AI, with an operating model
In Avera, AI is not a chat window beside your data; it works inside the system of record, and every change it suggests is a proposal a named human reviews and approves. Nothing enters your design history without a decision.
AI output lands as typed, reviewable changes (an item to create, a field to update, a link to add), accepted or dismissed one by one or as a batch.
Every accepted change records what proposed it, who approved it, and why; AI authorship is visible in the history, forever.
Drafts are built from your connected data (the requirement, its risks, its tests), not from a pasted excerpt.
AI proposals pass the same permissions, lifecycles, and gates as any human change.
What it drafts
Risk analyses and FMEA entries · test protocols · submission sections · document passages · trace-link suggestions with rationale: each from the system of record, each a proposal.
Describe your process, and AI proposes the configuration (item types, workflows, forms, dashboards) as typed changes in a change request. You preview the impact, approve, and promote; the validation evidence regenerates with it. That's why implementation takes days, and why improving a validated system later is cheap instead of scary. The change pipeline, step by step →
BYOK
Avera connects to the AI provider you choose, under your keys. Your data never trains anyone's model.
MCP
Your own AI tools connect through MCP and work the whole record, and their every write is still a proposal for human review. Integrations →
The AI accelerates. The record enforces. The human decides.