Building AI chat features often means too much complexity — SDKs, databases, and infrastructure — just to support conversations and memory. Conversations API removes that overhead. Build stateful AI chat without managing backend systems. All chat data is stored for you — you only keep the conversation_id. What it helps with – AI chat memory & state – Faster prompt iteration – No backend setup – Ideal for low-code builders Built after helping builders stuck on AI chat infra instead of product.
Hey Product Hunt 👋
I built Conversations API after repeatedly helping people integrate AI chat into their products.
The common problem wasn’t models — it was everything around them:
conversation memory, storage, infra, and slow iteration cycles.
This is a small, focused API that removes those blockers.
No SDKs. No databases. No infra to manage.
Happy to answer questions, explain design decisions, or hear what you’re building.
https://amarsia.comhttps://www.amarsia.com/document...
Sounds interesting! We’re actually building several AI startups, so we’ll take a look at your product with the team.
how does Amarsia handle context window optimization as the conversation history grows?
Can we bring our own API keys for different models, or is the billing centralized through Amarsia's infrastructure?
Interesting approach to handling conversation state. I'm curious about multilingual support — how does the API handle context and memory for non-English conversations? Also, does it offer any webhook integration for real-time events like new messages or conversation summaries?
Really like the direction you’re taking here.
From my experience building and shipping multiple tools, conversation memory and state management is where most AI projects get messy fast — too many SDKs, databases, and custom glue code just to keep context stable.
The “just configure and get an API” approach feels very practical, especially for indie builders and small teams who want to focus on product value, not infra.
Curious to see how this scales with longer conversations and multi-session users, but this is a solid abstraction layer. Nice work 👏
The 'no glue code' promise is exactly what we need right now. Managing backend state for LLMs is such a headache. How does Amarsia handle long-term memory retrieval—is it vector-based or something more structured?
Very nice, handling the backend for AI agents and bots is not easy. How long can you keep the context? in terms of tokens and time
Looking forward to checking this out! In my previous startup we dealt with conversation memory a lot and I still believe AI can help humans communicate better.
Congrats on the launch! I really like how opinionated and minimal this is, just keeping a conversation_id instead of juggling memory, storage, and infra feels very builder-friendly. What kinds of products you’re seeing benefit most from this so far?
Congrats on your launch guys!
For teams embedding conversational AI into web (e.g., React/Next.js) or mobile (React Native/Flutter) apps like us, how does your API handle client-side session management and persistence across page reloads or app restarts?
Wow, Amarsia looks amazing! The auto-stored conversation data sounds like a lifesaver for iterating. How does versioning handle changes that impact older conversation histories? Super curious!
Good idea to include memory out of the box, that's a big time savings for a new chat setup!
Curious This looks promising. Does the Conversation API also handle long-term memory limits, or is it mainly for session-based conversations?
Been cobbling a chat demo; keeping memory/state is the messy part. If Amarsia handles that + versioning, huge relief. How easy is data export or self-hosted later? I try to avoid lock-in. Either way, no-backend setup sounds handy for quick tests.
This looks clean! How do you handle long-running conversations as context grows? Do you summarize, chunk, or apply any memory pruning over time?
