Enterprise Generative AI Development
Be at the Forefront of the AI Revolution
Powerful new tools are reshaping how companies develop products, deliver services, and manage their operations.
A more profound relationship between humans and technology.
Unlock new possibilities by harnessing the potential of Enterprise Generative AI for competitive advantage.
How to Derive Business Value from Generative AI
Revolutionize the Product Development Process
Product teams will leverage Generative AI tools to design and develop human-centric solutions using deep learning and natural language to enhance customer engagement and reduce support costs.
Enable the Next Level of Customer Service
With Generative AI, enterprises can have machine learning models create personalized and dynamic content, such as chatbots, virtual assistants, and recommendation systems, to deliver tailored experiences and build strong customer relationships.
Accelerate Data Analysis
Generative AI empowers enterprises to analyze and interpret vast amounts of data quickly and accurately. By automating tasks like anomaly detection, pattern recognition, and predictive modelling with machine learning, businesses can make data-driven decisions with increased speed and precision.
IT Infrastructure and Services
Generative AI has the potential to revolutionize IT processes by automating tasks, predicting and preventing faults, enhancing cybersecurity, training data, and providing intelligent decision support. These advancements enable IT teams to operate more efficiently, mitigate risks, and drive innovation in the rapidly evolving technology landscape.
Quantifying the Impact
Quantifying the Impact
$1.05 trillion dollars
The estimated impact of Generative AI on the US GDP over the next 4 years.1
80%
of the North American workforce will be impacted by large language models (LLMs).2
Save 10-$20K per Team Member
Anticipated savings by automating mundane tasks for customer support agents by reducing turnover, training, and recruiting costs.3
$7 trillion dollars
the amount Generative AI could raise global GDP by over the next 5 years.4
Enterprise Applications Of GenAI
The Enterprise Adoption Curve
Phase 1: Early Adoption of Generic Language AI Tools
(We are here)
Productivity gains will go well beyond today’s base state as more enterprise data becomes available to augment LLMs and models are fine-tuned toward valuable outcomes for workers.
Phase 2: Custom Models with Company Data Access
Large language models will leverage retrieval augmented generation (RAG) and have full access to relevant corporate data. This will enable use cases that allow LLM’s to fetch proprietary and users can interact with them like a very knowledgable chatbot.
Phase 3: Knowledge Assistants Empowered to Take Action
Custom Models that can take action on command. This will require customized mapping and integration to enterprise systems. Eg- Using a simple voice or text interface, interacting with a Knowledge Assistant that can update and issue new insurance documents for a new vehicle.
Gen AI Tools Overview
Enterprise Generative AI Insights
2023 Fall Economic Update on Consumer-Driven Banking 🥳
Blanc Labs provides their POV on the recent Open Banking Update by the Federal Government.
2023 Fall Economic Update on Consumer-Driven Banking 🥳
Blanc Labs provides their POV on the recent Open Banking Update by the Federal Government.
2023 Fall Economic Update on Consumer-Driven Banking 🥳
Blanc Labs provides their POV on the recent Open Banking Update by the Federal Government.
What is Generative AI technology?
Unlike traditional AI systems that recognize and classify existing data, Generative AI technology creates models capable of generating new and original content (images, text, audio, video) based on patterns and examples they have learned from by mimicking human creativity with deep learning algorithms, neural networks, and probabilistic modeling.
This technology has applications in image synthesis, text generation, music composition, and video generation, among others, and has the potential to revolutionize industries through enhanced creativity, automation, and personalization.
What are some examples of enterprise Generative AI?
Some examples of enterprise generative AI include automating content generation for marketing, revolutionizing design processes, augmenting datasets with synthetic data, providing personalized customer experiences through chatbots, and assisting in anomaly detection and fraud prevention while improving natural language processing for efficient communication in enterprises.