Generative AI started as a wave and is now transforming industries across the board. No longer hype or theory, there are already solutions that span from marketing content to advanced robotics and are generating revenue, each revolutionizing an area of work.
Where should you start? We can help with practical solutions tailored for your goals, ranging from simple and helpful to sophisticated and revolutionary.
How We Do It
1. Discovery & Assessment. Our process starts with a deep understanding of your business. We take time to learn about your challenges, target audience and desired goals. Chances are, we have a lot of experience within your industry.
2. Revolutionize with AI. Develop a custom generative AI solution for your needs that leverages existing tools, platforms and frameworks to accelerate to goal. We do this right alongside you and your team. This may involve:
- Focusing on practical solutions: We're not interested in building shiny toys that don't deliver real value. We're focused on helping you achieve your business goals.
- Laying the Foundation: A robust data strategy defines how you collect, store, manage, and analyze data to achieve specific business goals. It encompasses data governance, infrastructure, quality control, and access policies.
- Building custom AI models: We have a team of experienced AI engineers who can develop custom models for your industry and operating procedures leveraging your existing data and public sources.
- Integrating AI into your existing workflows: We can help you seamlessly integrate AI into your existing business processes; internal or customer-facing.
- Optimizing for AI: Data strategies evolve to accommodate AI requirements. This may involve identifying new data sources, implementing real-time data pipelines, and prioritizing data security to protect sensitive information.
3. Ongoing support. We don't just leave you hanging after we've implemented your solution. At your request, we will provide ongoing support to ensure that you're getting the most out of your investment.
What You Also Get
The things that set us apart are just part of the reason so many other companies have trusted us with their zero to one initiatives. Here are a few ways we cultivate trust within the AI realm:
- Human-centered approach: We believe that AI should be used to augment human intelligence, not replace it entirely. That's why we take a human-centered approach to our work, ensuring that your AI solutions are always aligned with your business needs and values.
- Deep expertise: Our team has extensive experience in AI, machine learning, and data science. We have a proven track record of success in helping businesses implement practical generative AI solutions.
- Data-Driven Insights: Your data is always your data. We will make sure your solution isn’t just a cookie-cutter or clone of an existing solution by extracting valuable insights from existing data. The solution will be unique and yours.
- People and Tech Integrations: Your teams and existing solutions will likely benefit from your newfound AI solution, practices and technology. We will help you identify the right touch points and areas for integration.
- Ethics-based collaboration: We implement strategies that ensure ethical and responsible AI development, fostering collaboration between humans and AI to leverage the strengths of both.
- AI Handoff and Excellence: You will learn new methods, tools and strategies that help your organization develop its AI muscle and establish it as a practice.
The landscape of enterprise AI tools is ever-evolving. Lolay strategically leverages many of these tools to deliver customized and impactful AI solutions for its clients:
- Data Warehouses: Tools like Snowflake and BigQuery offer robust storage and retrieval capabilities for massive datasets. These ensure clients have reliable access to the data needed to train and operate AI models.
- Data Lakes: Platforms like Databricks and Azure Data Lake Store provide flexible storage for structured and unstructured data. These are regularly used to ingest diverse data sources and prepare them for AI analysis.
- Data Preprocessing Tools: Tools like Trifacta and DataRobot streamline data cleaning, transformation, and feature engineering. Great tools to prepare high-quality data that fuels accurate and efficient AI models.
Machine Learning & Deep Learning Libraries:
- TensorFlow and PyTorch: These established libraries provide powerful frameworks for building and training complex neural networks. Engineers can utilize these to tackle a wide range of AI tasks, from image recognition to natural language processing.
- AutoML Platforms: Tools like AutoGluon and H2O.ai automate parts of the machine learning pipeline, making AI accessible to a wider audience. These are used to quickly prototype and iterate on AI models for clients with less technical expertise.
Model Management & Deployment Platforms:
- MLflow and Kubeflow: These platforms streamline the lifecycle of AI models, from development to deployment and monitoring. These tools ensure smooth integration of AI models into clients' existing workflows and infrastructure.
- MLOps Tools: Tools like Metaflow and Atlantis streamline collaboration and automation in the AI development process. These tools are utilized to build robust and reliable AI solutions that scale with time.
Generative AI Platforms:
- OpenAI API and Google AI Platform (Vertex AI): These platforms offer pre-trained generative models for tasks like text generation, image creation, and code synthesis.
- Specialized Generative AI Tools: Tools like RunwayML and Jasper focus on specific generative tasks like video editing or marketing copywriting.
It’s time to be at the forefront of the AI transformation and achieve your business goals. We know you won’t be like the others that will have to play catch up tomorrow.