260 MQLs and 20+ sales on $745 in ads: the Aisha AI case
Voice AI platform
$745 in ads → 260 MQL, 20+ sales
Can you sell an AI product while it's still an MVP? The Aisha AI case gives a clear answer: a $745 ad budget brought in 260 MQLs at ~$2.9 each, and 20+ sales followed within 2 months. The product wasn't fully finished yet.
Video
$745
Ad budget
260
MQLs
20+ (in 2 months)
Sales
Fact sheet
Situation
Aisha AI (aisha.group) is a voice artificial intelligence platform built in Tashkent. It offers businesses speech technology and AI agents that work in Uzbek, Russian and English: voice AI agents that answer customer calls 24/7; Speech-to-Text with speaker separation; Text-to-Speech in natural voices; call analytics that score conversation quality; Meeting AI and chatbots.
The platform connects to existing telephony and to CRMs such as Bitrix24 and amoCRM. Today Aisha AI is used by airports, restaurant chains, travel companies and other large businesses.
When we started working together, though, the product was an MVP (minimum viable product): the core features were ready, but it was still unknown how the market would respond and which solution would be in highest demand.
Note: Aisha AI now operates under the name VoiceLab.
Every MVP-stage startup has the same question: does anyone need this product, and will they pay for it?
Many founders make a mistake here: they spend several more months making the product "perfect" and only then go to market. The Aisha AI team chose a different path — test the market with the MVP and land the first sales.
Strategy
The partnership lasted ~3 months and ran in 2 phases.
Execution
- We tested the MVP in the market — Targeted ads to the right audience on Instagram and Telegram. 200+ leads came in during the very first month.
- We turned leads into MQLs — 260 MQLs on a total budget of $745 — people who understood the product and were looking for a solution to their problem. One MQL cost ~$2.9.
- We set up the sales process — Working the leads produced 20+ sales within 2 months.
- We fed market feedback back into the product — Based on conversations with customers, the founder saw that the market needed solutions like an AI sales assistant and an AI head of sales (AI-ROP), and adjusted the product direction accordingly. That's a pivot done right: based on market numbers, not guesswork.
Results
Client feedback
“We did Go-to-Market and started seeing results from the very first days.”
Conclusion
This approach fits AI and SaaS startups at the MVP stage, and founders who want to validate demand before spending months building the product. With a small budget ($745 in this case) you learn how the market responds, get your first sales and find out which direction the product should take.
1. You can sell with an MVP. 20+ sales came in without waiting for a finished product.
2. A test gives you direction, not just sales. Conversations with customers showed where the product should go.
3. Small budget, big answer. 260 MQLs on $745 is a clear market signal.
FAQ
How much did Aisha AI spend on ads?
$745. That budget brought in 260 MQLs, at ~$2.9 per MQL.
How many sales were made?
20+ sales over a 2-month sales period. 200+ leads came in during the first month alone.
Which channels were used?
Instagram and Telegram.
Can you sell a product at the MVP stage?
Yes. Aisha AI made 20+ sales as an MVP and used customer feedback to define the product direction. Similar cases: Loome, Memor CRM.
How long did the partnership last?
About 3 months, in 2 phases.
Is it a fit for you?
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