Best AI Analytics Tools (2026)

Understand how users interact with your AI agents.

Why it's here: Purpose-built for AI agent analytics, unlike generic tools repurposed for LLMs

Voker is an analytics platform built specifically for AI product teams who want to monitor, analyze, and improve the performance of their AI agents and conversational products. Rather than relying on generic web analytics tools that were never designed with AI in mind, Voker gives teams a dedicated workspace to track how users engage with their agents, where conversations break down, and how agent behavior evolves over time. It is especially useful for product managers, engineers, and AI developers who are shipping LLM-powered features and need actionable insights beyond simple usage counts. Voker helps teams identify friction points in agent workflows, surface patterns in user queries, and make data-driven decisions about how to tune and improve their AI products. By centralizing agent telemetry and conversation analytics in one purpose-built platform, Voker reduces the guesswork involved in iterating on AI-powered experiences and gives teams the clarity they need to ship better, more reliable agents faster.

Automatically detect and fix product usability issues as you ship.

Why it's here: Proactive issue detection reduces reliance on manual QA and user complaints

Novus is an AI-powered analytics tool built by Pendo that automatically catches and resolves usability problems in digital products the moment they are shipped. Designed for product managers, UX designers, and engineering teams, Novus continuously monitors user interactions to surface friction points, drop-offs, and confusing workflows that might otherwise go unnoticed until they impact retention. What makes Novus stand out is its proactive, automated approach: rather than waiting for support tickets or manual testing cycles, it flags issues in real time and suggests or applies fixes without requiring deep analytical expertise from the user. It integrates naturally into the Pendo ecosystem, meaning teams already using Pendo for product analytics can layer on Novus capabilities with minimal setup overhead. Whether you are launching a new feature or iterating on an existing workflow, Novus helps ensure that quality and usability are maintained continuously, reducing the gap between shipping and learning.

Stop overpaying for LLM tokens with smart cost visibility.

Why it's here: Provides clear, actionable visibility into AI spending that is otherwise hard to track

Tokenwise is an intelligent LLM proxy tool designed to help developers, startups, and engineering teams gain full visibility into their AI API spending and identify exactly where they are overpaying. By sitting between your application and large language model providers like OpenAI, Anthropic, and others, Tokenwise intercepts requests and delivers detailed cost breakdowns so you can make data-driven decisions about your AI infrastructure. The tool is especially useful for teams running multiple LLM-powered features simultaneously, where token costs can spiral quickly and silently without proper monitoring. Tokenwise surfaces inefficiencies in prompt design, model selection, and request frequency, giving engineers and product managers the insights they need to optimize spending without sacrificing output quality. Whether you are a solo developer prototyping with GPT-4 or an enterprise team processing millions of tokens per month, Tokenwise helps you understand your true AI costs and take action to reduce them.

Unlock product analytics programmatically for AI agents and developers.

Why it's here: Eliminates manual dashboard navigation by exposing analytics programmatically

Mixpanel Headless is a programmatic API layer built on top of Mixpanel's product analytics platform, designed to give AI agents, automation pipelines, and developers direct query-based access to their analytics data. Rather than navigating a visual dashboard, developers can retrieve metrics, funnels, retention data, and event-level insights through structured API calls, making it possible to embed product analytics into custom workflows, LLM-powered agents, and backend systems. This tool is ideal for engineering teams, data engineers, and AI developers who need to integrate behavioral product data into broader automated systems without manual dashboard interaction. What makes Mixpanel Headless particularly useful is its ability to serve as the analytics backbone for AI-driven product monitoring, automated reporting, and intelligent alerting systems. By exposing Mixpanel's rich event tracking and segmentation capabilities in a headless format, teams can build agents that proactively surface anomalies, answer natural language questions about user behavior, or feed real-time product signals into other tools and models. It bridges the gap between traditional analytics platforms and the growing ecosystem of AI-native developer tooling.

Embed powerful AI analytics directly inside your product today.

Why it's here: Dramatically reduces time to ship analytics features compared to building in-house

Basedash Embedded Analytics is a freemium AI-powered analytics platform that allows SaaS companies and product teams to embed fully functional, customizable analytics dashboards directly inside their own applications. Instead of forcing customers to leave your product to access data insights, Basedash lets you deliver a native analytics experience that feels like a seamless part of your platform. It is best suited for product managers, engineering teams, and SaaS founders who want to offer their customers self-serve data exploration without building a custom analytics stack from scratch. What makes Basedash especially useful is its AI-driven query layer, which lets end users ask natural language questions about their data and receive instant visual answers, no SQL knowledge required. The platform connects to common databases and data sources, renders interactive charts and tables, and gives you fine-grained control over branding and permissions so your customers see only what they should. Whether you are building a B2B SaaS tool, an internal operations platform, or a customer-facing dashboard product, Basedash provides a fast path to shipping analytics features that would otherwise take months of engineering effort.

Pinpoint exactly when YouTube viewers love your content

Why it's here: Delivers granular, timestamp-specific insights that standard YouTube Analytics does not provide

LikePulse is an AI-powered analytics tool that reveals the precise moments in YouTube videos where audience engagement peaks, helping creators and marketers understand what resonates most with viewers. By mapping reactions and engagement signals to specific timestamps, LikePulse gives video creators a clear picture of which segments spark the most interest, so they can replicate success in future productions. It is particularly useful for YouTubers, content strategists, brand marketers, and video editors who want to move beyond vanity metrics and make data-driven decisions about pacing, storytelling, and content structure. Rather than guessing why some videos perform better than others, users can pinpoint the exact scenes or talking points that hold attention or trigger reactions. This granular insight saves time during the editing process and helps creators focus their energy on producing the moments audiences actually care about, ultimately improving watch time, subscriber growth, and overall channel performance.