Today, Cisco announced the launch of Motific, a software-as-a-service (SaaS) offering that aims to streamline and accelerate generative AI deployment for enterprises.
Born from Outshift, the company’s incubation engine focused on emerging technologies, ideas and solutions. Motific provides a central view of the entire generative AI lifecycle, right from assessment to production. This enables IT and security teams to deliver trusted gen AI capabilities across their organizations – with control over aspects like data in use, security, responsible AI and costs.
The launch marks the introduction of Cisco’s first product that navigates the complexities of generative AI deployment. And, the timing could not have been better. Enterprises across sectors are bullish on the potential of generative AI and are bringing the technology into their internal and customer-facing applications. According to recent data from Workato, the adoption of gen AI across business processes grew 400% in 2023, with revenue operations and IT teams leading the way in implementation.
How will Cisco Motific help enterprises?
While gen AI is known to provide a range of business benefits, including improved productivity and bottom line, the technology can also lead to trust gaps due to its susceptibility to biases and hallucinations. To avoid this, companies have to hire talent to provision the best-suited model (per the targeted use case), build the assistant on top of it using clean and current data and then track performance in production to make sure it does not veer into unknown territories.
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This entire effort can be both time and resource-intensive.
Motific addresses this challenge by giving teams an all-in-one, model and vendor-agnostic product to cover the entire gen AI journey from assessment and experimentation to production. All one has to do is set up the product with a few clicks and it automatically configures assistants, abstracted APIs and RAG (Retrieval Augmented Generation) using relevant data sources and models. This, Cisco says, can cut down the time to deploy gen AI applications from months to mere days.
More importantly, the offering comes with much-needed controls that ensure the AI projects deliver accurate outputs while being secure and cost-effective at the same time.
This includes compliance controls for over-usage, overrun spending and integration with organization-specific data sources, built-in policy controls to handle sensitive data (such as prompts with personally identifiable information), potential security gaps like prompt injection and reliability risks such as toxicity and hallucinations. Teams can either use these controls as is or customize them using their internal policies to get a system that accurately detects and mitigates issues between user inputs and model responses.
Once the model is deployed in production, Motific also tracks business processes and provides prompt usage intelligence with ROI and cost analysis, including consolidated monitoring audit trail and key metrics of all user requests. This gives teams a way to establish budgets to work with as well as prevents shadow AI usage.
“Motific accelerates the time to value an enterprise organization spends on gen AI usage and deployment by mitigating the risk up-front and enabling teams to innovate faster,” Vijoy Pandey, senior vice president for Outshift, said in a statement.
Available by June 2024
While the offering looks promising, especially for companies that want to tap into the power of gen AI but do not have the resources to provision a dedicated team to manage secure deployments, it remains to be seen how it performs in the real world. Cisco notes the software will be previewed at Cisco Live EMEAR and will become generally available by June 2024. However, the company has not shared how much teams will have to shell out to use the product.
Questions sent by VentureBeat remained unanswered at the time of writing.
That said, it is important to note that Motific is not the only one in this space. Over the last year, the rise of generative AI, which is expected to add up to $4.4 trillion in global corporate profits every year, has created this new crop of tooling centered around ensuring gen AI apps are built and run with accuracy. Multiple startups operate in the category with their own approaches, including Arize, which has an open-source library to monitor LLMs, Datadog and Google-backed Context.
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