EyeTrustAIFor social listening & intelligence providers
Less manual triage
for your customers.Controlled risk of
missed priority mentions.
EyeTrustAI works with the AI behind your listening platform to establish how much review can be automated within agreed error limits.
∴ Statistical risk control, backed by research ↓Immediate attention
Routine mentions
Retained“The cable works well. I wish the packaging used less plastic.”
Less review for your customers. Mentions stay available in your product.
Explore the walkthrough ↗︎The science behind it
Evidence for
automated prioritization.
Statistical risk control uses reviewed examples to establish how much triage your platform can automate within agreed error limits.
Two risks matter: priority mentions missed, and priority in the routine queue. Each uses a different denominator.
The supported policy is tied to a defined model, priority rules and population, with a process for reassessment when conditions change.
Inspect risks & evidence ↗︎How much priority-post review
can be reduced?
Our crisis-triage study examines review reduction and priority errors on human-labelled social posts.
Read the study ↗︎HumAID measures priority in the routine queue. It does not establish the walkthrough’s two-risk guarantee or customer savings.
Working together
Start with one workflow in your product.
EyeTrustAI: evidence & risk control.
We assess error risk and review effort, define the supported policy’s scope and specify reassessment requirements.
Your team: product integration.
You connect and operate the capability within your listening product, including activation, monitoring and pauses.
Together: the customer’s workflow.
With the customer or service team, agree priority rules, reviewed evidence and ongoing review and audit responsibilities.
Evidence, scope and adoption effort
Existing reviewed examples may be reusable after checking label quality, model version, sampling, languages and sources. New customer populations or priority definitions may need new evidence. The amount of review and integration work depends on the workflow and error limits.
We would agree the evaluation baseline, data access and responsibilities before integration. Incident response stays with the organization responsible for acting on the mention; the provider, customer and any service team agree who supplies labels and carries out continuing reviews and audits.
The walkthrough demonstrates fictional interfaces and prepared outcomes; it does not connect your listening product or send alerts.
See what happens when conditions change ↗︎Your product
What could your product automate?
Tell us about your listening product or workflow, and the prioritization decision you want to automate.