Every organization is weighed down by manual or repetitive tasks that could be accelerated or eliminated by AI products. Whether you’re building AI products for your unique internal operations or for external customers, or perhaps looking to implement existing products alongside your current and complex architecture, efficiency is one of the most scalable benefits in the AI space.
By creating the right environment, guardrails, and processes to test and build new AI products, you can innovate in a way that builds confidence with your stakeholders and technical teams. This will increase your speed to market, delighting both customers and internal stakeholders.
of organizations are already using generative AI, according to a recent report.
Creating or implementing AI products can transform the customer experience you currently offer. Aligning on your priorities within this space will be important, and that could look like:
Predictive analysis: Provide better recommendations or manage potential risks by putting AI products to work on your data.
Customer service: AI products like chatbots will provide 24/7 customer support, empowering your users to get to the answers they need—fast.
Personalization: Offer a personal experience based on individual preferences by combining your first-party data and AI product strategy.
In this pocket guide, we offer a practical machine learning operations (MLOps) framework that captures the concepts and tools to accelerate a machine learning (ML) adoption journey.
How We Can Help
At Credera, one of our core values is integrity. There is no “one-size-fits-all” solution with AI, so we won't force specific products on clients, and we know how to strike the balance between innovation and risk management to ensure your organization is working within the right legal and regulatory guardrails. Through experience, we’ve carefully crafted best practices and accelerators that are tailored to meet our clients’ unique AI challenges.
We’re focused on creating real partnerships that build trust quickly based on our integrity. We call this the Credera Difference, and we invite you to hear directly from our clients on how it feels to work with us.
Read how we worked with an eyewear company to develop a machine learning model that will pave the way for customer experience improvements, product optimization, and market share growth.
Learn how we partnered with a leading automotive manufacturer to enable real-time, personalized user experience at scale.
Lead Developer
Global Energy Group
Offerings
Ensure you’re set up for success with your AI product priorities, regardless of where you are on your AI maturity journey.
Create end-to-end support in areas such as model versioning, reproducibility, continuous integration, and automated deployment.
Understand your unique industry and regional data requirements to ensure any interaction with your data is compliant. Use a dedicated clean room environment to perform rigorous quality assurance processes.
Focus on designing and implementing efficient mechanisms to collect, pre-process, and transform data from various sources. Establish data pipelines, data lakes, and data integration frameworks that ensure the availability, quality, and relevance of data for AI initiatives.
Our Experts
At Credera, we believe that unique perspectives and backgrounds make us better, stronger, and faster. Meet our leaders in this space who are creating a better environment to work, grow, and deliver outstanding client experiences.
Director
London
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