Verification checkpoints
Context-aware checklists per output type (code, documentation, or triage) so reviewers verify what actually matters.
Platform · Co-Sovereignty
Trust, made formal. Every AI output gets co-signed.
AI drafts the work; humans verify it. Lornian bakes a Co-Sign ritual into every agent output: confidence-scored, checkpoint-gated, and routed by risk, so “almost right” never ships.
66% of developers are frustrated by “almost right” AI output, and 45% find debugging AI code slower than writing it. With AI trust at just 29%, formal handover protocols are essential.
Below the gate, it doesn't ship alone
Click a checkpoint to see the gate move.
74%Confidence
80%What the trust layer enforces
Risk-based routing
Policy decides the path. Sensitive surfaces always get a human critic; routine items never get bottlenecked.
Confidence scoring
Derived from model certainty, data quality, and historical accuracy on similar tasks, not a black box.
Co-Sign history
A full ledger of who verified what, when, and why, turning AI collaboration into governable, accountable work.
How a deliverable earns its signature
01
Confidence-gated review
Every agent output ships with a Confidence Score. Below 80% it triggers a mandatory human-in-the-loop review before it can advance.
02
The Co-Sign ritual
Agents draft; nothing reaches “Done” or “Published” without a human clearing context-specific verification checkpoints for logic, edge cases, and intent.
03
Planner → Critic → Executor
High-risk output (architecture, auth, billing) always routes through a human critic. Low-risk, high-confidence routine work executes directly.
04
Auditable trail
Every co-sign, score, and checkpoint result is recorded, a behaviour trace you can review, govern, and trust.
29%
baseline trust in AI for complex tasks
Industry research, 202680%
confidence gate before human review
Co-Sign policy defaultBring verified trust to your team
Every AI output, checkpoint-gated and auditable. Join the waitlist, or book a walkthrough of the ritual.