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Veeamly

by Emno GarianiLaunched 2017-10via Nathan Latka Podcast
See all SaaS companies using product led growth
Growthproduct led growth
Pricingfreemium
The Spark

Emno Gariani's obsession with communication and information overload led her to found Veeamly in mid-2017. As a former global director at the Founder Institute and product builder, she saw firsthand how teams were drowning in notifications across fragmented tools—Slack, Jira, Zendesk, and dozens more. The core insight: what if you could bring all of these tools into one unified workspace with intelligent prioritization on top?

Building the First Version

Veeamly launched to market in fall 2017 with a few early customer tests. Working alongside co-founder and CTO Ramzi—a veteran software engineer with decades of experience—they built a desktop app that consolidated collaboration tools and powered a prioritized feed using NLP and deep learning to detect what mattered most. The team grew to 10 people total, including Emno and Ramzi. Initial capital came from a mix of bootstrap funding, angel investors, and a seed accelerator (The Refiners), totaling about $200K. Many early team members worked for free, believing in the vision.

Finding the First Customers

After the initial launch, Veeamly went quiet for product development, then soft-launched again with a small private beta. By the time of this interview, they had roughly 10 companies in closed beta testing with approximately 100 free active users. The activation metrics were impressive: users were spending around 4 hours per day in the platform, sending replies, archiving conversations, and staying engaged. Emno had tested premium pricing early ($200/user/month) but pivoted to a freemium approach, deciding to keep the tool free until Q2 to prove the core value proposition around "stickiness"—keeping users in the workspace 4-6 hours daily.

What Worked (and What Didn't)

The team validated that users would consistently engage with the workspace if the prioritization engine worked well. They discovered that early assumptions about premium pricing were wrong; charging immediately drove users away. Instead, they decided to let free users experience the tool's core value, then upsell them on premium features like "similarity" (pulling similar conversations across tools into a single view). Customer success would drive upgrades. The goal was to save users time—instead of spending 2 hours sifting through messages, tickets, and pull requests, Veeamly would compress that into 60-90 minutes by surfacing the most important items first.

Where They Are Now

At the time of this interview, Veeamly was pre-revenue but extremely confident. They were actively raising a $500K seed round (via convertible note/SAFE) with existing angel investors leading the round. Their plan: use that capital to reach product-market fit by validating different use cases (Operations, Dev Ops, Product, Support) in B2B. They committed to launching paid pricing in April (early Q2) and expected to be post-revenue shortly after. The prioritization engine would continue to learn from user behavior, personalizing what each person saw based on their interaction patterns and role.

Why It Worked
  • Solving a self-experienced pain point allowed the founders to deeply understand the problem space and iterate authentically with early customers who shared the same frustration.
  • The freemium model with high engagement metrics (4 hours daily usage) proved core value before monetization, reducing churn risk when premium pricing was eventually introduced.
  • A technical co-founder with deep expertise in software engineering combined with a product-focused CEO who understood distribution created the capability to build both a sophisticated AI-powered product and navigate go-to-market strategy.
  • Private beta testing with early adopter companies provided controlled feedback loops to validate the prioritization engine's effectiveness before broader launch, ensuring product-market fit signals were genuine.
How to Replicate
  • 1.Identify a specific workflow inefficiency you personally experience repeatedly, then validate that 10+ other companies in your target segment face the same problem before building anything.
  • 2.Launch a freemium product designed to demonstrate core value in under 30 minutes of usage, then measure daily active usage time as your primary engagement metric before introducing any paid tier.
  • 3.Recruit a technical co-founder with 5+ years of relevant deep expertise (in this case, NLP/ML engineering) and ensure decision-making authority is split between product vision and technical execution capability.
  • 4.Run a closed private beta with 5-10 handpicked early adopter companies for 2-3 months, collecting weekly engagement data and feature usage patterns to inform your monetization strategy and use-case prioritization before public launch.

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