Product Reports Resources Pricing Login Book a demo
COMPANY PROFILE

Ople

Explore full profile

World class deep-learning in days, not months

San Mateo, United StatesFounded 2017AI
Valuation $25–50M Last recorded · 2018
Revenue <$1M Latest reported FY
Headcount <100 Current team size
Total funding $10–50M Disclosed equity funding
Unlock exact values This page shows ranges. Dealroom has the exact numbers for Ople and the history behind them.

About Ople

Ople.ai operated as an artificial intelligence software company with a mission to simplify and accelerate the adoption of machine learning for businesses. Founded in 2017 by Pedro Alves and headquartered in Silicon Valley, the company developed a platform that automated many complex data science processes. The firm's core offering was a software-as-a-service (SaaS) platform, accessible via Amazon Web Services (AWS), designed to empower business users, data analysts, and citizen data scientists—not just PhD-level experts—to build and deploy production-grade predictive models.

The inspiration for Ople came from founder Pedro Alves's extensive background as a data science and machine learning expert. Having led data science teams at companies like Microsoft and Banjo, and with academic work in computational biology at Yale, Alves recognized a critical bottleneck in the industry. He observed that data scientists spent significant time on repetitive tasks that could be automated, which limited their ability to focus on high-impact business problems. This led to the core concept behind Ople: using AI to build AI, a process the company termed "Behavioral Assimilation." The platform was designed to learn from every model it built, progressively getting faster and smarter, mimicking how a human data scientist gains experience over time.

The platform's business model centered on providing this automated machine learning (AutoML) solution to enterprises, aiming to make AI cheaper, easier, and more ubiquitous. It allowed companies to move from raw data to actionable predictions in days or even minutes, a process that traditionally took months. The technology was engineered to integrate with existing business intelligence tools like Tableau and Google Sheets, enabling users to embed predictive analytics directly into their workflows without needing deep technical expertise. Ople targeted a broad market, from business leaders seeking strategic advantages to data professionals aiming for greater efficiency. The company successfully raised a total of $25.1 million over several funding rounds, including a Series A and a Series B, from investors such as Triage Ventures, Hack VC, and Plug and Play Tech Center. In October 2021, Ople.ai was acquired by Aktana, a company focused on intelligent customer engagement for the life sciences industry.

Source: Dealroom company data

At a glance

Founded
2017
Headquarters
San Mateo, United States
Sector
AI

Investors

2 investors on the cap table

From Dealroom's funding and investor records, grouped by the round each investor first entered.

Series A2 investors entered at this stage

Team profiled 17 named & role-tagged
Founders Hidden — book a demo/100 quality score
Key operators 1 quality Hidden — book a demo/100
Potential founders Hidden — book a demo likely future founders
Startup mafia Hidden — book a demo alumni-founded startups
Talent movements Hidden — book a demo in · Hidden — book a demo out past 12 months

Source: Dealroom Talent Intelligence.

Global footprint

Workforce and web traffic by country
Workforce by country
3 countries with
team presence
🇺🇸 United States50%
🇲🇽 Mexico25%
🇩🇿 Algeria25%
3 countries shown

Market sentiment

Posts on X, past 7 days

An AI-synthesised read of the highest-engagement posts about Ople 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

See Ople on the full Dealroom platform

Live deal flow, founder pedigree, hiring signals, revenue trajectory, and the full cap table.