AgentStatus × Liberate, a quick map of how we fit
Independent verification for Liberate's AI agents.
We continuously test AI agents from outside your stack and check whether the answers are correct, across voice, SMS, and email, from 800+ nodes across 30 countries. We sit alongside Liberate's reporting, transcripts, recordings, and quality signals, we don't replace them.
What we understand about Liberate (public)
Insurance-native AI across sales, servicing, and claims.
Liberate positions as insurance-native AI for sales, servicing, and claims, with Voice AI plus email and SMS, aimed at end-to-end resolution and tight integration into core insurance systems.
Public messaging emphasizes always-on coverage, multilingual voice, warm transfer with context, and an operations layer that includes call transcripts and recordings, sentiment, and a proprietary "smoothness" quality measure, alongside enterprise security claims such as HIPAA, SOC 2, PCI, and GDPR.
Their integrations story is ecosystem-heavy (Guidewire, Duck Creek, Salesforce, Snapsheet, and similar), which implies deep workflow and data-plane work, not a generic "drop-in widget" deployment model.
What AgentStatus is
We continuously test your AI agents and check if the answers are correct.
We send controlled test calls, messages, and emails to your production and staging agents from a global network, then we compare each answer to a library of known-correct answers ("expected answers") for that scenario. When something drifts or breaks, we flag it with the evidence attached.
That includes multi-turn conversations and multi-agent journeys when customer paths span tools, escalations, and handoffs, and it supports governance and risk conversations when stakeholders ask what was tested, from where, and what changed.
Where we fit
Complement, not overlap.
Outside-in vs inside-out
Liberate gives carriers strong inside-the-platform visibility: transcripts, recordings, sentiment, smoothness, and operational reporting. AgentStatus answers a complementary question: what did the real customer channel actually do for a controlled validate from a specific geography, network path, and latency profile, including failures that only show up outside your own telemetry.
Voice-first reality
Insurance voice is path-dependent (carrier routing, telephony, ASR/TTS, regional behaviour). A distributed execution mesh is built to catch regressions that single-region checks miss.
Global execution footprint
800+ nodes across 30 countries is the proof we are not 'synthetic from a single cloud region.' That matters for national and regional carriers, seasonal spikes, and buyers who distrust lab-only validation.
Consent-first posture
We do not pitch covert scanning of production policyholder lines. The right model is explicit pilot fixtures: sandbox numbers, approved test accounts, agreed call/SMS/email volumes, and clear success criteria.
The split
Two truths, one story.
Liberate, Inside-out
- • Voice AI + email + SMS
- • Transcripts & recordings
- • Sentiment & "smoothness"
- • Carrier system integrations
- • HIPAA / SOC 2 / PCI / GDPR
AgentStatus, Outside-in
- • Continuous validate traffic
- • Expected-answer checks & drift detection
- • Multi-turn / multi-agent journeys
- • Real-network execution evidence
- • 800+ nodes across 30 countries
Proof of scale
Plain definitions, no inflation.
In about two months, we have executed on the order of 18 million validate runs across the network. We also maintain on the order of 6,000 agent records in our system, meaning rows/configurations we track, including evaluation and pipeline agents, not "6,000 paying customers."
If helpful, we can share stricter production-only definitions under NDA.
What we are not claiming
An independent layer that coexists.
We are not a replacement for Liberate's dashboards, QA workflows, or customer experience management features. We are an independent layer that can coexist, and, where useful, help teams correlate outside-in validate outcomes with inside-out transcripts, recordings, and quality scores.
What we'd like from this conversation
Asks.
A 2-week sandbox pilot
A test phone number, a test inbox, and a set of agreed scenarios with expected answers. Two-week evaluation window. No production traffic, no policyholder data. At the end you get a written report of what we tested, what passed, and what drifted.
Security and procurement posture
How AgentStatus should connect in a way that satisfies carrier security reviews, data handling, least privilege, audit evidence, and clear test-traffic boundaries.
Where independent proof is most useful
Whether the right starting point is Liberate-internal QA, a joint carrier design where the carrier wants third-party evidence for go-live, or both.
Closing
Liberate helps insurers automate and operate insurance-native AI across the channels that matter. AgentStatus helps those same organizations prove, continuously, that customer-facing behaviour still matches policy and expectations in the real world, globally, with evidence that holds up under scrutiny.
Metrics are stated with explicit definitions: validate runs are scheduled executions over ~two months; agent records are database rows, not revenue customers. Liberate references above reflect public marketing on liberateinc.com as of the date of this note, not an endorsement by Liberate.