Cygnetium gives every business an AI workforce that learns how the organization works, takes real action, and delivers outcomes over days, weeks, and months, so people set the direction and the work gets done. Features include mission-driven workflows, AI Boardroom, My Apps, Knowledge Base, persistent memory, 500+ LLMs, enterprise integrations, and human-in-the-loop oversight.
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how does it actually handle long-running workflows when something goes wrong mid-process, like an api call failing a week in?
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Maker
@sonerh1i2ย There are guard rails in place to surface any issues or failures to the user. There is a notification system for these events as well as a system log. It will retry on its own first though and if there are more than three retries it will tell the user. It should never fail in silence.
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The persistent memory feature is what caught my attention, set up a workflow for client follow-ups and it actually remembered context from previous runs without me re-explaining. Feels closer to a real teammate than another chatbot wrapper.
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Maker
@tugay865925ย The way we engineered it is that the memory is persistent even if you swap out LLM's to do a specific task, or the lead agent doing a task delegates jobs to different LLM sub-agents. I might do a blog post on it as it is fairly unique.
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Hunter
Hey Product Hunt! ๐
Jack here, Product Manager at Cygnetium.
Super excited to finally launch today and share what our team has been building.
We built Cygnetium because we believed enterprise AI should do more than answer prompts. Organizations need AI that can take a business objective, coordinate specialist AI agents, produce real deliverables, and help teams complete meaningful work from start to finish, while keeping people firmly in control of every decision. Security, governance, and human oversight have been core principles from day one.
We'd really appreciate any feedback you have, and feel free to give Cygnetium a try. Thanks for checking us out!
how does it actually handle long-running workflows when something goes wrong mid-process, like an api call failing a week in?
@sonerh1i2ย There are guard rails in place to surface any issues or failures to the user. There is a notification system for these events as well as a system log. It will retry on its own first though and if there are more than three retries it will tell the user. It should never fail in silence.
The persistent memory feature is what caught my attention, set up a workflow for client follow-ups and it actually remembered context from previous runs without me re-explaining. Feels closer to a real teammate than another chatbot wrapper.
@tugay865925ย The way we engineered it is that the memory is persistent even if you swap out LLM's to do a specific task, or the lead agent doing a task delegates jobs to different LLM sub-agents. I might do a blog post on it as it is fairly unique.
Hey Product Hunt! ๐
Jack here, Product Manager at Cygnetium.
Super excited to finally launch today and share what our team has been building.
We built Cygnetium because we believed enterprise AI should do more than answer prompts. Organizations need AI that can take a business objective, coordinate specialist AI agents, produce real deliverables, and help teams complete meaningful work from start to finish, while keeping people firmly in control of every decision. Security, governance, and human oversight have been core principles from day one.
We'd really appreciate any feedback you have, and feel free to give Cygnetium a try. Thanks for checking us out!