ClearML, an open-source AI solutions firm, has officially launched ClearGPT, an enterprise-grade generative AI platform designed to enable organizations to leverage large language models (LLMs) securely and effectively. The platform’s key objective is to empower businesses to deploy and utilize state-of-the-art LLMs at scale while ensuring the protection of intellectual property, compliance, and knowledge.
One of ClearGPT’s distinguishing features is its ability to customize LLMs to align with an enterprise’s specific data, seamlessly integrating within its network infrastructure. This customization guarantees comprehensive security measures and facilitates the safeguarding of sensitive information. By harnessing the power of ChatGPT-like LLMs, businesses can drive innovation, enhance productivity, and improve overall operational efficiency.
ClearGPT aims to expedite the development of both internal and external products, giving organizations a competitive edge and enabling the creation of new revenue streams.
Moses Guttmann, the co-founder and CEO of ClearML, shared insights on the platform’s capabilities with VentureBeat, stating, “Our new platform is a drop-in replacement for LLM chat interfaces, such as ChatGPT, specifically designed for enterprise companies. It allows enterprises to control and create AI models directly from their organizational data without compromising any AI-as-a-service functionalities. Companies can utilize ClearGPT to deploy their models as APIs, integrate them into internal applications, or incorporate them into their existing workflows.”
Guttmann further explained that ClearGPT securely manages the end-to-end workflow at scale. This includes the secure collection of internal business data from various sources like SharePoint, Google Drive, or Slack. Customers have the flexibility to select a model, train their data, and proceed to the quality assurance phase to assess and test the model’s performance.
The platform ensures that the trained models maintain the same access rights as the original data, thus creating a secure enterprise environment. This approach prioritizes privacy and access control, enabling businesses to harness the power of AI without compromising data security.
“ClearGPT manages the entire AI model building and deployment process within the organization’s secure network. This ensures that data remains within the organization and is not shared with third-party vendors or companies, while maintaining internal data access privileges,” explained Guttmann. “By following this process, enterprises retain full ownership of their data and any AI models generated from it, which sets ClearGPT apart from other generative AI-as-a-service solutions.”
Mitigating ChatGPT concerns for secure generative AI adoption
The company said that the inherent limitations of existing solutions, such as ChatGPT, have hindered the widespread adoption of LLMs in the enterprise. Concerns regarding security, performance, cost, data governance, and customization have prevented organizations from taking full advantage of the potential of LLMs within their secure enterprise boundaries. ClearGPT is meant to directly address these challenges and eliminate the associated risks.
Using public APIs to access generative AI models and xGPT solutions has left organizations vulnerable to data leaks and privacy breaches. ClearGPT offers a solution by providing a secure environment within the organization’s network, ensuring complete control and eliminating the possibility of data leakage.
“For an organization to comply with ISO 27001, SOC2, HIPAA, GDPR and other compliance standards, it should refrain from sharing its customers’ sensitive information and its sensitive data,” Guttmann told VentureBeat. “Unfortunately, when it comes to AI-as-a-service, there is zero control over the type of data being transferred outside the company. This means maintaining compliance is challenging. ClearGPT’s design ensures no company would leak private internal data, and enterprises can continue to provide the level of privacy their customers expect.”
Guttmann explained that enterprises could achieve dynamic AI capabilities by building AI models using internal data and maintaining a continuous flow of fresh data for the model’s training. This approach ensures that the AI models have access to the latest version of the organizational data.
The training and deployment of AI models occur within the enterprise’s secure network, and the ClearGPT platform guarantees that customers maintain complete ownership of any model developed and refined on the platform.
“We ensure that competitors will never have access to the capabilities you are developing internally,” Guttman said. “ClearGPT is fully customizable to the enterprise’s unique use cases and can be easily integrated with any business application. We designed ClearGPT as low-code to allow rapid internal adoption by CxOs, business units and knowledge workers — so no AI experience [is] needed.”
Tackling enterprise AI performance and cost challenges
Guttmann believes that existing xGPT solutions have consistently posed challenges in performance and cost. He said that GPT performance in these solutions typically remains opaque and unmodifiable. In contrast, ClearGPT stands out by delivering real-time feedback and extensive customization options, all while significantly reducing operational costs.
“We offer the unique advantage of continuously improving the performance of our foundational models internally, ensuring models’ answers based on fresh data and your feedback. [This is] unlike other solutions, where their GPT performance remains fixed and cannot be improved because they’re working off stale, inaccurate data,” added Guttmann.
Moreover, the platform supports enterprise-grade LLMs, regardless of the model types being used. This eliminates the risks and burdens associated with expensive, time-consuming maintenance and overhead. As a tangible example, organizations would be able to seamlessly deploy an enterprise chat agent capable of effectively addressing complex queries using a combination of internal and external enterprise data.
“Our solution enables you to power an enterprise chat agent that answers even the most complex questions based on internal and external enterprise data,” said Guttmann. “ClearGPT allows enterprises to combine multiple data sources into a single AI model. Doing so gives the model direct access to numerous data signals and insights. This allows any new AI request to infer and correlate hidden connections between data sources and provide new business insights that are otherwise non-trivial or impossible to correlate with current enterprise data tools or dashboards.”
What’s next for ClearML?
Guttmann firmly believes that ClearGPT will spearhead a revolutionary transformation in the enterprise AI landscape, as the platform empowers enterprise companies to effortlessly develop automated AI-driven processes that would have seemed like science fiction just a few years ago.
He said these advancements are achieved while ensuring complete control and ownership of data and models.
“Enterprises will be able to use ClearGPT to drive innovation, productivity and efficiency at vast scale and develop new internal and external products faster and at reduced costs, outmaneuver the competition and create new AI revenue streams,” he said. “With the release of new AI models to market, enterprises will be building more and more standalone automated processes where employees will only need to supervise the AI performance and direct it towards the best path of action; this is the beginning of a new industrialized AI era.”