NethraCX Observe watches the contact center you already run. NethraCX Reach answers the phone for a small business. Pick the one you came for.
For teams running Genesys Cloud CX or Amazon Connect. Priced per monitored agent, with AI billed by your own provider.
Link Genesys Cloud CX or Amazon Connect with read access. Try it first on built-in demo data, with no connection needed.
Each interaction is stored as observed facts, then measured with plain arithmetic. Your AI provider adds sentiment, intent and compliance flags.
Unusual movement is detected against each metric's own baseline, grouped into one incident, and explained with the evidence behind it.
Every incident comes with a recommended action and the exact interactions that support it, in dashboards your team can open.
For small businesses that cannot always pick up. A monthly plan, with AI minutes and texts included.
Enter your services, hours, policies and FAQs in plain language, and choose your receptionist's name and voice.
Call it from the dashboard and fix anything it gets wrong before a real customer hears it.
Forward your business number, or use a new one. Reach answers, takes messages, books times and transfers urgent calls to your cell.
Read every call's transcript and summary, see who to call back first, and send follow-up texts. On Pro Max, run outbound campaigns to people who agreed to be called.
This isn't a formatting choice — it's enforced in the data model and the API contract, so an AI's opinion can never quietly become "the data."
Duration, disposition, resolution status, transcripts — exactly what your contact-center platform reported. Never overwritten by AI.
Handle time, hold %, transfer rate — plain arithmetic over raw data, computed on read. Can never drift from what it's derived from.
Sentiment, intent, resolution assessment, compliance flags — a model's read on the conversation, versioned and always attributable.
Every AI field carries its own confidence score, so you always know how much weight a given interpretation deserves.
When metrics move, NethraCX doesn't ask an LLM to guess why. It correlates stored evidence deterministically — every incident has a traceable answer to "why did the platform say this."
Statistical anomaly detection compares a recent window against each metric's own baseline, per agent, queue, or intent — with a stated observed value, baseline, and z-score.
Anomalies that moved together for the same or a related entity are grouped into one incident, and matched against any manually-logged operational change nearby in time.
A deterministic narrative and recommended action are generated from the stored evidence, with a capped sample of the exact interactions supporting the finding.
The model's job is narrow and well-bounded: turn structured, already-computed evidence into a clear explanation — not to be trusted with deciding what the evidence is.
Observe has a 14-day free trial on demo data. Reach sign-up is open for practice calls.