AI Field Day 6: Kamiwaza and Superhuman Power for Enterprise AI
Jay Cuthrell
Chief Product Officer
Hi, I’m Jay Cuthrell and I’m a delegate for Tech Field Day this week for AI Field Day 6 in Silicon Valley on January 29–January 30, 2025. I’m sharing my live blogging notes here and will revisit with additional edits, so bookmark this blog post and subscribe to the NexusTek newsletter for future insights.
What is Kamiwaza?
Luke Norris, CEO and Co-Founder of Kamiwaza, shared perspectives on the name Kamiwaza and their customer demand for agents that use 100s and 1000s of interferences and data pulls to produce useful outcomes. In essence, to achieve autonomous non-human scale results requires the challenges for AI inference and data gravity need to be addressed.
Why does data gravity matter?
To address AI inference and data gravity, Kamiwaza is offering an opinionated but loosely coupled stack, an inference mesh, a local data engine, and a hardware agnostic design. When a request arrives the user service, the Kamiwaza inference mesh with locality aware distributed data engine might include a cloud RAG while simultaneously querying an on-premises inference Enterprise data source but only bringing tokens results back to the cloud that is essential as opposed to attempting replication.
For an example, genomics data need not be replicated entirely to the cloud from an on-premises data lake to participate in use of public cloud computing capabilities. Further, data sovereignty is ensured by only handling results that are local as only these results are further processed with the public cloud with local coalescence of results — i.e. data gravity for RAG is overcome.
Where does Kamiwaza fit into Enterprise?
Matt Wallace went into deeper details on other approaches like ClickHouse, Starburst, and Onehouse that are not meant to be displaced or replacing Enterprise OLAP but could be part of the inference mesh portion of the solution. For example, if a user needed to write a better query for their Enterprise OLAP that also leverages another unstructured data source and miscellaneous middleware involved queries, Kamiwaza would be the “Docker of Enterprise Generative AI”.
What problems can Kamiwaza solve?
Luke Norris went on to share their three products as a Community Edition (freemium), Standard Edition ($5k/year), and an Enterprise Edition ($25k/year) which includes outcome support for higher touch business objectives. Next, Matt Wallace clarified with any-to-many story that Kamiwaza stack solves specific problems that are business challenges such as a sales team needing to ingest multiple documents, multiple format pricing sheets, and return a useful response to a complex RFP in a fraction of the time using existing (legacy) Enterprise RFP tools.
Kamiwaza demo time!
The live demos were driven by Matt Wallace driven locally from his laptop all “hitting” the Kamiwaza stack.
Setup was local throughout the demos.
First, a question that anticipated what the delegates might find amusing.
Second, an “Agent” that has no knowledge of private company information.
Third, the same “Agent” become informed by gaining access to private company information and also be able to tell the user what is the capital of Nebraska.
Fourth, an “Agent” for creating articles is tasked with writing an article from multiple personas for the topic of “radiation hardening”. Each demo is an example of Model Context Protocol (MCP) and the final demo was a development assistant that was MCP-enabled to “create an app”, use OpenHands, lever age a remote repository, fix a defect, and then submit it back to GitHub.
About the Author
Jay Cuthrell
Chief Product Officer, NexusTek
Jay Cuthrell is a seasoned technology executive with extensive experience in driving innovation in IT, hybrid cloud, and multicloud solutions. As Chief Product Officer at NexusTek, he leads efforts in product strategy and marketing, building on a career that includes key leadership roles at IBM, Dell Technologies, and Faction, where he advanced AI/ML, platform engineering, and enterprise data services.