Hear

What is Hear?

Hear is an AI conversation intelligence platform built for customer contact centres. It processes recorded customer calls and turns them into insights, quality scores and trends that managers can act on. The company describes its aim with the line “Millions of calls distilled” and markets the product as enterprise-grade conversation intelligence.

The platform sits on hear.ai and groups its work into conversation intelligence, automated quality assurance for call centres and predictive customer analytics. Its about page frames the mission as innovating AI for contact centres, and its blog announces a partnership with PwC Israel on AI-powered customer service insights. In October 2026 the site, case studies and careers page were all still indexed, which suggests the product is active, although we could not load the pages directly to confirm every detail.

Key Features

• Conversation intelligence: Hear analyses customer calls with AI to show why people contact your service team. Managers see recurring topics, friction points and sentiment trends across large call volumes instead of sampling a handful of recordings by hand.
• Automated quality assurance: Hear scores agent calls automatically rather than relying on manual QA sampling. One published case study covers automatic agent evaluation, which lets supervisors review every conversation against their checklist and focus coaching where scores drop.
• Predictive customer analytics: Hear offers a predictive customer analytics module that looks for patterns in conversations. The company presents it as a way to anticipate customer needs and behaviour shifts before they turn into complaints or churn.
• Compliance monitoring: Hear tracks whether agents follow required scripts and regulatory steps on calls. Its Shift case study reports 30% fewer compliance violations, a vendor-published figure that suits regulated service teams such as finance and insurance.
• Repeat-call reduction insights: Hear highlights the root causes of avoidable inbound calls. A MedicalCor case study on the Hear site reports a 20% drop in inbound calls after acting on these findings, although the result comes from the vendor.
• Speech analytics at scale: Hear processes large call archives, in line with its “Millions of calls distilled” message. This scale suits enterprise contact centres where manual listening covers only a small share of daily conversations.

Pros

• Built for contact centres: Hear focuses only on customer service and contact centre conversations. Its QA, compliance and analytics modules match the daily work of support managers, so teams avoid adapting a sales-focused call recorder.
• Published customer results: Hear backs its claims with named case studies on its own site. Shift reports 30% fewer compliance violations and 25% faster resolutions, while MedicalCor reports a 20% fall in inbound calls.
• Full call coverage: Hear evaluates every recorded conversation instead of a small manual sample. Supervisors get a fairer view of agent performance, and rare compliance problems are less likely to slip through unnoticed.
• Consulting partnership: Hear has announced a partnership with PwC Israel for AI-powered customer service insights. Larger organisations that prefer a consultancy-led rollout can bring in an established adviser alongside the software.

Cons

• No public pricing: Hear does not show a public price list that we could find. Buyers must contact the company for a quote, which makes early budget comparisons against rival tools slower.
• Few independent reviews: Hear has listings on G2, GetApp and AiDOOS, but little independent review detail surfaced in our checks. Most performance figures come from the company’s own case studies rather than third-party testing.
• Enterprise focus: Hear targets contact centres with large call volumes. Small businesses or solo operators handling a few calls a day are unlikely to justify an enterprise analytics platform and sales-led onboarding.
• Name causes confusion: Hear shares its name with hearing aid brands, hearing apps and unrelated audio tools. Searching for help, reviews or documentation can return the wrong product, so use hear.ai as your starting point.
• Unconfirmed technical details: Hear’s supported languages, telephony integrations and security certifications were not confirmed in our research. Ask for these in writing during a demo before you plan a rollout across regions or regulated teams.

Who is Using Hear?

• Contact centre managers: Leaders tracking call drivers, volumes and service quality.
• Quality assurance teams: Analysts replacing manual call sampling with automated scoring.
• Compliance officers: Teams checking script and regulatory adherence on calls.
• Customer experience leaders: Executives looking for insights to cut repeat contacts.

Pricing

Hear uses quote-based enterprise pricing, and we found no public plan list (checked October 2026 via search results and directory listings).

We could not load the official site or the G2 pricing page during this review, so treat this table as provisional. Ask Hear how call volume, seats and modules affect the quote before you commit.

What Makes Hear Unique?

Hear pairs contact centre analytics with outcome-focused case studies rather than generic call recording. Its public examples tie the platform to specific service results: fewer compliance breaches, faster resolutions and fewer repeat inbound calls. The product covers conversation intelligence, automated agent evaluation and predictive customer analytics in one place, and the PwC Israel partnership adds a consulting route for larger buyers. Rivals such as Cresta and Observe.AI lean heavily on real-time agent assistance, while Hear’s messaging centres on distilling insight from very large call archives.

Compatibilities and Integrations

• Platform: Web-based platform accessed through the hear.ai service.
• Data source: Recorded customer service calls from contact centre systems.
• Marketplaces: Listed on G2, GetApp and the AiDOOS marketplace.
• Integrations: Telephony and CRM connectors are not publicly confirmed; ask during a demo.

Hear Tutorials

Hear is rolled out with the vendor’s team rather than through instant self-serve sign-up.

1. Visit hear.ai and request a demo, sharing your call volumes and goals.
2. Agree which modules you need, such as automated QA or predictive analytics.
3. Connect your call recordings so the platform can process past and new conversations.
4. Set up your QA checklist, compliance rules and the topics you want tracked.
5. Review dashboards weekly and turn the top call drivers into coaching or process fixes.

How We Rated It

Summary

Hear suits mid-sized and large contact centres that want automated QA and clear reasons behind their call volumes. Its main limitation is transparency, since pricing, integrations and security details are only available through the sales team. The published case studies are encouraging, but they are vendor figures. Before signing, run a pilot on a few weeks of your own recordings and compare the findings with your current QA scores.