CogNerd News & Milestones

What the Startup India Seed Fund Scheme supports

The Startup India Seed Fund Scheme was created to help eligible startups move through the expensive steps between an idea and a product that customers can use. Its stated purposes include proof of concept, prototype development, product trials, market entry and commercialization. Startups are selected and supported through approved incubators rather than receiving funding through a general public grant process. Innovation Mission Punjab describes SISFS as one of the initiatives through which it supports early-stage ventures in the state.

For a young software company, that structure matters. Product assumptions need to be tested, measurement methods need to be repeatable, and early users need to see enough value to keep using a product. A seed award can make room for that work before the business has reached the scale expected by larger investors. The award through IMPunjab places CogNerd among the early-stage startups supported by the program as it moves from product development toward wider adoption.

The problem CogNerd is building for

CogNerd was founded by Aman Mundra and Sakshi Dhawan, PhD, bringing together production AI engineering and research into human behavior. The team is building an AI search visibility platform for brands that need to understand a changing discovery journey. A buyer can ask ChatGPT, Gemini or another answer engine to compare providers and receive a recommendation without seeing a conventional search results page. A strong search ranking alone cannot tell a marketing team how that conversation represented its brand.

CogNerd measures the prompts customers ask, whether a brand is mentioned or cited, which competitors appear alongside it, and what sources are shaping the response. Its wider platform connects those signals to website readiness, content opportunities and search analytics. The aim is to help a team move from a vague concern about being invisible in AI answers to a specific question it can investigate and improve.

What comes next

The SISFS milestone gives CogNerd support at a point where careful product development matters more than broad claims about the future of AI. The company is focused on making its visibility measurements useful across different engines and prompts, and on connecting the results to actions customers can take. As that work reaches users, CogNerd will publish the product changes and evidence behind them.

The award marks progress for CogNerd and for Punjab's growing startup community. Its lasting value will be measured in the product the team builds and the decisions that product helps customers make.

What readers can expect from CogNerd

An AI visibility report is useful when it changes what a team does next. CogNerd's product is designed to show where a brand appears in relevant answers, whether that appearance is favorable and which sources an answer draws upon. From there, a business can decide whether it needs a clearer product explanation, better evidence for a claim, more complete answers to buyer questions or a stronger technical search foundation. The company also connects AI visibility with traditional SEO and analytics, because customers ultimately need to understand the whole journey from discovery to action.

The program award gives CogNerd a chance to keep refining that workflow with the discipline early products require. The useful outcome is not simply more dashboards or more prompts scanned. It is a clearer connection between the questions people ask, the answers AI systems give and the practical changes a brand can make. That is where CogNerd intends to focus its next stage of work.

How IIT Mandi Catalyst EIR supports founders

IIT Mandi Catalyst is a technology business incubator with several entrepreneur-in-residence routes. Its published EIR materials describe a period of focused venture development, with guidance on business concepts, product strategy and commercialization, along with access to an innovation community. In that setting, founders can test an idea, refine a product direction and learn from people building businesses around emerging technology.

The EIR model is useful because a startup rarely fails for lack of ideas alone. It must decide which problem to solve first, put a product in front of users, learn what they actually need and then improve it. Working within an incubator can give a founding team a clearer rhythm for those decisions and a wider set of people from whom to learn.

Why CogNerd is focused on AI search

CogNerd's starting point is a gap in existing marketing measurement. Search Console can show queries and clicks, while analytics can show visits and conversions. Neither fully explains what an AI assistant says when a customer asks for the best option in a category. A brand may be mentioned without being recommended, cited from an outdated source or missed entirely while a competitor becomes the example.

CogNerd is building visibility workflows that examine those answers across prompts and AI engines. Teams can look at mentions, citations, relative presence and the questions where their brand is absent. The product also connects those findings to content and website changes, because a measurement only helps if it informs a next action. This makes the challenge as much about interpreting user behavior as it is about collecting technical signals.

Using the experience to build better

The Catalyst EIR experience comes at a valuable time for a company working in a young category. CogNerd can use the period to test how clearly it explains the problem, which findings customers trust, and which recommendations lead to meaningful improvements. The goal is a platform that lets a team return to the same set of questions over time and see whether its work changed its visibility.

CogNerd will continue to share concrete product progress as it develops. The program is one step in that work: a chance to combine technical development with disciplined learning about the customer problem.

The product questions behind the EIR period

An early-stage company has to distinguish a striking demonstration from a repeatable product. A screenshot showing that one assistant mentioned a brand is interesting, but a marketing team needs to know whether that result holds across many prompts and over time. CogNerd is working on that more demanding question. Its workflows group related buyer prompts, monitor brand and competitor appearances and identify the sources cited in answers. Those observations can then be compared after a company changes its website or content.

The EIR setting is relevant because it gives the team a chance to challenge what it is measuring and how it explains the result. If users cannot tell which gap matters most, the data has limited value. CogNerd's goal is to make the measurement both technically sound and easy for a business to act on. The experience at IIT Mandi Catalyst can help the founders keep those two requirements in view while they develop the next version of the product.

What IMC Aspire brings together

Aspire brings startups into a larger technology gathering where product demonstrations, mentoring, industry conversations and investor engagement can take place. Its official program describes showcases, workshops and opportunities for founders to meet people across the technology ecosystem. Selection creates a chance to put an emerging product and its underlying problem in front of an audience beyond its immediate customer base. The platform connects emerging companies with a national audience for their ideas and products.

For CogNerd, the fit is direct. Conversational systems have changed how people ask for information. Instead of typing a short keyword and comparing a list of pages, a buyer may ask an assistant to recommend software, explain a service or name a trusted provider. The answer can shape a decision before a visitor ever arrives at a brand's website. That is the shift CogNerd is working to measure.

CogNerd's view of discovery

CogNerd helps brands investigate what AI systems say about them across prompts and engines, which sources appear in answers, and which competitors are recommended instead. It brings together prompt intelligence, brand mentions, citations and competitive analysis, then ties those observations to content and website improvements. The platform is intended to make AI visibility a repeatable measurement problem, rather than a collection of one-off screenshots.

That problem is relevant to a wide technology audience. Product teams want to know how their companies are described. Marketing teams need to see where visibility is weak. Founders need to understand whether people asking for solutions in their category are hearing about them. CogNerd's presence at IMC gave the team a setting to explain these questions and learn how others are thinking about AI-led discovery.

Beyond the event

Being selected for Aspire is a company milestone, but the work continues after the event. CogNerd's priority is to turn feedback and industry conversations into clearer product decisions: which prompts to monitor, how to explain citations, and how to connect a visibility gap to the next useful action.

The company will keep sharing product updates and lessons from this developing category. The opportunity at IMC is part of a broader effort to make the way brands appear in AI answers understandable, measurable and useful.

Why this audience matters

India Mobile Congress brings together companies working across communication, software, infrastructure and emerging technology. In that environment, an AI search visibility platform can be discussed as more than a marketing dashboard. It raises questions about how information is found, which sources an AI system chooses to cite and how a business can make accurate information about itself easier to discover. Those questions matter to product builders as well as to brand teams.

For CogNerd, the value of being present is the chance to test whether its explanation of the problem resonates beyond the people already familiar with SEO or generative engine optimization. The company has built tools for tracking prompt performance, mentions, citations and competitor gaps. Talking about those capabilities in plain language helps expose where the product is clear and where it still needs work. That learning can shape how CogNerd presents its findings and which customer questions it chooses to solve next.

Why the IIM Bangalore program matters

IIM Bangalore has built a broad entrepreneurship ecosystem around founders, operators and researchers. Its startup incubator, NSRCEL, describes mentorship, access to networks and stage-specific programs as ways to help young companies develop and scale. For CogNerd, the selection creates a setting in which to sharpen the business as well as the product, testing its assumptions with people outside the founding team.

A new technology category creates several business questions at once. Who needs the information most urgently? Which measurement helps them make a decision? How should a product explain uncertainty in an AI answer? And what change would make a customer return to the platform next month? An entrepreneurship program can be valuable because it gives founders a place to test those questions with people outside their own team.

A product built for the shift from search results to answers

CogNerd's core idea is that discovery now happens in more places than a conventional search results page. A person may ask an AI assistant to compare solutions, recommend a provider or explain a category before visiting any company website. The answer may cite a third-party article, mention several competitors or leave a relevant brand out entirely. Brands need a way to inspect those results systematically rather than relying on occasional manual checks.

CogNerd brings prompt intelligence, brand mentions, citations and competitor analysis into one workflow. It also connects that evidence to AI readiness, content and search performance. The company is working toward a practical sequence: find the customer questions that matter, measure how a brand appears, identify the gaps and decide which improvements deserve attention first.

That combination reflects the founders' backgrounds. Aman Mundra brings production AI and data engineering experience, while Sakshi Dhawan, PhD, brings research into human behavior and decision-making. AI visibility depends on both: systems produce the answers, but people ask the questions and act on what they hear.

The work ahead

The IIM Bangalore milestone gives CogNerd another setting in which to pressure-test its assumptions about product value and customer needs. The team's goal is to make AI search visibility understandable to marketers and business owners, while keeping the underlying measurement rigorous enough to support repeated decisions.

CogNerd will continue publishing the features and findings that come out of its work. The program is part of that longer process of learning, building and showing customers what changed.

Turning visibility data into a business decision

The commercial question for CogNerd is not whether AI search exists; customers can already see that people use assistants to ask questions. The question is how a business should respond. A report may show that a competitor is mentioned more often, but a customer needs to know whether the difference comes from stronger source coverage, clearer product information or a topic the brand has never addressed. CogNerd is developing its platform around that chain of reasoning.

A startup program can help the team test how it presents that value. Marketers may want a quick gap report, while product leaders may need evidence that a proposed change is worth the effort. Founders and agencies may need a way to explain the opportunity to their clients. CogNerd's work at this stage is to make the same underlying evidence useful to each of those decisions without overstating what a single AI answer proves.

What NVIDIA Inception offers

NVIDIA describes Inception as a free program that supports AI startups from early product development through growth. Its published member opportunities include technical training, developer tools, selected hardware and software offers, partner benefits and investor exposure for eligible companies. Membership does not itself mean that NVIDIA has invested in a startup or that every advertised benefit has been granted to it. CogNerd will describe any specific benefit it uses once that support has been confirmed.

The value of a technical ecosystem is learning as much as access. AI applications change quickly: model capabilities evolve, infrastructure choices affect cost and speed, and new tools can alter what a team is able to build. A startup needs to make those choices while keeping the customer's actual problem in view. Inception gives CogNerd a place to follow that technical landscape and evaluate relevant resources as its product develops.

CogNerd's measurement challenge

CogNerd is building for a question that has become more urgent as AI assistants influence discovery. If a buyer asks for the best provider in a category, what brands are named? Which websites are cited? How is each company described, and does the answer change across different prompts or AI engines? A marketer cannot answer those questions with a conventional rank report alone.

The CogNerd platform tracks brand mentions, prompt coverage, citations and competitors across AI search experiences. Its AI readiness and content workflows help teams investigate why their presence may be weak and what they can improve. The goal is to connect observation to action: a missing mention may point to unclear positioning, weak source coverage or content that does not answer the customer's question.

As the team builds those workflows, it has to balance breadth and clarity. More data is useful only if customers can tell what it means. CogNerd's approach is to present the evidence behind a visibility gap and make the next step understandable, whether that involves a product page, a sourced answer, structured information or a broader content opportunity.

Building within a wider AI ecosystem

Joining NVIDIA Inception adds a connection to the tools and people working across AI development. CogNerd will use the opportunity to keep improving its platform and to learn where emerging technology can make the measurement more reliable and useful.

The company will continue to share concrete product progress. Its place in Inception is a milestone in that work, alongside the more important test: helping customers make better decisions about how their brands are discovered.

The technical work behind useful visibility

Measuring AI answers is harder than counting a mention once. A business may be described differently by different engines, and two similar questions can produce different sets of recommendations. Sources may be cited in one answer and omitted in another. CogNerd has to collect and present those variations without pretending the underlying systems are perfectly stable. Its current product direction includes prompt intelligence, citation analysis, competitive visibility and repeat scans so teams can compare what changed.

That work makes a technical startup ecosystem relevant. Access to learning resources and developer tools can help a team evaluate new approaches as AI systems evolve. CogNerd's job, however, remains centered on the customer's decision: identify the most important visibility gaps and explain what evidence supports them. Membership in Inception adds another place to learn and build, while the product's success will be determined by whether it helps brands act with greater clarity.

What DPIIT recognition means

Startup India sets eligibility criteria for companies seeking DPIIT recognition, including the nature of the entity, its age and its focus on innovation or a scalable business model. Recognition confirms a company's status under that framework. It can also be a prerequisite for applying to certain startup programs, but each grant, tax benefit or other incentive has its own conditions and approval process.

For CogNerd, the certificate is a company milestone rather than a claim that a specific financial benefit has been received. It places the venture within an ecosystem intended to help innovative businesses develop, connect and grow. CogNerd will continue to assess individual opportunities on their own terms while keeping the focus on the product it is building.

The business problem behind CogNerd

Search has become harder to measure from a brand's point of view. Traditional tools can show where a page ranks and how many visitors arrive. They do not fully reveal the answer a person receives after asking an AI assistant to compare vendors or recommend a service. The customer may never see a list of ten links, yet the answer can still shape who they consider.

CogNerd helps teams inspect that newer path to discovery. It tracks the prompts people ask, whether a brand appears or is cited, how competitors are represented and where useful sources are missing. The platform also links those observations to AI readiness, content and search work, so teams can decide what to change and check the result later.

This is a practical problem for companies of many sizes. A founder wants to know if buyers asking about a category encounter the company. A marketer wants to see whether content improvements affect visibility. A business leader wants evidence before investing more time in a new channel. CogNerd is building the measurement layer to make those decisions less speculative.

The next stage

DPIIT recognition marks progress in CogNerd's development, but the company's impact will come from what customers can do with the product. The team is continuing to refine the visibility signals it measures and the guidance it gives, with the aim of making AI search a channel brands can understand and improve over time.

CogNerd will share that progress through product updates, research and examples grounded in real customer questions.

Why the recognition fits the company's work

DPIIT recognition is especially relevant to a venture addressing a new market need. CogNerd is building around the observation that search discovery is changing faster than the tools many businesses use to measure it. Its platform brings together AI answer monitoring, citations, competitive signals, content opportunities and traditional search data so a team can see a more complete picture of how people find and evaluate a brand.

The company is also trying to make that picture useful beyond specialist SEO teams. A founder should be able to see whether the company appears when buyers ask about its category. An agency should be able to show a client which topics need better answers. A marketing team should be able to check whether changes to its content or website are followed by a shift in AI visibility. The recognition marks CogNerd's position within India's startup ecosystem as it works to turn those use cases into a reliable product.