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AI Partnerships

by Tom KaurLaunched 2024-01via Nathan Latka Podcast
See all SaaS companies using partnerships
Growthpartnerships
Pricingusage-based
The Spark

Tom Kaur is a serial entrepreneur with deep experience in fintech and software. After founding and exiting two companies (Momentum Systems and Applied Development Corp) and leading Canada's largest startup accelerator and academic IP commercialization fund, he spotted a clear market gap: mid-sized SaaS companies doing $500K-$10M annually want to AI-enable their products but lack the in-house expertise, data science talent, and resources to build AI capabilities themselves. Rather than compete directly, Tom saw an opportunity to become the enabler.

Building the First Version

AI Partnerships launched in January 2024 with a pre-seed round of $2.5M raised at a $6M valuation. The company operates from Toronto with a San Francisco office handling marketing and lead generation. The team is 20 people strong. The model is straightforward: identify established mid-market software companies with existing customer bases, provide them white-label AI services and software, take margins on all services and software delivered through them, and eventually acquire the most promising affiliates as part of a larger consolidation strategy.

Finding the First Customers

Tom and team signed 15 affiliate partners in their first month, adding new partners at a rate of 1-2 per week. These aren't paying customers yet—the company is pre-revenue. Instead, these are strategic partnerships with companies like a 10-year-old manufacturing software vendor with ~100 customers. The affiliate will begin generating leads in 90 days, at which point Tom expects revenue to flow from AI-enabled features (like quality control software) that the affiliate can bolt onto its existing offerings.

What Worked (and What Didn't)

The affiliate model addresses a real pain point: these mid-sized companies have customer relationships but no AI expertise. Rather than hire expensive data scientists or build from scratch (which could take years), they partner with AI Partnerships and immediately offer new AI-powered features to their installed base. Tom is explicit that this is a short-term revenue stream. The real play is the acquisition strategy.

Where They Are Now

AI Partnerships is executing a "land grab" strategy inspired by US Web, which in the late 1990s established 50 affiliates in year one, acquired them in year two, and scaled to $100M+ in two years and $1B+ in four years. Tom is on track to hit 50 affiliates by year-end (representing roughly 5,000 existing customers across the network), with plans to begin acquisitions later in 2024 using public shares and raised capital. The path to IPO is designed to provide the currency (cheap shares) to acquire these partners at attractive valuations.

Why It Worked
  • Tom leveraged his track record as a serial entrepreneur and accelerator leader to gain credibility and access to mid-market SaaS founders, which accelerated partner acquisition to 1-2 per week.
  • By positioning as a white-label enabler rather than a direct competitor, AI Partnerships removed the threat perception that would block partnerships, allowing rapid affiliate growth without building product-market fit with end users first.
  • The usage-based pricing model aligns incentives with partner success—AI Partnerships only makes money when partners generate revenue from AI features—reducing sales friction and enabling partners to test the offering with minimal risk.
  • Tom identified a specific market gap (mid-sized SaaS companies wanting AI capabilities without in-house talent) that was underserved by both large consulting firms and early-stage AI startups, allowing focused positioning and messaging.
How to Replicate
  • 1.Identify a market segment with existing customer relationships but clear capability gaps, then design your business model to fill that gap as an enabler rather than a competitor.
  • 2.Use direct outreach from a geographically strategic office (San Francisco for marketing/lead generation in this case) to target mid-sized companies with $500K-$10M in annual revenue that match your ideal partner profile.
  • 3.Implement a usage-based or revenue-share pricing model so partners can pilot your solution with minimal upfront commitment, reducing perceived risk and accelerating partnership agreements.
  • 4.Set a specific, measurable target for affiliate acquisition velocity (e.g., 1-2 new partners per week) and establish a clear timeline for when partners will activate (e.g., 90 days post-signature) to maintain momentum and demonstrate traction.

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