Your Generative AI and Data Engineering Partner
Work side-by-side with our experienced team to turn your generative AI projects into reality.
Software can now understand natural language and work with unstructured data: opening up major opportunities for innovation, efficiency, and business process automation. We can help you integrate generative AI into practical, impactful applications for your business — while maintaining data privacy.
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Generative AI Services
Your business is unique. Explore how our services can help you best leverage generative AI.
Initial Consultation
Explore your needs, challenges, and the potential use cases and benefits of generative AI through in-depth discussions.
Assessment & Discovery
Evaluate your infrastructure, identify data capabilities, and discover opportunities for integrating generative AI.
Proof of Concept
Develop prototypes to showcase the feasibility of generative AI applications, and evaluate potential impacts on your organization.
Capabilities
There are endless applications of generative AI for your business, but here are a few core capabilities to explore.
Domain-Specific Chatbots
Tailor chatbots to meet the unique needs of your industry or business.
Intelligent Data Extraction From Documents
Automate the extraction of valuable information from complex documents.
Interactive Search Capabilities
Enhance user experiences with advanced search functionalities.
Customized Content Generation Tools
Develop tools for generating tailored content in education, marketing, and sales.
Prompt Engineering Automation
Streamline prompt creation for language models through automation.
Data Excellence
The performance of generative AI is only as good as the data that you provide it.
Large language models, or LLMs, perform best when you can provide as much data (“context”) as possible, be specific about what you are asking, and instruct the LLM on how to respond, providing example queries and responses.
Our engineers have a wealth of experience in building data pipelines that pull in, process, and structure the data. This is important for extracting valuable insights and feeding into large language models, or LLMs.