Agentic AI Comparison:
Avaamo vs Project Mariner

Avaamo: 8

Avaamo provides agentic conversational AI workflows and pre-built virtual agents that can automate customer service, patient access, employee support, and other enterprise processes across voice and digital channels. Its platform supports thousands of workflows, with some packaged solutions (e.g., appointment scheduling, MyChart support, prescription workflows, records access agents) designed to run 24/7 and autonomously manage tasks like scheduling, portal access support, and information retrieval with minimal human intervention. The platform allows deep integration into EHRs, ERPs, and other enterprise systems via 150+ connectors and APIs, enabling agents to perform transactional operations, route requests, and update records programmatically, which indicates substantial operational autonomy in production environments. At the same time, Avaamo’s autonomy is typically constrained by enterprise workflows, policies, and supervision; agents are configured per use case, with defined intents and guardrails rather than general-purpose free-form web navigation, so its autonomy is strong but more domain-bound compared to Mariner’s browser-level, general web agent capabilities.

Project Mariner: 9

Project Mariner was explicitly designed as a high-autonomy web agent that can take control of the Chrome browser, move the cursor, click buttons, fill out forms, navigate websites, and complete multi-step tasks with minimal human micro-management. It leverages Gemini’s multimodal capabilities to see the screen, understand complex page layouts (including images, code, and forms), reason about goals, and plan a sequence of actions, making it capable of tasks like booking travel, online shopping, and complex data-gathering workflows based only on natural language instructions. Benchmark performance on real-world web tasks — e.g., an 83.5% score on WebVoyager and a reported ~91% success rate on WebArena — further indicates that Mariner can independently carry out a broad range of web-based tasks with relatively high reliability compared to earlier agents. However, as a research prototype, its autonomy still operated within safety constraints such as user oversight and intervention, and it was not broadly tuned for fully unsupervised enterprise operations, which justifies a very high but not perfect autonomy score.

Avaamo: 8

Avaamo is designed for enterprise usability, providing a full conversational AI platform with pre-built agents, guided configuration, analytics, and integration tooling, as well as omnichannel deployment options that allow organizations to roll out agents via web, mobile, voice, and messaging channels with relatively low friction. Key usability features include pre-built workflows, domain ontologies, and vertical solutions that reduce the amount of configuration required for common scenarios (e.g., healthcare front-door, banking customer service), as well as trial/sandbox environments (e.g., free platform trial or sandbox with thousands of interactions) for exploration without upfront commitment. Enterprises can configure agents with graphical tools, leverage 150+ pre-built integrations, and use built-in analytics for monitoring and optimization, making setup and ongoing operations relatively straightforward for a typical enterprise IT or CX team. The need for sales engagement and solution design for complex use cases introduces some friction, but overall usability is high given Avaamo’s focus on production deployments and supporting documentation.

Project Mariner: 6

Project Mariner was accessed as an experimental Chrome extension that accepted natural language instructions, allowing users to describe high-level goals (e.g., buy groceries, book tickets, collect emails from a spreadsheet) and have the agent plan and execute the actions in the browser. This interaction model — chatting with the agent while it performs the work in the background — is conceptually simple for end users and reduces the need for manual navigation or scripting. However, Mariner was limited to select trusted testers, framed as a research prototype, and not supported with broad user-facing documentation, onboarding, or standardized configuration tools typical of commercial products. The need to understand its experimental nature, occasional task failures (acknowledged by Google as not always precise or fast), and the lack of persistent production support or configuration UI for non-technical users reduce its overall ease-of-use score relative to mature enterprise platforms.

Avaamo: 9

Avaamo offers broad platform flexibility across use cases, channels, languages, and integrations: it supports omnichannel deployment (voice, chat, web, mobile), over 100–114 languages, and more than 150 pre-built integrations (APIs, web services, ESBs, MQs, custom adapters) into enterprise systems such as ERPs and EHRs. The platform allows configuration of custom workflows and use cases via a flexible agentic framework, with billing per use case and support for unlimited sessions and users within each use case, indicating that enterprises can design very different agents for different processes (e.g., appointment scheduling, portal support, prescription management, record sharing, internal employee support). Avaamo’s presence across 21+ industries and concentration in verticals like healthcare, banking, and insurance further reflects its adaptability to varied operational contexts and regulatory environments. While it does not operate as a general-purpose browser agent for arbitrary websites, its flexibility across enterprise IT environments, contact channels, and domain-specific workflows is extremely high, justifying a slightly higher score than Mariner for overall flexibility in real-world deployments.

Project Mariner: 8

Project Mariner’s core design — a Gemini-based agent that perceives the visual contents of arbitrary web pages, reasons about tasks, and controls Chrome — inherently gives it high flexibility in the domain of web-based tasks. Mariner can operate across diverse sites (e-commerce, travel, information portals, forms, spreadsheets, etc.), interpret different user goals, and plan multi-step actions such as searching listings, filling forms, gathering data, and booking services, without requiring site-specific code or manual scripting. It supports complex, multi-step workflows and autonomously adapts to varying page layouts using multimodal understanding and browser interaction protocols, which is more flexible than traditional rule-based web automation. However, its flexibility is primarily limited to browser interaction; it does not present itself as a generalized multi-channel enterprise automation platform with built-in connectors to back-office systems or omnichannel channels, and its experimental, non-customizable nature for enterprises constrains its practical flexibility in organizational settings.

Avaamo: 6

Avaamo uses a subscription and pay-per-use-case pricing model, where enterprises are billed per automated workflow with unlimited sessions, users, and languages included, but most specific prices are available only through direct sales engagement. Some public references describe significant annual costs (e.g., pricing starting around $100k/year per use case for certain deployments, or around $1,000,000 per year for particular patient access automation solutions), indicating that Avaamo targets large enterprises with substantial budgets, especially in healthcare. However, Avaamo also offers a free platform trial or sandbox with thousands of interactions (e.g., free trial without a credit card, free sandbox with up to 5,000 interactions per month in some reviews), which lowers initial cost barriers for testing and proof-of-concept work. The lack of transparent public tier pricing and the high typical contract sizes mean cost can be relatively high for smaller organizations, but for large enterprises the per-use-case structure with unlimited usage can be cost-effective when spread across large volumes of interactions.

Project Mariner: 4

Project Mariner was a research prototype, and publicly available information emphasizes its experimental status, limited trusted-tester rollout, and eventual discontinuation rather than a clear, stable pricing model. There is no widely documented commercial pricing structure (subscriptions, per-seat fees, or usage-based charges) for Mariner, and it does not appear to have been sold as a standalone product to enterprises before Google shut it down in May 2026. While prototypes may be available at no direct monetary cost to selected testers, the absence of a defined pricing model, potential internal resource costs for integration and evaluation, and the fact that the agent is no longer available for production use effectively limit its cost-effectiveness and predictability for organizations planning long-term deployments. As a result, Mariner receives a low score for cost from a practical procurement perspective, despite possibly being free to some testers during its experimental phase.

Avaamo: 8

Avaamo has significant enterprise adoption, with data indicating that companies using the platform are concentrated in large organizations (often >10,000 employees and >$10B in revenue) and span over 21 industries, including strong presence in IT services and healthcare. The platform is used worldwide, with a majority of customers in the United States and notable adoption in India, and is particularly prominent in healthcare, banking, and insurance sectors where conversational AI and automation solutions are in high demand. Listings on software review and market intelligence sites, along with AWS Marketplace entries and third-party reviews, reinforce that Avaamo is recognized as a leading enterprise conversational AI platform and agentic solution for patient access automation and other regulated verticals. While it may be less known among general consumers compared to consumer-facing chatbots, its penetration in large enterprises and vertical solutions supports a high popularity score in its target markets.

Project Mariner: 5

Project Mariner attracted significant media and technical-community attention at launch, with coverage from major technology outlets and inclusion in AI agent benchmarks and wikis, reflecting strong interest among AI researchers and practitioners. It was introduced at Google I/O and during Google AI events, and later rolled out more broadly to users and developers beyond the initial trusted testers, but always within an experimental frame rather than as a mainstream consumer or enterprise product. Its discontinuation in May 2026, as reported by media sources noting the shutdown of the tool and the removal or archiving of its landing page, limits long-term adoption and ongoing popularity, even though it remains notable as a reference point in the evolution of agentic AI. Given this trajectory, Mariner’s popularity is meaningful in the research and early adopter community but modest in terms of sustained, large-scale production usage or market penetration, justifying a mid-range score.