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Lastro
Creators of Lais, an all-in-one real estate management platform with integrated payments that simplifies managing rental properties
About Lastro
Founded in 2021, Lastro is a Brazilian company operating in the real estate technology sector, initially focused on property management software. The company was established by a team with diverse and relevant backgrounds: Allan Paladino, co-founder and CEO, previously a partner at coworking giant GoWork, brought his direct experience with the complexities of property management. He was joined by José Thomaz Pereira, a former senior executive from Blackstone's real estate division; Pedro Milanez, an early Nubank employee and head of mobile engineering who became Lastro's CTO; and Alain Michel, founder of the Mundo Pet retail chain. This combination of real estate, finance, and technology expertise shaped the company's initial direction.
Lastro has demonstrated significant strategic agility, pivoting from its original business model. Initially, the firm developed a platform to help landlords and property managers automate recurring tasks like rent collection, contract management, and financial reconciliation for a variety of property types, from residential to commercial warehouses. However, after identifying slow sales cycles and recognizing a greater market need, the company shifted its focus in late 2022 to artificial intelligence. This strategic change was driven by the emergence of powerful new AI models, leading to the creation of its flagship product, Lais (Lastro Artificial Intelligence System). The pivot proved successful, attracting over 700 clients and securing recognition from AWS as one of Brazil's top 10 AI startups.
The company's primary offering is now Lais, a conversational AI specifically designed for the Brazilian real estate market. This tool integrates with platforms like WhatsApp to provide instant, automated responses to prospective buyers and renters. Lais handles the initial stages of customer engagement by welcoming leads, answering questions, qualifying opportunities with precision, and suggesting suitable properties from a client's portfolio. Built using advanced AI models and trained on specialized real estate data, including tenancy laws and market data for hundreds of cities, the system provides accurate and contextualized interactions. This automation allows real estate agents to focus on high-value activities like closing deals, reportedly increasing lead conversion rates by up to 60% for some clients. Lastro's business model is centered on selling subscriptions to its Lais platform to real estate agencies and property developers. To date, the company has raised a total of $5.3 million in funding from investors including Canary, QED Investors, 1Sharpe Ventures, and AWS Startups.
Source: Dealroom company dataKnowledge graph
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Funding history
Company financing events and reported valuations.
| Deal type | Date | Amount | Valuation | Investors | Source |
|---|---|---|---|---|---|
| SERIES A✓Equity / VC | Sep 2025 | $15M | $60M | QED Investors · FJ Labs · Canary · Prosus Ventures | ↗ |
| SEED✓Equity / VC | Dec 2022 | $4M | $16M | QED Investors · Canary · 1Sharpe Ventures | ↗ |
Financials
Revenue, earnings and other financial measures where available. Years marked “E” are estimates.
Growth signals
Latest recorded traffic for Lastro is 340K monthly website visits, up 17.2% over the last three months. Lastro's team grew 21.5% over the past year.
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Investments and acquisitions
Recent portfolio relationships for companies that also act as investors or acquirers.
Investors
From Dealroom's funding and investor records, grouped by the round each investor first entered.
Seed3 investors entered at this stage
QED InvestorsCanary
- 1V1Sharpe Ventures
Series A3 investors entered at this stage
Prosus Ventures
FJ Labs- EVEndeavor Scale Up Ventures
Source: Dealroom Talent Intelligence.
Global footprint
team presence
Market sentiment
An AI-synthesised read of the highest-engagement posts about Lastro on X, ranked by likes and reposts, corporate channels excluded.
Reading the room on X — pulling top posts and synthesizing themes…
Source: X recent search ranked by engagement (likes + retweets) · Synthesis by Claude · Cached for 1 hour
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