Amsterdam-headquartered Orq.ai, a Generative AI platform catering to enterprises by interfacing with large language models (LLMs) to facilitate organizational collaboration, has recently announced the successful acquisition of an additional €1.5M in growth funding.
After a well-received pre-seed round of €800K in September 2023, the Dutch firm is rolling out two innovative products, namely Experiment and Optimize.
The infusion of capital will be channeled towards expanding the product and go-to-market teams, with a particular emphasis on the European market, commencing with Germany and the Benelux countries.
Backing from Investors
The recent funding round was spearheaded by XO Ventures (led by Bart Malenstein and Marc van Meerwijk) and xdeck ventures. Noteworthy participation was also observed from existing investors Curiosity VC and Spacetime, with Adriaan Mol (the brains behind Mollie and Bird CRM) backing the endeavor.
Bart Malenstein, Managing Partner at XO Ventures, expressed enthusiasm about collaborating with founders Sohrab and Anthony, along with the entire Orq.ai team, to advance their cutting-edge Generative AI platform.
“In a landscape where the complexity and proliferation of Generative AI models are on the rise, there exists a pressing need for a solution that facilitates AI transformations and seamlessly integrates AI models within businesses,” commented Bart Malenstein.
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Marc van Meerwijk, Managing Partner at XO Ventures, added, “Orq.ai offers precisely such a solution through a remarkably user-friendly platform that empowers non-technical team members, including domain experts and product managers.”
Unveiling Orq.ai’s Latest Offerings
Orq.ai advocates for inclusive AI transformations by providing tools and security protocols accessible to all team members. The company has introduced two novel products, Experiment and Optimize, complementing the existing Run solution, thereby offering flexibility for autonomous utilization within organizations.
Experiment streamlines the testing of myriad Generative AI use cases, prompts, and datasets across over 75 models, presenting tailored controls for quality, cost, and performance.
On the other hand, Run, an intelligent rules engine, streamlines production deployment by incorporating localization, personalization, and data privacy management. Optimize furnishes real-time analytics on AI model interactions, enabling ongoing enhancements and fine-tuning by domain experts.
Orq.ai’s end-to-end workflow fosters seamless collaboration among domain experts, product managers, and engineers.
Co-founder of Orq.ai, Sohrab Hosseini, remarked, “The evolving complexity and pace of new possibilities in Generative AI necessitate a fresh approach and new tools for organizations. Our objective is to demystify AI by making it accessible to all.”
“With our integrated Generative AI platform adhering to the highest EU security and data protection standards, Orq.ai emerges as the ideal partner for companies striving to retain their competitive edge. Our existing Enterprise clients have already leveraged Orq.ai as a catalyst for extensive AI transformations and novel work methodologies.”
Sohrab further added, “Anthony and I are thrilled about this latest funding round and anticipate unveiling additional products that aid clients in embracing AI innovation securely and responsibly.”
Orq.ai: Pioneering Generative AI Collaboration
Established in 2022 by Sohrab Hosseini and Anthony Diaz, Orq.ai (formerly Orquesta.cloud) aims to empower companies in integrating and managing their products through Generative AI.
The no-code collaboration platform empowers product teams to construct and evaluate production-ready AI applications securely. It centralizes prompt management, streamlines experimentation, gathers feedback, and provides real-time insights into performance and expenditures.
Compatible with leading Large Language Model providers, the platform ensures transparency and scalability in Large Language Model Operations (LLM Ops), leading to shortened customer release cycles and cost efficiencies in experimental and production settings.
