K-AI is an AI-powered middleware solution designed to transform enterprise document repositories into clean, structured, and AI-ready knowledge bases. It empowers large organizations to enhance data quality, improve generative AI application performance, and streamline decision-making by eliminating inconsistencies and optimizing document content.
Ideal for knowledge management teams, IT departments, and business units deploying GenAI, chatbots, or retrieval-augmented generation solutions, K-AI offers a comprehensive approach to mastering information chaos and unlocking valuable insights.
Instantly detects and flags outdated, conflicting, duplicate, and inconsistent data within document repositories
Restores and structures knowledge to make content accessible and usable for AI applications
Provides seamless API connectivity to existing databases for flexible integration
Supports integration with popular Electronic Document Management (GED) systems and home SFTP solutions
Audits and cleans databases to ensure AI-readiness and maximize knowledge exploitation
Delivers performance analytics on anomalies, duplicates, conflicts, and optimization metrics such as space saved and documents deleted
Enhances multiple AI use cases including chatbots, copilot apps, agentic AI, and natural language search
Operates up to ten times faster than manual processes, cleaning up to 80% of databases
Reduces operational costs and environmental impact by minimizing dark data and optimizing storage
K-AI’s customizable API and middleware design allow it to easily adapt to existing enterprise workflows and technology stacks, making it a trusted choice for large companies aiming to improve data quality and operational efficiency while supporting critical business decisions.
Highlights
Middleware solution that cleanses and structures document repositories for AI readiness
API connectivity enabling seamless integration with enterprise databases and GED systems
Proven to enhance generative AI performance with over 92% response accuracy and operational efficiency.
AWS Marketplace now accepts line of credit payments through the PNC Vendor Finance program. This program is available to select AWS customers in the US, excluding NV, NC, ND, TN, & VT.
Pricing is based on the duration and terms of your contract with the vendor. This entitles you to a specified quantity of use for the contract duration. If you choose not to renew or replace your contract before it ends, access to these entitlements will expire.
Additional AWS infrastructure costs may apply. Use the AWS Pricing Calculator to estimate your infrastructure costs.
This listing uses a single contract-based pricing dimension: the K-AI Instance, billed per unit. Each unit covers one K-AI instance for one use case. A K-AI instance represents one knowledge base with its own access model and document scope. You add units as you add use cases. Pricing scales directly with the number of instances you run. There are no tiers or size variations to choose between. To cover more use cases, you commit to additional units under the same contract structure.
Top-of-mind questions for buyers
What exactly counts as one K-AI instance for billing purposes?
One instance is a single knowledge base with its own access model and document scope. It carries its own RBAC policy, groups, users, and business links. Each instance also exposes one endpoint for AI agent and expert access. You bill one unit per instance you run.
If we add a second use case, does cost change automatically or must we add units?
Each use case needs its own instance, and each instance is one billed unit. Adding a use case means committing to another unit under the same contract. Cost does not scale automatically with document volume or user count. It rises step by step as you add instances for new use cases.
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