Tin eQMS · AI-assisted quality management
Bring a conversational interface to quality work. Find the right procedure, understand its requirements, and review the source behind an answer. Tin eQMS combines AI assistance with version-aware documents and accountable human decisions.
Early-access development. The hosted preview is available to enrolled reviewers.
Ask in plain language
Ask how a procedure handles competence, find document-control requirements, or locate material for your review. Fuzzy search helps you find documents even when your search terms are approximate. A floating assistant keeps the conversation beside the documents.
Retrieval-first AI
Relevant excerpts from the verified review package are retrieved before generation. Inspect referenced documents, read rendered Markdown, and compare versions while you evaluate the answer.
Human accountability
The preview binds confirmed draft comments to your Google identity and the exact document version. Edit suggestions and draft review requests follow the same explicit confirmation pattern.
A conversation with context
Use chat to navigate, ask questions, and prepare findings. Keep the source, its changes, and your review observations close together. AI-assisted answers remain material for your review; the original evidence stays accessible.
Conversational workflows · Preview
Streamed answers and confirmed draft actions keep the conversation moving. Each proposed change has a visible scope, a version-specific preview, and a saved receipt after confirmation.
The assistant proposes an exact-text edit. Inspect the difference before choosing to save a draft suggestion.
The server checks the logged-in reviewer, source version, and confirmation. A saved suggestion preserves the proposed text, its predecessor hash, and an attributable receipt. The frozen baseline stays intact.
Choose an enrolled reviewer and confirm the draft review request. The owner and assigned reviewer can reopen the saved suggestion.
These examples describe draft collaboration in the preview. Formal QMS approval and signing have separate authorization requirements.
Client-selectable AI
The adapter architecture gives clients a progression from local retrieval to their own AI system or a configured remote provider. Workflow permissions, confirmation, and record handling remain within the eQMS application.
Start local
Offline catalog retrieval and direct SOP counts provide a starting point with no AI API calls.
Bring your AI
An installed, reviewed adapter can translate the eQMS interface to a client-supplied local, on-premises, or remote AI system. Each integration needs configuration and qualification.
Configure remote AI
The hosted pilot uses Gemini through Google Cloud. Provider settings and credentials are deployment-controlled, with a shared application allowance for budgeted requests.
One organization, connected product work
The Tinverse Quality System defines processes and responsibilities. Tin eQMS is the application being developed to operate those processes across product workspaces. Product repositories retain their own requirements, designs, code, risk records, tests, and release evidence.
The roadmap connects that evidence to broader document workflows, training, CAPA, and regulatory-package preparation. Product-wide AI queries and submission assembly require further integrations. Regulatory transmission remains a separately authorized activity.
Capability status
Tin eQMS is in development. Intended-use assurance, organizational adoption, and operational authorization remain separate requirements. Organizations retain responsibility for their quality decisions, validation, and regulatory obligations.
Discuss your document workflows, evidence sources, deployment requirements, and preferred AI provider.
