**Avintra** is an enterprise Agentic AI and workflow automation platform that enables organizations to build, deploy, orchestrate, and scale AI agents and business automations. Avintra helps automate complex business processes across finance, HR, customer service, IT, and operations. Its unique execution-based pricing model lets organizations pay only for AI agent execution run-time - eliminating traditional per-user and per-license costs.
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Maker
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We are entering a new era where Artificial Intelligence is reshaping every aspect of business. Yet, AI delivers value only when it is connected to the systems, data, processes, and people that drive an organization. That belief is at the heart of Aventisia.
Our mission is simple - to help enterprises adopt AI with confidence. With Avintra, we are building a platform that enables organizations to design, orchestrate, and govern intelligent workflows that seamlessly combine AI, automation, and human collaboration. By abstracting technical complexity, Avintra empowers teams to focus on solving business problems and delivering measurable outcomes.
We also believe that trust is fundamental to enterprise AI. As organizations embrace intelligent systems, governance, security, transparency, and control become as important as innovation itself. Every capability we build reflects this commitment, ensuring our customers can scale AI responsibly while maintaining the reliability and compliance their businesses demand.
At Aventisia, we see AI not as a replacement for people, but as a force multiplier that enhances human potential, accelerates decision-making, and enables organizations to operate with greater agility. Our goal is to provide the foundation on which businesses can build the next generation of intelligent operations.
Kaushal Agarwal
Co-founder & CEO
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The execution-based pricing model is a smart move for enterprise adoption, especially since it sidesteps the usual sticker shock from per-seat licensing. Curious how the orchestration layer handles complex handoffs between agents across different departments.
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Curious how the execution-based pricing actually plays out in practice, like does a single multi-step workflow across finance and HR count as one execution or does each agent handoff get billed separately?
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The execution-based pricing caught my attention. Most enterprise AI platforms still charge per seat or per agent, but pricing on actual execution feels much closer to how customers measure value. Curious what led you to that model, and how enterprise buyers have responded to it so far?
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Would love to see a built-in observability dashboard that tracks per-agent token usage, success rates, and average runtime. Paying per execution is great, but without granular analytics it is hard to spot which workflows are actually driving value and which ones need tuning.
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The execution-based pricing caught my attention right away, finally a model that scales with actual usage instead of seat counts. Spent some time wiring up a small finance workflow and the orchestration felt surprisingly clean.
Report
Spent some time poking around the demo and the pay-per-execution pricing actually feels refreshing, especially for finance and HR workflows that don't run constantly. Also like that I could string a few agents together without it feeling like enterprise bloat.
The execution-based pricing model is a smart move for enterprise adoption, especially since it sidesteps the usual sticker shock from per-seat licensing. Curious how the orchestration layer handles complex handoffs between agents across different departments.
Curious how the execution-based pricing actually plays out in practice, like does a single multi-step workflow across finance and HR count as one execution or does each agent handoff get billed separately?
The execution-based pricing caught my attention. Most enterprise AI platforms still charge per seat or per agent, but pricing on actual execution feels much closer to how customers measure value. Curious what led you to that model, and how enterprise buyers have responded to it so far?
Would love to see a built-in observability dashboard that tracks per-agent token usage, success rates, and average runtime. Paying per execution is great, but without granular analytics it is hard to spot which workflows are actually driving value and which ones need tuning.
The execution-based pricing caught my attention right away, finally a model that scales with actual usage instead of seat counts. Spent some time wiring up a small finance workflow and the orchestration felt surprisingly clean.
Spent some time poking around the demo and the pay-per-execution pricing actually feels refreshing, especially for finance and HR workflows that don't run constantly. Also like that I could string a few agents together without it feeling like enterprise bloat.