Free pilots and premature GTM choices are why Indian deep‑tech struggles to scale through channels

Kae Capital’s Abhishek Srivastava on why partners hesitate, where founders lose credibility, and when channel models actually work.

For most deep-tech startups in India, the breaking point doesn’t come from the product, it begins much earlier, in how pilots are structured.

“Over the last couple of years, many deep tech startups have become very focused on signing POCs with large customers in India. That’s understandable, they need proof points and demonstration of business outcomes. But two things often get missed in this journey,” Kae Capital’s managing partner, Abhishek Srivastava, told CRN India in an interaction.

Startups enter pilots with heavily discounted, or even free, commercial structures to secure marquee customers. That initial compromise on monetisation, however, is difficult to reverse.

“Once you’ve taken that hit early on with design partners, it becomes very difficult to ramp up your pricing or revenue model later,” said Srivastava.

At the same time, these pilots are frequently driven by internal champions rather than budget owners.

While technical teams may validate the product, the absence of business buy-in means pilots remain confined to experimental environments, never translating into organisation-wide adoption.

Srivastava said, “One thing that’s hardest to fix later, it’s pilots. Pilots, especially in deep tech and AI, can become a trap. You need to be very careful about which pilots you sign, define a clear scope, and establish upfront how that pilot converts into a full-scale deployment and what the expansion path looks like. At the end of the day, it has to translate into a real enterprise win.”

Weak ROI and market misalignment deter partners early

Deep‑tech startups in India struggle with channel adoption, not because the technology isn’t strong, but because early go‑to‑market choices make it difficult for partners to back them.

Srivastava pointed out that several deep‑tech founders build for India by default, largely because it is easier to secure initial customers. However, early accessibility does not always translate into market readiness.

“Many deep tech startups end up building for India simply because it’s accessible, you can get your first one or two customers easily. But that can lead to building the wrong product for the wrong audience,” he said.

He cited Cartesian Kinetics, an automation machinery manufacturer and a Kae Capital portfolio company, as an example.

The startup initially pursued design partners and POCs in India, but soon realised the market was not ready for large‑scale adoption. The company took what Srivastava described as a hard call, relocating to the US to pursue customers better aligned with its offering. Since then, Cartesian has progressed across business outcomes, product maturity, and sales execution.

Beyond geography, Srivastava said founders often over‑index on technical validation while under‑communicating business outcomes and ROI.

“You may find a strong technical champion on the customer side, but that person may not have budget authority,” he noted, adding that CISOs and technical buyers may validate products, while final decisions often rest with business heads.

This gap becomes critical once partners enter the picture.

From a channel perspective, Srivastava said monetisation clarity is the first filter. Partners want to understand how they make money, whether margins are meaningful, and how much access they will have to the startup’s leadership, engineering, and support teams.

Equally important is proof that the startup has already “walked the talk”.

Partners look for evidence of at least five to seven clean deployments, referenceable customers, and clearly demonstrated outcomes.

“If the intent is to use partners to discover product‑market fit because the startup hasn’t been able to sell directly, that’s a red flag,” Srivastava said.

According to Srivastava, channel players insist on clear deal protection so that if they open doors, they are not bypassed later. They expect transparency on which customers the startup will pursue directly and where partners are expected to lead.

Founder sales first, channel scale later

For deep‑tech startups, Srivastava said channel strategy cannot be reduced to fixed ACV (annual contract value) thresholds. What matters more is the startup’s ideal customer profile and how the product fits into the customer’s broader problem.

“In the early stages, the first few enterprise deals are almost always direct and founder‑led,” he said, adding that this is true globally and not unique to India.

Those early deals help founders build a sales playbook, understand how to demonstrate business outcomes, and learn how enterprise buyers actually make decisions.

Based on Kae Capital’s portfolio experience, startups that begin with SMB customers and then move upmarket typically need to establish this direct sales motion before bringing partners into the picture.

Once two or three enterprise customers are closed and the sales motion starts to formalise, partnerships can then be introduced to scale that momentum.

The decision to go direct or partner‑led also depends on the deal context, not just deal size.

Srivastava noted that products sold as part of large digital transformation programmes, where the startup’s offering is one component within a broader scope, are naturally channel‑led.

In such cases, system integrators and consulting firms often anchor the engagement, with startups plugging into the overall deployment.

However, where the product addresses a focused problem for a clearly defined customer segment, especially in SMB or mid‑market environments, direct sales continues to make sense even at higher deal values. “It’s difficult to define a fixed ACV threshold unless you break it down by sector and vertical,” he said.

The right time to introduce partners

Srivastava cautioned against introducing partners too early, especially before product‑market fit is achieved.

“If you’re trying to achieve product‑market fit through partnerships, that’s the worst idea; it won’t work,” he said. Partnership readiness, he added, requires a separate company‑partner fit that cannot be addressed alongside PMF.

Clear signals of readiness include the ability to close deals without founders being present in every conversation, smooth deployments, referenceable customers, and clarity on business outcomes.

Startups also need documented FAQs, ROI narratives, and positioning guidance that partners can confidently take to market.

At the same time, delaying partnerships for too long can dilute partner interest if opportunities have already been fully tapped through direct sales.

According to Srivastava, “There’s an optimal window, typically after your first set of enterprise wins, once you’ve established a playbook across sales, deployment, and outcomes, and have clarity on margins. That’s when you should start building and scaling your partnership roadmap.”

Where channels help startups graduate, not create momentum

Drawing from Kae Capital’s portfolio, Srivastava said channel partnerships tend to work best once a startup has already established sales momentum on its own.

“To be candid, I wouldn’t say that partners materially change outcomes on their own,” he said. “If you’re not able to make the sale, no partner can come in with a magic wand and make it happen.”

Instead, partnerships begin to matter when startups look to access a different category of customers or scale into environments where credibility, scale, or local presence becomes critical.

Srivastava pointed to Cartesian Kinetics as an example.

After establishing momentum through direct sales, partnerships helped the company engage with much larger enterprises in its sector. The shift was not driven by product changes, but by added credibility.

“That engine was already functioning well. Partnerships helped them step up by enabling access to larger organisations where engagements typically happen through partner‑led models,” he said.

A similar pattern emerged at IDfy, which operates in identity verification and compliance technology.

While CISOs and compliance teams understood the product well, moving into large banks and financial institutions required a higher degree of trust. Engaging through consultants and system integrators helped IDfy access that segment effectively.

In these cases, Srivastava said, the early indicators of a working channel model were straightforward. Are partners opening doors to the intended ICP? Can they engage customers independently without constantly routing conversations back to the founders? And does the partnership help the startup graduate into larger deals, new geographies, or more regulated environments?

Where the partner-led model makes sense

India’s fragmented market structure further shapes where partner‑led models make sense.

According to Srivastava, regulated sectors, including BFSI and healthcare, strongly favour partnerships, given legacy systems, compliance requirements, and institutional buying behaviour.

While fintechs are often open to direct engagement, traditional banks and insurers rely heavily on trusted SIs and consultants.

Beyond regulation, geography also plays a role.

Srivastava said Tier‑2 and Tier‑3 markets may be better served through local partners who understand regional dynamics. Building a direct presence in these markets is often uneconomical, while demand still exists.

In manufacturing clusters across regions such as Gujarat, Coimbatore, and Punjab, longstanding relationships, language familiarity, and local trust networks make partners more effective than centralised sales teams.

However, direct sales continue to matter where products are highly technical, and buyer sets are narrow and clearly defined.

In such cases, sales often require deep technical engagement that is difficult for partners to replicate early on.