Invisible Technologies posts 20x revenue growth as AI labs hire its workers
Why does a decade‑old task‑routing startup suddenly matter to the AI industry? Invisible Technologies began as a modest personal‑assistant service, funneling micro‑jobs to a distributed workforce overseas. Over the past year that same labor pool has become a commodity for AI research labs needing labeled data, and the company’s top line has responded dramatically.
Revenue is now climbing at a rate that eclipses its early growth, with figures suggesting a twenty‑fold increase. That surge has attracted fresh capital and a leadership reshuffle: an ex‑McKinsey executive took the helm as CEO, and venture investors have stepped in. The shift hints at a broader pattern where human‑in‑the‑loop operations underpin machine‑learning pipelines.
It also raises questions about scalability, worker conditions, and the sustainability of a model that trades on outsourced labor. Below, the company’s own words lay out the timeline and the forces driving this rapid expansion.
Invisible Technologies started 10 years ago as a personal assistant bot that directed tasks to workers overseas, but it started posting twentyfold revenue increases as AI labs hired those workers to produce data. This year, it brought on an ex-McKinsey executive as CEO, took on venture funding, and is positioning itself as an AI training company. The company Pareto followed the same trajectory, launching in 2020 by offering executive assistants based in the Philippines and now selling AI training data services. The company Micro1 began in 2022 as a staffing agency for hiring software engineers, who had been vetted by AI, but now itâs a data labeling company too.
Invisible Technologies’ trajectory illustrates how a modest automation tool can evolve into a sizable data‑supply operation. Ten years after its launch as a personal‑assistant bot, the firm now reports a twenty‑fold revenue jump, driven largely by AI labs that contract its overseas workforce to generate training data. This surge coincided with a leadership change; an ex‑McKinsey executive took the helm as CEO, and the company secured venture capital to fuel further growth.
Mercor’s story runs in parallel. Founded by Brendan Foody at 19, the startup leveraged language models to screen and interview candidates, turning a $1 million annualized run‑rate into modest profit within months of its 2023 debut. Early 2024 brought interest from Scale AI, suggesting that larger AI players are scouting such automated staffing platforms.
Whether these models can sustain profitability beyond the current demand for data remains uncertain, and the long‑term impact of relying on overseas labor pipelines has yet to be fully assessed. The facts point to rapid expansion, but the durability of that growth is still open to question.
Further Reading
- Invisible Technologies Secures $100M in Growth Funding Led by TPG Spinoff - EE News Europe
- Invisible Technologies Just Raised $100M - Here's Why VCs Are Betting Big - TechNews180
- Invisible Technologies: $100 Million Raised For AI Infrastructure For The Enterprise - Pulse 2.0
- Invisible Technologies Raises $100 Million to Power the Next Generation of Enterprise AI - Invisible Technologies
More in Business & Startups
Bolmo architecture enables efficient byte‑level LM training, easing AI
Enterprises that run language models today wrestle with a hidden cost: the tokenizers that split...
Motif finds teacher model choice impacts enterprise LLM coding performance
Motif, a Korean AI startup, has just released a paper that pulls back the curtain on a practice...
Sood says India shifts from superficial AI trials as his mother uses ChatGPT
India’s AI scene has long been defined by pilot projects that never left the lab, a pattern that...
Enterprise AI pilots lag; workflow redesign needed for gains, McKinsey says
Most companies that have rushed to test AI‑driven coding assistants are seeing results that fall...
OpenAI builds Sora Android app in 28 days with Codex assistance
In just under a month, OpenAI turned a fresh concept into a functional Android app for Sora, a move...
Common Questions Answered
What caused Invisible Technologies to achieve a twenty‑fold revenue increase?
The surge was driven primarily by AI research labs hiring the company's overseas workforce to generate labeled training data. This new demand transformed the firm from a personal‑assistant service into a major data‑supply operation.
How did the leadership change at Invisible Technologies impact its growth trajectory?
In the past year, an ex‑McKinsey executive was appointed CEO, bringing strategic experience that helped secure venture funding and reposition the company as an AI training provider. This leadership shift coincided with the rapid revenue growth linked to AI lab contracts.
What role does the overseas workforce play in Invisible Technologies' business model for AI labs?
The distributed workforce, primarily based overseas, performs micro‑tasks such as data labeling and annotation, which are essential for training large AI models. Their scalability and cost efficiency have made them a commodity for AI labs seeking high‑quality training data.
What recent financial developments have supported Invisible Technologies' expansion?
The company recently secured venture capital funding, which is being used to scale its operations and invest in infrastructure for AI data production. This infusion of capital complements the revenue boost from AI lab contracts and underpins future growth plans.