Questions, answered.

Nivision transcribes and analyzes every customer call. It classifies each call by type, scores sentiment, detects objections, checks compliance, extracts custom fields, and surfaces it all on a live dashboard with advanced alerts and scheduled reports - so insight from every conversation turns into action.

You define a classifier for each type of call your team handles. Every classifier has its own custom fields, scoring rules and summary format, so a sales call and a service call are each analyzed on their own terms - automatically, on every call.

Yes. You can upload a knowledge base and attach it to a classifier or a specific field. Nivision uses it as a fine-tuning signal for the analysis model, so results reflect your products, policies and terminology rather than generic assumptions.

Every call is processed post-call - the transcript, summary and classifier outputs are available within minutes of the call ending, no queues and no manual review. The dashboard refreshes continuously as new calls finish, and alerts fire the moment a completed call matches a trigger condition. In-call real-time streaming is on the roadmap.

Every call. A manual QA team typically reviews a sample of two to three percent of calls; Nivision transcribes and scores all of them against the criteria you define. That difference is the point — a failure that happens rarely is almost invisible to sampling.

Yes. Alongside phone calls and video meetings, you can record an in-person conversation — a field sales meeting, an interview, a team meeting — from mobile or desktop, and it is transcribed and analyzed like any call.

Both descriptions fit, and the distinction people usually mean is scope. Call monitoring is the input side — every call captured and checked. Conversation analytics is the output side — classification, scoring, dashboards and reports across the whole team. Nivision does both halves rather than only recording or only reporting.

60+ languages. Transcription and analysis run natively in Hebrew - including accents, slang and crosstalk - and equally in English and 60+ more languages, so Nivision fits any call center whatever language your customers speak.

Call data is processed under strict access controls with clear retention rules. Compliance monitoring is built into the product, and you stay in control of how data is stored, used and removed.

Yes. The built-in AI chat lets you ask questions across every conversation - for example, why customers churned last week - and get answers grounded in your real calls, with the conversations behind them.

Aggregate reports are generated automatically on a daily, weekly and monthly cadence and delivered to the right stakeholders - no spreadsheet to chase and no manual export.

Phone calls, video meetings and in-person recordings are live today. Text channels — WhatsApp, website chat and email — are rolling out with early customers, so ask us where they stand for your setup before you plan around them.

Gong and Chorus are built for enterprise revenue teams and deal forecasting, and price per user plus a platform fee. Avoma is meeting-first with published per-seat pricing. Nivision is built for call centers: it scores 100% of calls against criteria you define and prices by call volume rather than per seat, so scoring every agent does not mean licensing every agent. Our comparison guides cover each of them, including when the other product is the better choice.

No. Nivision connects to the telephony and CRM you already run — Voipe, PayCall, Voicenter, KavKom and Mvoice on the telephony side, Origami, Fireberry, Salesforce, Zoho and Monday on the CRM side — and takes recordings from them. It is a layer on top, not a replacement.

Not today. Analysis happens after the call, with transcripts available within minutes of it ending. Real-time in-call guidance, AI avatar roleplay training and an in-call knowledge agent are on the Coach roadmap. If changing what an agent says mid-call is your priority, platforms like Cresta, Balto and Observe.AI do that today and we would rather tell you than sell around it.

No. Nivision is a configured deployment — classifiers, scoring rules and integrations are set up for your call types before it is useful — so it starts with a conversation rather than a signup form. If you want a personal note-taker for your own meetings, a self-serve tool will serve you better.

Three cases. An individual or a very small team wanting a personal meeting note-taker — a self-serve tool is cheaper and faster. A team whose main requirement is real-time coaching during the call — that is roadmap here. And a one-off transcription job, where a per-hour transcription service costs a fraction of a platform.

For scoring against defined criteria — was the disclosure read, was the script followed, how was the objection handled — yes, and on every call rather than a sample. For judgement calls, disputed scores and the coaching conversation afterwards, no. In practice QA analysts stop hunting for problem calls and start working on the ones the system surfaced.

Yes. You define the disclosures and suitability checks each call type must contain, and every call is checked against them, with the result marked as met, breached or not applicable and the evidence quoted from the transcript. This is the most common reason regulated teams — insurance, pension, finance — start with us.

Every scored value links back to the point in the transcript it came from, so a manager can check the evidence rather than trust the score. When a criterion produces the wrong result repeatedly, the classifier behind it is adjusted — that tuning is a normal part of the first few weeks and continues afterwards.

Partly, and it is worth being precise. Live today: every call scored, aggregated agent-performance reports hourly, daily and weekly, comparison between agents, and post-call coaching insights. On the roadmap: real-time guidance during the call, AI avatar roleplay training and certification scoring.

Yes. Because every call is scored by the same classifier rather than by whichever reviewer happened to hear it, the comparison is consistent — which is the part manual QA cannot give you. Aggregated performance reports roll the whole team up by hour, day and week.

Yes. You can send a Nivision bot into a Google Meet, Microsoft Teams or Zoom meeting. It joins, transcribes and analyzes the conversation exactly like a phone call.

Nivision connects to your existing telephony and CRM - including partners like Voipe and Origami - so there is no rip-and-replace. New integrations are added as customers need them.

Yes. Every customer has a profile that gathers all of their calls in one place, with an aggregate read on sentiment, open alerts and the health of the relationship.

You define trigger conditions on any call signal - a low score, a missed disclosure, a cancellation intent, a competitor mentioned. Nivision raises an in-system alert with severity and context the moment that condition is met.

Yes. There is a partner API with its own keys, and webhooks that fire on events you subscribe to — when a recording finishes ingesting, when a transcript is ready, when an analysis completes, and when an alert rule matches. Webhook deliveries are signed.

No. Our privacy policy states it explicitly: client data is not, and will never be, used to train general AI models, and one client's data is never mixed with another's. The third-party AI providers we use — OpenAI/Azure, Google Gemini and Anthropic/Claude — operate under agreements that forbid training on your data unless you approve it in writing.

On AWS, which may include servers outside Israel, subject to applicable law and international transfer arrangements. Retention is configurable per client — 30, 60, 90, 180 or 365 days — and data is deleted automatically at the end of that period unless your commercial agreement says otherwise.

Encryption in transit (TLS 1.2+) and at rest (AES-256), key management through AWS KMS, role-based access control with multi-tenancy separation, immutable audit logs, PII masking, and a private VPC with environment separation. Full security documentation is available during procurement.

Access is role-based: people see only the calls, dashboards and reports their role allows, and masked values require a separate permission to reveal — every reveal is written to the audit log. For enterprise deployments, single sign-on through Microsoft Entra or Google is available.

Initial telephony integration runs in 1-2 weeks. Custom classifiers and dashboards are calibrated in another 2-4 weeks. Most call centers reach operational value in 4-6 weeks from Discovery and full value within 1-2 months.

Plans start with Listen for full conversation analysis, then add Coach and Act as you grow. Pricing is tailored to your call volume and team size - talk to us for a quote.

Listen is fully live today. Coach's first capability - aggregated agent performance reports, with hourly, daily and weekly team analytics - is live now; real-time script guidance, AI avatar training and the knowledge-base agent are still on the roadmap. Act - voicebots and automated workflows - is on the roadmap too. Together they close the loop from insight to autonomous action.

Yes. Book a demo and we will show Nivision analyzing calls like the ones your team handles every day - a 30-minute walkthrough, no slides.

Access to the recordings — usually a connection to your telephony provider — and someone on your side who can say what a good call looks like. The second one matters more. Classifiers, scoring rules and alert conditions are configured to your criteria, so someone has to decide what those criteria are.

Nivision is built for teams of roughly ten agents and up. Below that, a manager can still meaningfully review calls by hand, and the setup effort of configuring classifiers is harder to justify.