If you would like your announcement to be included in Amalgam Insights\u2019 weekly data and analytics roundups, please email lynne@amalgaminsights.com<\/a>.<\/p>\n\n\n\n

Funding<\/h2>\n\n\n\n

Aporia Raises $25 Million to Grow its Machine Learning Observability Platform<\/a><\/p>\n\n\n\n

On February 22, Aporia, a machine learning observability platform, announced that it had raised $25M in a Series A funding round. Tiger Global Management led the round, with participation from existing investors TLV Partners and Vertex Ventures, and new investors Samsung NEXT and Tal Ventures. The funding will go towards hiring and global expansion.<\/p>\n\n\n\n

Decodable Raises $20M Series A Funding Round For Its Realtime Data Platform<\/a><\/p>\n\n\n\n

Decodable, a realtime data engineering platform, raised a $20M A round this week. Bain Capital Ventures and Venrock led the funding round, with additional participation from individual investors including former US Chief Data Scientist DJ Patil, DataDog CEO Olivier Pomel, Cockroach Labs CEO Spencer Kimball, and Redis CRO and President Jason Forget. Decodable also debuted the Decodable Real-Time Data Platform, which supports functions like event-driven micro services, data mesh deployment, realtime data integration and ML\/AI pipelines, and data governance and regulatory compliance.<\/p>\n\n\n\n

Grata Closes $25 Million A Round For Its Data Intelligence Engine<\/a><\/p>\n\n\n\n

Grata, a data intelligence engine, announced February 22 that it had raised $25M in a Series A funding round led by Craft Ventures. Existing investors Accomplice, Bling, and Touchdown Ventures also participated, along with new investors Altai Ventures, Eigen Ventures, and Teamworthy Ventures. The funding will go towards further product development. Grata uses proprietary machine learning and natural language processing models to process unstructured data from websites into insights on private companies, made available in a search-based interface.<\/p>\n\n\n\n

GraphQL Engine Provider Hasura Announces $100M in Series C Funding<\/a><\/p>\n\n\n\n

Hasura, a GraphQL engine provider, has raised a $100M Series C funding round. Greenoaks led the round, with participation from existing investors Lightspeed Venture Partners, Nexus Venture Partners, and Vertex Ventures. Hasura will use the funding for R+D and global expansion of their go-to-market strategy.<\/p>\n\n\n\n

Streaming Data Platform Redpanda Raises $50M Series B<\/a><\/p>\n\n\n\n

Redpanda, a data streaming platform, announced February 23 that they had raised a $50M Series B Funding Round led by GV. Haystack VC also participated, as did Lightspeed Venture Partners (busy week for Lightspeed, also participating in the Hasura C round!). The funding will go towards hiring for their engineering and go-to-market teams.<\/p>\n\n\n\n

SeMI Technologies Raises $16M Series A Round For AI-Based Search Database<\/a><\/p>\n\n\n\n

SeMI Technologies, providers of open source vector search engine Weaviate, announced a $16M Series A funding round February 22. Cortical Ventures and New Enterprise Associates co-led the round. The funding will go towards hiring, community development, and product improvement including increasing potential use cases and creating and improving the ML models Weaviate is based on.<\/p>\n\n\n\n

Launches and Updates<\/h2>\n\n\n\n

cnvrg.io Announces AI Blueprints, Customizable ML Pipelines<\/a><\/p>\n\n\n\n

On February 22, Cnvrg.io, an AI\/ML platform provider, debuted cnvrg.io AI Blueprints. AI Blueprints is a curated open-source library of machine learning model APIs and customizable pipelines, allowing companies to quickly piece together models to analyze their data. Availability of cnvrg.io AI Blueprints is planned for the first half of 2022.<\/p>\n\n\n\n

Equalum Releases v3.0 of their Continuous Data Integration Platform 3.0<\/a><\/p>\n\n\n\n

Equalum released version 3.0 of their \u201ccontinuous\u201d data integration platform this week. New features include expanded support for cloud targets across AWS, Azure, and GCP; enhanced binary parsers for Oracle logs and SQL replication; improvements to replication groups to allow for extensive data migrations and cross-platform data warehousing; and no-code data integration capabilities for streaming ETL and ELT data, as well as batch ETL and change data capture.<\/p>\n\n\n\n

Mage Debuts Low Code AI Ranking Model Tool for Product Developers<\/a><\/p>\n\n\n\n

On February 24, Mage announced the general availability of its low code AI tool. Mage is targeted towards product developers needing to build AI ranking models to increase user engagement and retention.<\/p>\n\n\n\n

nRoad Launches Unstructured Data Processing Platform Convus<\/a><\/p>\n\n\n\n

nRoad, an NLP startup, introduced its Convus platform February 23. Convus provides machine learning models for financial services to extract insights from unstructured data. This allows FinTech businesses to avoid manual data extraction and entry while incorporating information in documents into business processes.<\/p>\n\n\n\n

thatDot Releases Complex Event Processing Engine Quine Streaming Graph<\/a><\/p>\n\n\n\n

thatDot, complex event processing software providers, debuted Quine Streaming Graph, an open source event processing engine based on streaming graph data. Developers can use Quine to quickly build complex event processing workflows to apply to streaming graph data using \u201crecipes.\u201d Recipes currently available include blockchain realtime tag propagation, CDN cache efficiency analysis, and Apache server log observability.<\/p>\n","protected":false},"excerpt":{"rendered":"

If you would like your announcement to be included in Amalgam Insights\u2019 weekly data and analytics roundups, please email lynne@amalgaminsights.com. Funding Aporia Raises $25 Million to Grow its Machine Learning Observability Platform On February 22, Aporia, a machine learning observability platform, announced that it had raised $25M in a Series A funding round. Tiger Global […]<\/p>\n","protected":false},"author":3,"featured_media":0,"comment_status":"closed","ping_status":"closed","sticky":false,"template":"","format":"standard","meta":{"jetpack_post_was_ever_published":false,"_jetpack_newsletter_access":"","_jetpack_newsletter_tier_id":0,"footnotes":""},"categories":[2,6],"tags":[],"class_list":["post-13592","post","type-post","status-publish","format-standard","hentry","category-data-science","category-from-bi-to-ai"],"jetpack_sharing_enabled":true,"jetpack_featured_media_url":"","_links":{"self":[{"href":"https:\/\/amalgaminsights.com\/wp-json\/wp\/v2\/posts\/13592","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/amalgaminsights.com\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/amalgaminsights.com\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/amalgaminsights.com\/wp-json\/wp\/v2\/users\/3"}],"replies":[{"embeddable":true,"href":"https:\/\/amalgaminsights.com\/wp-json\/wp\/v2\/comments?post=13592"}],"version-history":[{"count":5,"href":"https:\/\/amalgaminsights.com\/wp-json\/wp\/v2\/posts\/13592\/revisions"}],"predecessor-version":[{"id":13601,"href":"https:\/\/amalgaminsights.com\/wp-json\/wp\/v2\/posts\/13592\/revisions\/13601"}],"wp:attachment":[{"href":"https:\/\/amalgaminsights.com\/wp-json\/wp\/v2\/media?parent=13592"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/amalgaminsights.com\/wp-json\/wp\/v2\/categories?post=13592"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/amalgaminsights.com\/wp-json\/wp\/v2\/tags?post=13592"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}