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DronaHQ Agentic Platform
One framework for chatbots, webhook, voice & data agents
DronaHQ is a full-featured agentic AI platform for building any kind of production-ready agent — chatbots with gen UI, intelligent APIs, voice agents, data agents. It brings together LLMs, 1000+ tools, a ready skill library, vector DB, memory, native RAG, observability, guardrails, and evals inside a single execution engine. Comes with a built-in AI copilot that lets you describe the agent and builds it for you. No middleware to host. Just simple, usage-based pay-as-you-go plans.
Happy to go deep on anything — how memory works across sessions, how RAG is set up for enterprise use cases, what Gen UI looks like in a real app, or how Artisan (our prompt-to-agent copilot) actually assembles an agent under the hood. Drop your questions below
Also genuinely curious: what kind of agent would you build first? Customer support? Sales assistant? Internal knowledge bot? Voice agent? Something weirder? Tell us.
I have been at this since 2014 — bootstrapped, computer science grads who just couldn't stop building tools for other builders.
Honestly, launching an agentic platform wasn't the plan two years ago. We were deep in internal tooling and dashboards. But customer after customer started asking the same thing: "Can we add an AI layer to this?" And every time we dug in, we saw how fragmented it was — LLM here, vector DB there, tool integrations scattered everywhere, and zero visibility into what the agent actually did once it ran.
That's the gap we decided to close. Not just an agent builder — a complete platform with Artisan, our onboard copilot, means you don't start from a blank canvas — just describe what you want and it assembles the agent for you.
I have spent 10 years watching how software really gets built inside companies. This is our bet on how the next decade looks.
Would love to hear what you'd build — or what's broken in your current AI stack.
Use code AGENT25PH for free community credits. No credit card needed.
Happy to go deep on anything — how memory works across sessions, how RAG is set up for enterprise use cases, what Gen UI looks like in a real app, or how Artisan (our prompt-to-agent copilot) actually assembles an agent under the hood. Drop your questions below
Also genuinely curious: what kind of agent would you build first? Customer support? Sales assistant? Internal knowledge bot? Voice agent? Something weirder? Tell us.
I have been at this since 2014 — bootstrapped, computer science grads who just couldn't stop building tools for other builders.
Honestly, launching an agentic platform wasn't the plan two years ago. We were deep in internal tooling and dashboards. But customer after customer started asking the same thing: "Can we add an AI layer to this?" And every time we dug in, we saw how fragmented it was — LLM here, vector DB there, tool integrations scattered everywhere, and zero visibility into what the agent actually did once it ran.
That's the gap we decided to close. Not just an agent builder — a complete platform with Artisan, our onboard copilot, means you don't start from a blank canvas — just describe what you want and it assembles the agent for you.
I have spent 10 years watching how software really gets built inside companies. This is our bet on how the next decade looks.
Would love to hear what you'd build — or what's broken in your current AI stack.
Use code AGENT25PH for free community credits. No credit card needed.