Q: Who are Recordly's clients?
A: Recordly's clients vary from disruptors at the beginning of their journeys to global conglomerates with billion-euro annual revenues.
Q: How quickly can Recordly deliver AI solutions?
A: Through our eight‑week Recordly AI Program, we deliver working AI solutions that also improve data foundations. Doing this, we create a cycle of continuous improvement.
Q: What industries does Recordly work with?
A: Recordly partners with organizations across all industries. We've worked on projects and programs for example within the public sector, energy, manufacturing, forestry, retail, finance, and media, helping clients build secure, scalable, and AI-ready data foundations.
Q: What makes Recordly different from other data and AI consultancies?
A: We don't stop at PoCs. Recordly specializes in production-grade solutions that deliver long-term impact on its clients. We deliver real-world value by combining technical excellence with strategic advisory, strong data governance, and rapid delivery in our work.
Q: Does Recordly offer data and AI strategy, or just implementation?
A: Yes, we do offer strategy creation services. We help organizations across the AI maturity curve, from defining strategy and use cases to hands-on implementation, MLOps setup, and post-deployment optimization.
Q: What is GenAI and how does Recordly work with it?
A: GenAI (Generative AI) refers to systems that generate content like text, code, or images. Recordly integrates GenAI into enterprise workflows to automate decisions, augment knowledge work, and unlock new service capabilities and revenue streams.
Q: Can Recordly work with our existing data platform?
A: Most definitely. We integrate with cloud-native stacks (like Azure, GCP and AWS), existing warehouses, or custom pipelines, adapting to your architecture while improving quality and performance.
Q: What are the differences between a data engineer, data architect, data scientist, and a machine learning engineer?
- A data engineer builds and maintains the infrastructure needed to process data, such as data warehouses and data pipelines. They ensure that data is of high quality and available for analytics
- A data architect designs an organization's data structures and flows. They ensure that the infrastructure is scalable, secure, and efficient, as well as work at a strategic level
- A data scientist analyzes data and develops predictive models/algorithms using machine learning and statistics to uncover valuable insights for business
- Finally, an ML (machine learning) engineer develops and deploys machine learning models into production, ensuring they work effectively and integrate with systems.
Q: Where is Recordly based?
A: Recordly is headquartered in Helsinki, Finland, with a team of data engineers, scientists, architects, and advisors working across the country, serving clients both in the Nordics and globally. In Finland, Recordly also has offices in Tampere and Jyväskylä.
