10 Best AI Call Analytics Software of 2026

CallRail ranks first because it puts AI call analysis inside a call tracking product that a marketing team can buy and set up the same day. The $50 Lead Tracking plan already tracks calls and texts to their marketing source, records and routes calls, and transcribes and analyzes them. The $150 Lead Conversion plan adds Premium Conversation Intelligence: call summaries, sentiment analysis, trend reports that roll hundreds of calls into one summary, automatic tagging of outcomes such as appointment scheduled, and coaching feedback for staff. A useful marketing detail is self-reported attribution, where the AI notes how callers say they found you and reports it next to the tracking data. The tradeoff is usage billing. Extra local minutes cost $0.06 and extra analysis minutes $0.05, so high volume accounts should model their bill. CallRail also sells only in the US, Canada, the UK and Australia.

CallTrackingMetrics, also branded CTM, places second because it publishes every price and pairs attribution with call scoring that teams can define themselves. Marketing Lite costs $65 per month billed yearly and includes unlimited users with call and text attribution. The $149 Marketing Pro plan is the one to compare against CallRail: it includes 3,000 transcribed minutes, custom AI call analysis through AskAI, if/then triggers that score and route calls automatically, form tracking with 5,000 submissions, and sub-accounts with white labeling for agencies. Sales Engage at $274 adds a softphone, dynamic call scripts and live coaching, which makes CTM usable as a small contact center as well. HIPAA and GDPR options cover healthcare and EU work. The downsides are usage fees on top of the plan and a steep jump to the $1,999 Enterprise tier for volume pricing and a dedicated account team.

Dialpad is the strongest pick for teams that want call analysis to come with the phone system rather than sit on top of it. The $15 Standard plan already provides real-time transcripts and instant call summaries. Contact centers get more at the $89 Essentials tier, which adds AI recaps, PII redaction, sentiment and contact center analytics, while the $119 Advanced tier adds Live Coach for real-time guidance and Quality Management with AI CSAT, scorecards, playbooks and a coaching hub. Sales teams have their own ladder from $39, with Quality Management at the $79 Premium tier. Because every tier is published, Dialpad is easy to budget. The limit is focus: Dialpad analyzes calls placed through Dialpad, so it does not replace call tracking numbers or marketing attribution, and teams on another phone system would need to migrate.

JustCall fits teams that want a phone system with call scoring built in and published prices. The $29 Team plan includes unlimited AI transcription minutes under a fair usage policy, team performance reporting and more than 100 CRM integrations, with AI Review Assist available as an add-on. The analytics that matter for this list sit on Pro Plus at $89 per user billed annually: AI call scoring, sentiment analysis, standard and custom topics, coaching comments, real-time agent assist and AI-powered script compliance. That bundle is cheaper per seat than Dialpad's contact center Advanced tier, though Dialpad offers a deeper quality management workflow. JustCall requires at least 2 licenses on every self-serve plan and 10 on Business, where single sign-on and HIPAA compliance live. It does not offer marketing attribution, so marketers measuring ad spend should look higher on this list.

Aircall is a good fit for teams that already like a simple cloud phone and want AI analysis without a separate tool. The $30 Essentials plan, billed annually with a 3 license minimum, includes call and voicemail transcription. The Professional plan at $50 per license adds the call analytics this list is about: AI call summaries, sentiment analysis, key topics and talk-to-listen ratio, along with smart routing, queue callback and a power dialer. Call scoring, trending topics and the AI and transcription API come through the AI Assist add-on, so teams that want automated scorecards will pay more than the list price. Aircall connects to more than 250 apps, including Salesforce, HubSpot, Zendesk and Pipedrive. It ranks below JustCall because scoring is an add-on and below the enterprise tools because it lacks QA calibration workflows.

Invoca has the deepest marketing analytics on this list, but its custom pricing and enterprise focus put it sixth on a ranking that weights ease of use and value. Signal AI analyzes every call to score agents against your KPIs, track caller and agent sentiment, and surface trends through unsupervised machine learning. Signal AI Studio goes further by training models on your own calls to detect intent, product interest and conversion outcome, and those signals can flow back into Google Ads and other platforms for value-based bidding. The AI Quality Management product adds scorecards for outcomes, script adherence and compliance, with editable forms for soft skills such as empathy. Integrations cover Google, Salesforce, Adobe, HubSpot, Meta and Microsoft. Invoca does not publish prices and asks buyers to fill out a form for a proposal, so it suits enterprises with large call volumes more than small teams.

Level AI is built for QA leaders who want to stop sampling a handful of calls per agent. Its QA-GPT engine scores open-ended scorecard questions, not only yes or no checks, and shows the evidence and reasoning for every score across calls, chats, emails and bot conversations. Teams can keep the scorecards they already report on, mix AI-scored questions with human-scored ones in a single scorecard, and override AI scores, with those corrections used to recalibrate future scoring. Around QA the platform adds Agent Assist, screen recording, Voice of the Customer analytics and iCSAT. That depth makes it one of the most complete contact center analytics tools here. It ranks seventh because pricing is only available through a demo and because the product is not designed for marketing attribution, which half of this list's audience needs.

Gong is the reference product for B2B sales call analysis, and it earns a place here for revenue teams that want call insights tied to deals. It records and transcribes sales calls, meetings and emails automatically, then analyzes them for topics, objections, competitor mentions and buying signals, with sentiment and talk ratio analysis on top. Conversation data feeds deal and pipeline tracking, and Gong integrates with Salesforce, Zoom and other core platforms. Gong says its models are trained on billions of sales interactions. It ranks ninth on this list because it is not built for the inbound phone calls that marketing teams attribute or for contact center QA programs, and because pricing is a custom mix of per-user licenses and a platform fee based on the number of users. For B2B sales leaders, though, it remains a strong option.

Observe.AI positions its Interaction Intelligence product as the data layer under its own AI agents, and for call analytics that means full-coverage scoring with evidence. Auto QA evaluates every call and chat against your existing rubric and cites the transcript moment behind each line of the score. Reviewers handle edge cases through manual QA workflows for disputes and appeals, while calibration sessions keep AI and human scores aligned. Transcripts are redacted for PII, PCI and PHI, and the platform extracts intent, sentiment, entities and outcomes from every interaction. Case Management links calls, chats and emails about the same issue, so a customer who contacted you three times shows up as one record. Observe.AI does not publish pricing, and the wider platform, including voice and chat agents, is more than a small team needs, which keeps its value and ease of use scores lower.

CallMiner Eureka has the broadest analytics toolkit on this list, which is why it scores highest on features and lowest on ease of use. The platform captures and analyzes all omnichannel interactions and is sold as modules: Record and Screen Record for capture, Redact for sensitive data, Analyze and Visualize for insight, Coach and RealTime for agent guidance, and Outreach and OmniAgent for automation and virtual agents. CallMiner lists use cases that go beyond QA, such as fraud detection, risk and compliance, sales effectiveness, and product and brand experience, across industries like collections, insurance, healthcare and BPOs. That breadth suits large enterprises with dedicated analytics teams. For everyone else, the module count, demo-only pricing and longer rollout make it harder to justify than Level AI or Observe.AI, so it closes the list at tenth.