Cham

Organizations in regulated industries operate on enormous volumes of unstructured content: underwriting files, policy documents, contracts, compliance records, clinical notes, and regulatory guidance, scattered across shared drives, legacy systems, and individual employees. Traditional enterprise search finds documents but cannot reason across them. Generic AI tools hallucinate answers from public training data with no connection to an organization's actual records. Neither is acceptable when accuracy is mandatory and every answer needs to be traceable. Cham solves this by ingesting an organization's documents and data and building a knowledge graph, a structured network of entities, relationships, and facts, that becomes the authoritative source the AI reasons over when users ask questions. The result is precise, evidence-backed answers that connect information across sources, not just surface-level keyword retrieval.

Cham is delivered as a SaaS product through a hosted web portal, with infrastructure provisioned in the client's own AWS account or QyrosCloud's managed environment. The platform is powered by AWS Bedrock for AI inference, supports multi-tenant organizational architecture via Clerk, and is designed to qualify for the Deployed on AWS designation. Core capabilities include Ask, a natural language interface for querying the organization's knowledge base; Doc QA, for deep question-answering over specific document sets such as loan files, policy packages, or clinical records; and Publish, for generating branded, client-facing knowledge outputs. Custom workflows for vertical-specific use cases, such as underwriting automation, compliance checklists, or intake processing, are available as separate statement-of-work engagements. Client data is never used to train foundation models, and the architecture supports HIPAA BAA addenda and data processing agreements for regulated deployments.

QyrosCloud is an AWS Advanced Tier Managed Services Partner specializing in compliance-embedded cloud infrastructure for regulated industries. Clients receive not just a software platform but a fully managed, continuously maintained AI capability operated by a team with deep expertise in regulated cloud environments. The commercial model consists of a one-time implementation fee covering standard knowledge graph setup and portal access, a monthly managed service retainer covering patching, model updates, prompt management, and infrastructure monitoring, and SOW-based fees for custom workflow development.