Generative AI is transformative! It’s most impactful when safe, reliable, and cost-effective.
AI is not magic. It’s up to AI engineering teams to use AI effectively to make existing apps, products & processes intelligent and create new solutions.
Gartner predicts1 an increase in AI budgets and a 10x increase in share of Generative AI in the enterprise AI workload in just a few years.
With this change, the AI workload changes – there are new capabilities, new components like large language models to build these capabilities and new ways to build & run these components. AI workload of enterprises with an LLM in production2 runs on a mix of cloud service - 71% use GenAI as a Service and 88% use a public cloud service. Among the public cloud users2, 85% manage their own compute to serve up custom models, LLM orchestration, vector searches and other ancillary components.
Pratik & Prasad started Okahu to help AI engineers make AI safe, reliable & cost-effective by making it simple & actionable to monitor this new AI workload in production.
With so many different components and options to run them, there are different ways to monitor each portion of the AI workload, including app tracing, model debugging, cloud/API monitoring and infra monitoring of app dev run-times or compute. AI engineering teams end up collecting, scrubbing & stitching logs across monitoring tools - 70% end up custom integrating two or more monitoring tools2. This creates gaps in understanding, loss of business context and integration costs.
Okahu AI Observability solves this problem. Okahu observes all the apps and components that make up your AI workload to understand how they are working now and how to make them work better without the hassle of custom integration or log analysis.
Okahu helps you discover what components your AI app uses & how they work together and observe how they run to learn what impacts reliability, performance or any other aspect of running AI you care about. With Okahu, you quickly understand if there is a problem, what to do about it - change the model, change to app code or change where it runs, and the impact of a change you make.
We’re building Okahu with Ravi, Kshitiz, Anshul & Akshay. For the last decade at various companies, we’ve been helping enterprise IT teams monitor, secure & improve their analytics & data workloads with deep tech to transparently observe & intervene to bring consistency to distributed systems.
Think about your AI workload - what observations or systems do you want to understand?
Okahu AI Observability is now in preview.
