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Airbyte raises $5.2M for its open-source data integration platform

Airbyte, an open-source data integration platform, today announced that it has raised a $5.2 million seed funding round led by Accel. Other investors include Y Combinator, 8VC, Segment co-founder Calvin French-Owen, former Cloudera GM Charles Zedlewski, LiveRamp and Safegraph CEO Auren Hoffman, Datavant CEO Travis May and Alain Rossmann, the president of Machinify.

The company was co-founded by Michel Tricot, the former director of engineering and head of integrations at LiverRamp and RideOS, and John Lafleur, a serial entrepreneur who focuses on developer tools and B2B services. The last startup he co-founded was Anaxi.

Image Credits: Airbyte

In its early days, the team was actually working on a slightly different project that focused on data connectivity for marketing companies. The founders were accepted into Y Combinator and built out their application, but once the COVID pandemic hit, a lot of the companies that had placed early bets on Airbyte’s original project faced budget freezes and layoffs.

“At that point, we decided to go into deeper data integration and that’s how we started the Airbyte project and product as we know it today,” Tricot explained.

Today’s Airbyte is geared toward data engineering, without the specific industry focus of its early incarnation, but it offers both a graphical UI for building connectors, as well as APIs for developers to hook into.

As Tricot noted, a lot of companies start out by building their own data connectors — and that tends to work alright at first. But the real complexity is in maintaining them. “You have zero control over how they behave,” he noted. “So either they’re going to fail, or they’re going to change something. The cost of data integration is in the maintenance.”

Even for a company that specializes in building these connectors, the complexity will quickly outpace its ability to keep up, so the team decided on building Airbyte as an open-source company. The team also argues that while there are companies like Fivetran that focus on data integration, a lot of customers end up with use cases that aren’t supported by Airbyte’s closed-source competitors and that they had to build themselves from the ground up.

“Our mission with Airbyte is really to become the standard to replicate data,” Lafleur said. “To do that, we will open source every feature that addresses the need of the individual contributor, so all the connectors.” He also noted that Airbyte will exclusively focus on its open-source tools until it raises a Series A round — likely early next year.

To monetize its service, Airbyte plans to use an open-core model, where all of the features that address the needs of a company (think enterprise features like data quality, privacy, user management, etc.) will be licensed. The team is also looking at white-labeling its containerized connectors to others.

Currently, about 600 companies use Airbyte’s connectors — up from 250 just a month ago. Its users include the likes of Safegraph, Dribbble, Mercato, GraniteRock, Agridigital and Cart.com.

The company plans to use the new funding to double its team from about 12 people to 25 by the end of the year. Right now, the company’s focus is on establishing its user base, and then it plans to start monetizing that — and raise more funding — next year.


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Machinify raises $10 million to help businesses use AI to monetize data

Data is valuable — if you know how to access it and reap the insights from it. That’s where Machinify comes in. The artificial intelligence company just raised a $10 million Series A round led by Battery Ventures with participation from GV and Matrix Partners.

“Our core notion is that today, enterprises are collecting a ton of data,” Machinify founder and CEO Prasanna Ganesan told TechCrunch. “But if you look at how many of them are successful in turning it into smarter decision-making to drive efficiency, very few companies are succeeding.”

With Machinify, enterprise customers feed the system raw data, specify what they’re trying to optimize for — whether that be revenue or some other goal — and then the machine figures out what to do from there. Based on past decisions, the machine can figure out the right thing to do, Ganesan said.

A good example of how companies use Machinify is in the healthcare space, where businesses are using the tool to increase the accuracy and speed with which they process claims. By doing so, these companies have been able to increase revenue and reduce costs.

“Machinify is laser-focused on the critical operational issues created by the deployment of what we often call Software 2.0 within enterprises,” GV general partner Adam Ghoborah said in a statement. “Software 2.0 is software that is not written by humans like traditional software but is dynamically driven by AI models and large enterprise datasets. Software 2.0 requires a completely different approach, and we believe that the Machinify platform holds the key to unlocking its value.”

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