Clause Risk Detection
Catches the non-standard clause a skim-read would miss.
Playbook checklists are good at catching what someone thought to write a rule for. They're structurally weak at catching what's new — a clause a counterparty's lawyer has never used with you before, worded just differently enough to slip past a keyword scan, buried on page 14 of an otherwise unremarkable vendor agreement.
Queviny's risk model works differently: it builds a baseline of what 'normal' looks like across your actual contract history — typical liability caps by deal size, typical indemnification scope by vendor category, typical assignment and termination language — and flags clauses that deviate meaningfully from that baseline, whether or not a specific rule exists for that exact deviation.
Every flag states the specific deviation in plain language: this indemnification clause omits the third-party IP infringement carve-out present in 94% of your executed vendor agreements. That's the difference between a risk score a reviewer has to investigate from scratch and a flag they can act on in under a minute.
What's included
Historical baseline modeling
Learns typical clause language and terms from your own executed contract history, by category and counterparty type.
Deviation flagging with rationale
States exactly what's unusual about a flagged clause and how it compares to your typical position.
Liability & indemnification exposure
Flags uncapped or unusually high liability terms and missing indemnification carve-outs before signature.
Missing-clause detection
Catches what isn't there — a standard protection your playbook expects that's simply absent from the draft.
Counterparty pattern tracking
Flags when a specific counterparty's contracts trend toward less favorable terms over time.
Configurable risk thresholds
Tune sensitivity by contract category and deal size — tighter for enterprise MSAs, looser for standard NDAs.
How it works
Baselines build from your history
Queviny reads your executed contract archive to learn what typical terms look like, by category and counterparty.
New contracts are scored
Each incoming clause is compared against the relevant baseline the moment the document is uploaded.
Deviations are flagged with context
Anything unusual is surfaced with the specific deviation explained and comparable past clauses shown alongside it.
Your team clears or escalates
Clear a false positive in one click, or escalate to senior counsel with the full comparison already assembled.
Common questions
Will this flood us with flags on every minor wording difference?
Sensitivity is tunable by contract category and deal size, and the model calibrates to your team's clearing patterns over time — deviations your team consistently accepts stop generating repeat flags.
Does Queviny block a contract from being sent automatically?
No. It flags and explains; your existing approval workflow makes the call. Automatic blocking on a model score is exactly the kind of opaque automation legal teams are right to distrust.
Can flags route to specific reviewers based on risk type?
Yes — Scale plans support custom routing so liability flags reach one reviewer, IP flags reach another, without anyone checking a separate queue.
See risk detection on your own contracts.
Start a free trial and connect your contract repository, or explore the interactive playground with sample data first.
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