Agentic AI Comparison:
Lindy.ai vs Project Astra

Lindy.ai: 8

Lindy agents can execute multi-step workflows (e.g., lead qualification, follow-ups, CRM updates) based on high-level goals rather than step-by-step instructions, functioning as an AI orchestration and automation platform rather than a simple trigger–action tool. It supports agent-level reasoning, event-based triggers, and high-volume task handling, allowing agents to operate with substantial autonomy once configured, though governance and error handling are still evolving and complex workflows require careful design.

Project Astra: 9

Project Astra is explicitly positioned as a universal AI agent with strong multimodal capabilities—understanding speech, images, and live video, and leveraging tools like Search, Lens, and Maps—while maintaining short-term memory to sustain context over an interaction window. Its ability to perceive the physical environment in real time and respond conversationally indicates very high potential autonomy in interactive scenarios, but it is still a research prototype with limited public evidence of robust, repeatable workflow automation or long-term task management, and memory is currently short (about 10 minutes).

Lindy.ai: 9

Lindy is designed as a no-code agent builder, explicitly emphasizing accessibility so that users can create agents in minutes without touching code—by giving a prompt and connecting tools—backed by templates, onboarding flows, and a refined UX. Reviews describe agent building as “stupidly simple,” though there is a learning curve for designing complex workflows and some users feel constrained by credit-based usage when experimenting freely.

Project Astra: 6

Project Astra’s interaction paradigm—natural language with multimodal input (voice, camera, images)—is inherently intuitive for end users, and Google’s demos emphasize frictionless, conversational usage. However, Astra is still in a prototype stage with access limited to testers, no public tooling for workflow design or integration management, and no documented no-code builder or templates, which makes it currently much less accessible and operationally usable than mature SaaS platforms.

Lindy.ai: 8

Lindy supports a wide range of business use cases—lead qualification, customer support, outbound sales, scheduling, email management, and more—through configurable agents, customizable templates, and over 200 integrations with tools like Gmail, Slack, HubSpot, and Google Drive. It enables custom logic flows and goal-based workflows and can handle high volumes, but its no-code design can be restrictive for highly specialized or deeply customized tech stacks, and it is less ideal for teams wanting low-level technical control.

Project Astra: 7

Project Astra is architected for broad multimodal flexibility, able to process text, audio, images, and live video, and to use multiple Google tools (Search, Lens, Maps) in a unified agentic experience, making it highly adaptable conceptually for real-world interactions. Nonetheless, documented constraints include short-term memory (around 10 minutes) and the absence of public APIs, workflow builders, or integration ecosystems, which limits how flexibly third parties can currently harness Astra for complex or persistent workflows.

Lindy.ai: 8

Lindy uses a transparent credit-based SaaS model with a generous free tier (e.g., around 400 tasks/credits per month) and paid plans like Pro and Business that scale task capacity and features. Independent reviews note that serious usage generally requires paid tiers and that credit consumption can discourage casual experimentation, but overall the Pro plan is described as offering strong value compared to competitors for teams automating thousands of tasks.

Project Astra: 5

There is currently no official public pricing or plan for Project Astra; it is accessible only to trusted testers and waitlist users, and is positioned as a research prototype rather than a commercial SaaS product. While this may mean no direct cost for some testers, the absence of defined pricing, SLAs, or usage guarantees makes it impossible for most organizations to plan or model costs, effectively limiting its economic usability at present.

Lindy.ai: 7

Lindy is featured in multiple third-party roundups of top AI agents and automation platforms, often highlighted for no-code accessibility, integrations, and business use cases in 2025–2026. It is gaining traction within the AI automation niche, but remains a specialized tool rather than a mass consumer brand, and its visibility is mostly within professional and tech circles rather than the general public.

Project Astra: 9

Project Astra comes from Google DeepMind and has been widely covered as a flagship multimodal agent prototype, with significant attention from both mainstream media and the AI research community. Despite limited public access, the combination of Google branding, cutting-edge demos, and its positioning as a universal agent has driven high awareness and interest relative to most commercial agent platforms.