Gen AI . Engine
Our Gen GenAI Engine allows Private GenAI to work with Private Data across any hardware and location, Cloud, Core, or Edge.
Full Opinionated GenAI Stack but Loosely Coupled for Enterprise scale
Opinionated selection fully Integrated for immediate use with unlimited scale in one package
Direct use of Ray and CoackRoachDb, with Integrations of Milvus, Sentence Transformers, DataHub, Hugging Face, vLLM packaged in containers with extended connectors to additional fully supported commercial products.
Coupled with the Kamiwaza Inference Mesh and Locality Aware Data Engine for the only complete Stack that works across your Private Cloud, Core and edge.
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Your data everywhere with GenAI anywhere regardless of format
Raw, Unstructured, Semi-Structured, Structured, SaaS on Prem you name it we have built a connector to enable your Private Data to work with your Private GenAI Models on the Kamiwaza Stack.
AI Anywhere and Everywhere with the Kamiwaza Inference Mesh powered by the Kamiwaza Location aware Data Engine
Inference your Data where it lives
Enterprises have Data spread across multiple Clouds, Prem, and Edge and with the Kamiwaza stack running at all locations our Inference mesh and Location aware Data Engine will process your data where it lives never moving it and only passing the Inference result between locations!
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Private Open Source GenAI Stack with Enterprise Features
System Integration and Access
Flexible Enterprise Integration: Ready for the complexity of Enterprise requirements by being opinionated and configured for seamless use but loosely coupled to make custom components easier
Comprehensive Access Management: Incorporates enterprise identity systems for advanced access control and supporting quota management, access controls, and auditing at both user and application levels.
Data Retrieval
Location-Aware Retrieval Mesh: Facilitates proximity-based data processing, significantly boosting efficiency for geographically distributed deployments, ensuring processing can happen where the data is, where capacity exists.
Identity Access Management: Enterprise connectors such as SAML 2.0 and Active Directory to ensure user access to data through LLM is authorized by source.
Inference
Scalable Inference Architecture: Utilizes Ray to provide a distributed inference framework that intelligently scales across enterprise hardware resources, so you can smoothly scale from early-stage local/small POCs into enterprise production, with a flexible ability to direct inference to owned/operated hardware or external inference endpoints like Bedrock or Anyscale if desired (or for burst scaling).
Embeddings
Enterprise-Savvy Chunking: Implements tokenizer-aware text segmentation to maximize context and minimize resource waste, a strategic advantage for enterprise retrieval accuracy and efficient resource utilization at scale.
Storage Aware Embedding: Integration with major On prem storage systems and cloud storage for file updates and new file push pipeline ensuring RAG is instantly updated.
Vector Database
Unified Enterprise Interface: Delivers a standardized interface for vector database interactions, allowing flexible consumption of vector databases.
Indexing for Enterprise Needs: Offering flexibility but also comes with defaults optimized for enterprise GenAI uses, without SMEs being fully distributed (e.g., defaulting to IP/Cosine Similarity indexes in Milvus over L2 for Q&A/similarity retrieval)
System Integration and Access
Flexible Enterprise Integration: Ready for the complexity of Enterprise requirements by being opinionated and configured for seamless use but loosely coupled to make custom components easier Comprehensive Access Management: Incorporates enterprise identity systems for advanced access control and supporting quota management, access controls, and auditing at both user and application levels.
Vector Database
Unified Enterprise Interface: Delivers a standardized interface for vector database interactions, allowing flexible consumption of vector databases. Indexing for Enterprise Needs: Offering flexibility but also comes with defaults optimized for enterprise GenAI uses, without SMEs being fully distributed (e.g., defaulting to IP/Cosine Similarity indexes in Milvus over L2 for Q&A/similarity retrieval)
Data Retrieval
Location-Aware Retrieval Mesh: Facilitates proximity-based data processing, significantly boosting efficiency for geographically distributed deployments, ensuring processing can happen where the data is, where capacity exists. Identity Access Management: Enterprise connectors such as SAML 2.0 and Active Directory to ensure user access to data through LLM is authorized by source.
Model Management
Enterprise-Grade Stability: Provides an artifactory-style local model and metadata repository, insulating enterprise operations from external model source changes.
Lineage for Enterprise CI: Maintains a detailed version history, essential for continuous integration workflows in enterprise systems
Don't Just
Get Started Get Superhuman
Inference your Data where it lives
Developers, we know genAI moves at light speed.
You’re one pip install Kamiwaza and Kamiwaza docker quickstart from a set of curated, integrated tools that make it faster for you to get started instantly.
Download Kamiwaza Community Edition for Any Device
Get model management, a prompt library, retrieval tools for RAG, along with typical things like a notebook server and local inference with preconfigured tools - and the knowledge that you can go to production without having to re-platform what you’ve built.
Join our Kamiwaza Community on Discord for support on the Community Edition or to explore use cases and talk shop with others on how Enterprises are making the Journey to 1 Trillion Inferences a day!
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Download Our Kamiwaza Community Edition Works on your Laptop Desktop or Server
Get model management, a prompt library, retrieval tools for RAG, along with typical things like a notebook server and local inference with preconfigured tools - and the knowledge that you can go to production without having to re-platform what you’ve built.
Join our Kamiwaza Community on Discord for support on the Community Edition or to explore use cases and talk shop with others on how Enterprises are making the Journey to 1 Trillion Inferences a day!
Open Source Models For Real World Use Cases
Open Source models continue to be released showing extreme gains in reasoning. Through RAG (Retrieval Augmented Generation) coupled with Fine tuning current open source models out perform general LLMs from OpenAI and Google.
Data Analysis and Insight Generation
Meta's Llama 3.1 405B can process and analyze large datasets to identify trends, perform sentiment analysis, and generate insights that can inform business strategies. This capability is invaluable for market research, competitive analysis, and customer feedback evaluation.
Private Code Co-Pilot
Essentially, Code Llama features enhanced coding capabilities, built on top of QWEN or LLama. It can generate code, and natural language about code, from both code and natural language prompts (e.g., “Write me a function that outputs the fibonacci sequence.”) It can also be used for code completion and debugging. It supports many of the most popular languages being used today, including Python, C++, Java, PHP, Typescript (Javascript), C#, and Bash.
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Near Human level Agents
Abacus Smaug 72B model recently posted near human level capabilities on many tasks allowing insights from your internal knowledgebase and data, make decisions and automate routine tasks within minutes. Seamlessly expose Agents to end users through APIs, a Chat portal from Abacus that can be integrated into your website or through messaging apps such as Teams and Slack.
Real Time Human Emotive Speech Generation
With Metavoice 1.2B you can translate text to real time Emotive Human level speech allowing you to chat with your documents, change customer interactions with your data and so much more in this new modality.
Meet Our Founders
Matt Wallace
Matt Wallace
CTO and Co-Founder
Matt Wallace, the ingenious CTO and Co-Founder of Kamiwaza AI, is the technical mastermind behind the company’s cutting-edge solutions. With a robust background in AI and machine learning, Matt has spearheaded the development of Kamiwaza’s advanced inference engines and scalable AI platforms. His expertise in optimizing AI workflows and his dedication to pushing the boundaries of technology ensure that Kamiwaza AI remains at the pinnacle of innovation. Matt’s hands-on approach and deep technical acumen make him a driving force in transforming complex AI concepts into practical, high-impact Enterprise AI applications.
Luke Norris
Luke Norris
CEO and Co-Founder
Luke Norris, the customer driven CEO and Co-Founder of Kamiwaza AI, brings three decades of leadership experience in the tech industry. With a deep passion for the Fifth Industrial revolution's impact on humanity and a relentless drive for excellence, Luke has been instrumental in guiding Kamiwaza AI to the forefront of Enterprise AI Autonomous Agents. His strategic insight and commitment to customer success have fostered a culture of continuous improvement and groundbreaking advancements. Under his leadership, Kamiwaza is creating the future of the 1 Trillion Inferences a day Enterprise, revolutionizing the way businesses harness the power of artificial intelligence.
FAQ's
Frequently Asked Questions
Utilizing models on your private compute instances anywhere allows for the Enterprise to fine tune the models on its domain specific knowledge and jargon. Couple this with secure private access to Enterprise data giving the models the knowledge of the enterprise is extremely powerful. The Kamiwaza platform makes this simple to deploy and easy to scale.
Security is a first concern as recognized the stack of open source software typically doesn't understand the needs of the Enterprise. Kamiwaza exceeds standard enterprise security practices within its stack such as centralized Secrets, east west traffic for stable antifactory like version control and many more.
Yes! Our opinionated stack is built to work with a simple Kickstart but we have connectors to integrate many third party commercial solutions such as pinecone for vector data base as an example.
We test and have validated designs with many of the Enterprise Storage/Compute OEMs along with deployable Cloud instances. We strive for having the most adaptable platform for Inference and see our ability to help the Enterprise avoid lock in and take advantage of the ecosystems innovation as key value of our stack.
Pricing is available through Cloud Marketplaces (AWS,Azure,GCP) and our OEM partners such as Supermicro and Dell. Click the Pricing and Packaging link above for more information.