ENTERPRISE GENAI PLATFORM
The high-speed, low-code way to build GenAI apps and agents
Develop, deploy, and operate GenAI apps and agents at enterprise-scale.
ENTERPRISE GENAI PLATFORM
Develop at speed. Deploy at scale.
Operate with ease.
Building GenAI apps can be slow, complex, and expensive – not with Vertesia. Go from prototype to production without endless timelines, heavy infrastructure, or spiralling costs.
Automate
Unlock new insights and automate your most complex business processes.
Optimize
Reduce costs and increase time to value for generative AI apps and agents.
Scale
Deploy GenAI apps across your business with repeatable, scalable processes.
Grow
Gain a competitive edge, grow revenue, and increase ROI on GenAI projects.
GENERATIVE AI PLATFORM
Enterprise-ready when you are
Unified. Secure. Compliant. Vertesia was built for agile teams who want to build smarter, and deliver faster. Every enterprise needs an edge in AI – Vertesia is yours.
GenAI solutions and use cases
Just a few examples of different GenAI use cases across different industries
Go from experimenting to production in days, not months
GENERATIVE AI MODELS
One platform. Any model. Full flexibility.
Connect to a limitless library of large language models across leading inference providers – and seamlessly switch between them.
Building autonomous agents and digital co-workers quickly and safely at scale
This comprehensive technology spotlight paper from IDC explores how enterprises can quickly and safely build autonomous AI agents at scale. The paper highlights how the Vertesia platform is in a unique position to help enterprises accelerate building and deploying autonomous agents.
Why enterprises choose Vertesia
“Vertesia empowers us to take a strategic, forward-looking approach to AI at Hashgraph, enabling cross-functional collaboration, refined prompt engineering, and seamless integration into our workflows. As we continue to scale our impact, we see Vertesia as a catalyst for unlocking new levels of efficiency and innovation in how we support the Hedera community.”
Lionel Chocron
Chief Product Officer at Hashgraph
“Vertesia has developed a platform that is designed to provide a strategic response for large enterprises looking to rapidly build, evaluate, and deploy LLM-based tasks with enterprise-level standards and controls.”
Matt Mullen
Lead Analyst, AI Applications at Deep Analysis
“Vertesia is removing the friction to adopting Large Language Models, as well as reducing the cost of operation and maintenance of the exponentially growing number of applications that are leveraging LLMs”
Sébastien Lefebvre
Partner at Elaia Partners
Stay ahead of change
Solving the LLM Infrastructure Bottleneck: Enabling Scale
How an Enterprise AI Assistant App Transforms Daily Operations
For AI Agent Building - Speed and Security Matter More than ...
GenAI FAQs
What are enterprise GenAI platforms?
Enterprise GenAI platforms are software platforms that help organizations quickly and easily design, test, and deploy custom generative AI agents and applications. Uniquely, Vertesia is a unified, low-code generative AI platform that not only speeds development and testing but also provides a full runtime operating environment for generative AI agents and apps.
What are some of the most common use cases of generative AI across enterprise companies?
The use cases for generative AI are virtually unlimited and vary dramatically across different functions and industries. Some common examples include automatic first notice of loss in insurance, M&A deal room analysis in investment banking, and customer onboarding in commercial banking. In logistics and manufacturing, companies are using generative AI to process bills of lading and to optimize their supply chains. Retailers and consumer product companies are revolutionizing digital asset management, automating marketing content generation, and hyper-personalizing customer experiences. Generative AI is also being used to automate routine tasks and activities across finance, HR, engineering, marketing, sales, and other core functions.
Because the opportunity for generative AI is so ubiquitous, we believe that our customers will only realize the true potential of generative AI when they can easily and repeatedly transform all of their business processes with agentic automation.
How long does it take to develop and implement a generative AI solution?
It depends. For companies that elect to build their own infrastructures and have taken a one-off approach to building generative AI agents and apps, it can commonly take more than six months to develop, test, and implement a generative AI solution. And many of these agents and apps will get stuck in experimentation, never making it to full production.
For companies that employ an enterprise GenAI platform and a standardized, repeatable approach for deploying generative AI agents and apps, this timeframe can be dramatically accelerated. Vertesia customers commonly develop, test, and deploy new generative AI apps in a few short weeks.
How can generative AI be integrated into a business?
Let’s look at this from both a technical and business perspective.
First, from a technical perspective, generative AI agents and apps are typically services that can be called from any existing workflow, process, or enterprise application. A unique aspect of the Vertesia platform is that it is API-first, which means that any task, prompt, or project built with Vertesia is automatically assigned a unique REST API endpoint for ease of integration.
Again, potential generative AI use cases are virtually limitless. Therefore, from a business point of view, we find that it is critical for customers to identify high-value use cases – typically those involving core business processes – that are well-suited for generative AI solutions. This can be difficult for some organizations who have limited experience with generative AI solutions. This is why we offer a free, interactive workshop to help customers quickly identify ideal use cases and begin working with this powerful technology today.
What is the cost of developing a generative AI solution?
Cost is also dependent on your approach. For companies that elect to build their own infrastructure or choose to outsource generative AI solution development, the costs can run into hundreds of thousands of dollars per solution.
For companies that choose an enterprise GenAI platform, the cost is much, much less. Typically, we find that Vertesia customers can deploy new generative AI agents and apps more than 10x faster than with homegrown solutions and, not surprisingly, at less than 1/10th the cost.
How secure are GenAI platforms?
Like other enterprise software and SaaS solutions, enterprise GenAI platforms are extremely secure. For example, Vertesia is fully SOC2 Type II-certified, which means that we maintain the highest operating standards for security and availability. Vertesia also supports a number of data privacy standards – like HIPPA, GDPR, and CCPA – ensuring that private patient or customer information remains that way. Our solution runs on leading Cloud providers, like AWS, Google Cloud, and Azure – some of the most secure organizations in the world – and can also be deployed in customers’ VPCs or data centers.
Lastly, it is important to know that Vertesia is not a model provider. We have no models to train and, therefore, we have no need for your data. We also make use of state-of-the-art models from leading inference providers and, contrary to popular myth, these models cannot be trained using customer data.
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