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Eden AI launches platform to unify ML APIs

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Large cloud vendors like Amazon, Google, Microsoft, and IBM offer APIs enterprises can use to take advantage of powerful AI models. But comparing these models — both in terms of performance and cost — can be challenging without thorough planning. Moreover, the siloed nature of the APIs makes it difficult to unify services from different vendors into a single app or workflow without custom engineering work, which can be costly.

These challenges inspired Samy Melaine and Taha Zemmouri to found Eden AI (previously AI-Compare) in 2020. The platform draws on AI APIs from a range of sources to allow companies to mix and match models to suit their use case. Eden AI recently launched what it calls an AI management platform, which the company claims simplifies the use — and integration — of various models for end users.

Eden AI

Above: Eden AI’s management dashboard.

Image Credit: Eden AI

Prior to starting Eden AI, Melaine and Zemmouri worked as consultants on data science and AI projects at startup DataGenius, where they collaborated with corporations to leverage AI models from various providers. While there, they realizated data processing projects often involve several different APIs and obtaining the best performance — and cost savings — might require combining models from different providers, like Google Cloud’s optical character recognition combined with IBM’s translation and Amazon Web Services’ keyword extraction.

Unifying AI models

Eden AI’s new offering, which can deployed in the public cloud or on-premises, connects to AI models for computer vision, natural language processing, speech recognition, and machine learning to allow users to access, test, and compare the costs of vendor-specific models. From a dashboard, companies can create AI projects, generate keys, complete payment, upload datasets, and manage and delete AI projects from different providers.

For example, using Eden AI, a company could feed a document in Chinese into Google Cloud Platform’s optical character recognition service to extract its contents. Then it could have an IBM Watson model translate the extracted Chinese characters into English words and queue up an Amazon Web Services API to analyze for keywords.

Eden AI

Eden AI makes money by charging providers a commission on the revenues generated by its platform.

“We are driven by the desire to democratize the use of AI by offering our users simplified access to these technologies. In particular, we want to highlight innovative providers offering high-performance engines,” Eden AI writes on its website. “We believe that the use of AI engines will continue to develop in companies and that it becomes a commodity that must be easily integrated. We are therefore working … to facilitate the test[ing] and use of different AI engines.”

In the future, Eden AI aims to integrate open source models and build an algorithm that can automatically suggest the best AI model — trained in part on metadata from Eden AI’s customers. The company also plans to enable users to deploy their own algorithms on the platform, which they’ll be able to benchmark against third-party models to gauge their relative performance.

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Dixa nabs $105M to unify customer service channels

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Dixa, a startup developing conversational customer engagement software, today announced that it raised $105 million in a series C funding round led by General Atlantic, with participation from Notion Capital and Project A. CEO Mads Fosselius says that the proceeds will be put toward product development, new acquisitions following Dixa’s purchase of Melbourne-based Elevio in January, and quadrupling Dixa’s engineering team by the end of 2022.

The customer service industry remains fragmented and built around specific channels of engagement. Call center providers use the phone as a dominant channel, for example, while ticketing system providers focus on transactional experiences. The stakes are high — 90% of Americans use customer service as a factor in deciding whether or not to do business with a company, according to Microsoft.

Founded in Denmark in 2015 and launched to market in 2018, Dixa aims to help brands increase revenue through improved customer experiences. The platform allows brands to unify channels in a single system, equipping agents with tools like cross-channel prioritization, routing capabilities, and integrations. Dixa offers a phone system that runs in any web browser. And it provides email workflows as well as support for chat apps including Facebook Messenger and WhatsApp.

Dixa

“Dixa was founded with the mission to transform customer service and evolving an industry focused on efficiency and problem-solving to be a value driver for every business,” Fosselius told VentureBeat via email. “One of the foundations of Dixa’s vision and platform is the agent experience and the understanding that it’s tightly connected to customer experience. Today, customer service agents are disempowered by tools and standards that don’t allow them to provide a great customer experience. Agent experience is built into the core of Dixa — empowered with these capabilities, agents can become drivers of business outcomes.”

Automating customer service

While Dixa emphasizes the human element of customer service, it applies AI to some self-service experiences in addition to back-office tasks. According to Fosselius, Dixa’s AI bolsters the contextual relevance of knowledge-based documents, recommending articles to agents depending on the scenario. The AI improves with customer feedback and interactions data, recasting interactions into ostensibly better customer experiences.

For example, Dixa’s AI can match customers with agents based on variables including knowledge, customer relationship management data, and interaction history.

“Today, consumers are spoiled with choice and expect a personalized and positive experience with every engagement, which today’s standard can’t provide,” Fosselius said. “This requires a paradigm shift and retiring outdated concepts like omnichannel that keeps businesses lagging behind. Dixa is focused on the customer journey that transcends beyond a specific channel or modality.”

Dixa

Dixa, which has 200 employees spread across offices in Copenhagen, London, New York, Berlin, Kyiv, Tel Aviv, and Melbourne, competes with Kustomer, Zendesk, and Gladly in the over $7.54 billion customer experience management market. But the company has established a sizeable foothold over the past three years, with more than 700 customers including Epic Games, Wistia, and Rapha.

“The need for brands to differentiate through a great customer experience as well as the introduction and uptake of digital channels only grew during the pandemic. We’ve seen great brands growing together with us during these challenging times,” Fosselius said.

The latest round of financing brings Dixa’s total raised to $155 million to date. The company previously closed a $36 million series B in February 2020, which was also led by Notion.

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Osmos emerges from stealth to unify enterprise data

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Osmos, a company designing a platform to help enterprises adopt machine learning technologies, today emerged from stealth with $13 million in funding led by Lightspeed Venture Partners, with participation from CRV, Pear, and SV Angel. Cofounder and CEO Kirat Pandya says that the funds will be used to invest in Osmos’ product and grow its team, supporting R&D to advance the company’s services for data synthesis.

Companies have a growing number of data relationships, where they need to share data with customers, suppliers, partners, and others. The volume and variety of data are increasing, moreover, while the number of data sources and destinations ticks correspondingly upward. In 2016, IDG found that 7% of organizations are managing more than a petabyte of information across their data stores. And in a recent Forbes survey, 95% of companies cited the need to manage unstructured data as a problem for their business.

Osmos’ goal is to ease the analytics burden by eliminating data silos, allowing apps to talk directly to each. The company’s no-code platform provides users a way to bring in data from their systems or build pipelines to data, leveraging a real-time data transformation engine that automatically learns how to reconcile data.

Pandya and Naresh Venkat founded Osmos in late 2019 after a stint at Google Cloud, where they led AI and machine learning initiatives. Prior to Google, Pandya headed the Azure Cosmos DB rollout at Microsoft and worked on wireless mesh technology.

“During our time at Google, we noticed a few key trends,” Pandya told VentureBeat in an email Q&A. “Cross-company relationships are becoming more important than ever … [But] a lot of ‘automation’ companies [are] focused on connecting systems, automating workflows, and moving data within the four walls of an organization. When it [comes] to working with external data and systems … [t]here [are] no end-to-end solution to simplify data collaboration for the modern era … [M]ost solutions in the market that deal with data primarily target technical users — the non-technical frontline teams that actually deal with customers, partners, and vendors make do with Excel or nothing.”

Transforming data with AI

Unlike most AI-based systems, Osmos’ technology doesn’t require huge amounts of training data from customers, Pandya says. Companies only need to provide a couple of example rows of what the output should look like, and then Cosmos generates a debuggable data transformation program. This explainability is a key differentiator, Pandya believes, because it confers confidence that the system will do the right thing rather than make guesses based on arbitrary confidence values.

“Using this technology, Osmos is able to automatically learn complex transforms including conditionals, complex multi-column joins, and splits. It also ensures that the data that’s uploaded is not just schematically valid, but also passes any business rules [a users defines],” Pandya explained. “More importantly, we have turned [the platform] into a seamless full-feedback loop. [Users train] the system to learn transformations and clean up data. New data shows up, and if something breaks, the system notifies the relevant users. The users fix the errors with more examples and formulas, and the system relearns the transformation logic to handle such exceptions in the future.”

Osmos counts Bluecore, Mosaic, and Blissfully among its customers. One brand, an ecommerce company, is using the platform to automate the ingestion of catalog data from multiple distributors and vendors. Another client, a hospitality brand, is leveraging Osmos to bring property listings into its operational systems.

“Nowhere is this data silo problem more painful than when onboarding customers. One of the biggest challenges is populating your product with your customer’s live data as quickly as possible, so that they can start using it, have that ‘aha’ moment and see the value,” Pandya said. “Companies are moving more infrastructure to the cloud and investing in more efficient systems to make their teams more productive, and Osmos helps streamline one of the most manual and inefficient processes for engineering teams — dealing with external data on an ongoing basis. We are excited about the breadth of customers we have across multiple industries including manufacturing, ad tech, martech, analytics, IT service management, logistics, and supply chain.”

Osmos’ team currently stands at 15 employees. Pandya expects that number to double by the end of the year, with growth focused on the company’s engineering and go-to-market teams.

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Amperity raises $100M to unify customer data

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Amperity, a Seattle, Washington-based customer data platform, today announced it has raised $100 million in series D funding, valuing the company at more than $1 billion post-money. Founder and CEO Kabir Shahani said the company will use these funds, which bring its total raised to $187 million, to expand sales and marketing, grow internationally, and invest in R&D.

The pressures of the pandemic made knowing consumers a matter of survival for many businesses. Faced with the challenge of optimizing performance without third-party data, brands recognized the necessity of having an identity graph as part of an effort to sustain customer relationships. These graphs, which are at the foundation of customer data platforms, allow enterprises to make sense of trillions of data points from customers across in-store visits, web traffic, mobile usage, loyalty programs, and other touchpoints.

Amperity was founded in 2016 by Shahani and Derek Slager, who aimed to free engineers from integration duties while giving businesses access to the data they need to build loyalty. Prior to founding Amperity, Kabir and Derek worked together to launch enterprise marketing management startup Appature, where Kabir was CEO and Derek was VP of engineering. Appature was purchased in 2013 by IT medical services provider IMS Health, which has since merged with Quintiles.

“Amperity has created the first-party data graph and customer toolset for many of the world’s most loved consumer brands. There’s a vast universe of solutions that might provide an element of what we do, but no one can deliver a more complete customer [view] with an agnostic approach we provide at both ends — data in, data out,” Shahani told VentureBeat via email.

Behind the scenes

Customer data platforms are collections of software that create persistent, unified customer databases accessible to other systems. Data is pulled from multiple sources, cleaned, and combined to create a single customer profile. This structured data is then made available to other marketing systems.

The customer data platform market is anticipated to be worth $10.3 billion by 2025, according to Markets and Markets, up from $2.4 billion in 2020. Amperity’s competitors include homegrown solutions, as well as legacy on-premises systems from Acxiom and Epsilon Independent and cloud-based services like ActionIQ and Redpoint Marketing.

But Shahani claims Amperity is the only customer data platform with an “AI-driven customer 360.” Each of its products is built on what the company calls the DataGrid, a fully connected customer infrastructure that processes terabytes of data each day. DataGrid streams billions of rows of data at under 100 milliseconds per API call, enabling Amperity’s AI models to provide deterministic and probabilistic individual and household identity throughout customer segments.

Amperity works with customers across retail, travel, hospitality, and financial services, including Patagonia, Alaska Airlines, Starbucks, The Home Depot, Lucky Brand, and Crocs. Recently, Amperity teamed up with a lifestyle retail client to better understand the company’s customers. In 18 weeks, Amperity says it built a dashboard with transaction, marketing, store, product, and privacy data, correcting lifecycle status for 25% of the client’s customers with interaction and revenue attribution. This led to $7.7 million in campaign revenue from predictive segmentation and churn prevention campaigns.

Amperity

Above: Amperity’s customer profile dashboard.

Image Credit: Amperity

Over the past year, Amperity’s recurring revenue grew nearly 200%, Shahani says, thanks in part to business from new customers Williams-Sonoma, Tapestry, Under Armour, Smithsonian, and Airstream.

“The market opportunity for consumer data platforms continues to grow at a staggering rate, with 34% compound annual growth rate over the next five years … With an expected $10 billion total available market in 2025, we believe this category to be the next big emerging technology sector — on par with enterprise resource management [and] customer relationship management — signaling the importance of customer data platforms in the broader enterprise software ecosystem,” Shahani added. “Salesforce, Adobe, and Oracle … have been slowly rolling out their version of a customer data platform, but so far, there’s no proof they have a tangible product.”

He added that Amperity is not phased by the competition. “They operate within a closed ecosystem, so while we technically compete, we also believe that we’re complementary because we can fit into the larger marketing technology stack.”

Amperity’s latest funding round was led by HighSage Ventures, with participation from existing investors Tiger Global Management, Declaration Partners, Madrona Venture Group, and MaderaTechnology Partners. The company has 225 employees, and it expects to grow its workforce to over 300 by the end of the year.

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