Corectic AI

Turn AI API costs into a profit center

6 followers

Turn AI API costs into a profit center

6 followers

A single API key routes to 11 LLM providers with automatic fallback and semantic caching (up to 30% cost cuts). Track every token in real time, then resell access to your own clients with built-in margins, white-label dashboards and Stripe billing.

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Launch tags:API•Analytics•SaaS

Launch Team / Built With

Viktor.comAn AI coworker that actually does the work

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Maker

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A few months ago, I realized how difficult it is and the lack of a clean interface to centralize all these AI APIs, which would allow anyone using AI APIs to manage their costs. But if that were all, it would be too simple. So I racked my brains to find ways to reduce these costs that weigh heavily on intensive use of AI in SaaS or other applications. I then developed the idea of a proxy system that intercepts the user's request and processes it to decide its fate if it is sent to the AI provider in question (Claude, Chat GPT, Gemini, etc.). Or, I could switch to decoding in my system which can return pre-recorded answers for similar questions, which blocks the request to the AI and reduces token costs both for sending and receiving. With a semantic caching system. We can also compare the models, but the biggest part is yet to come. I'd like to get some feedback to know if anyone is curious or not.

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3mo ago

Forum Threads

p/corectic-ai

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3mo ago

Everyone watches their OpenAI bill. Almost nobody knows which feature is burning it.

I spent a year shipping AI features and the hardest part was never the AI. It was the bill.

I started with one provider, then added a second for longer context, a third for the cheap calls. Pretty quickly I had four keys, four SDKs, and four billing pages that never agreed. At the end of the month I could see one number, the total, and almost nothing about where it actually went. Which feature, which customer, which model.

A few things I learned the hard way:

The total bill is the least useful number you have. Attribution per feature and per model is what tells you where to cut.
A lot of traffic repeats more than you think. Support questions, retries, docs lookups. Caching the answer to those saved me more than swapping to a cheaper model ever did.
But naive caching is dangerous. Matching on wording alone serves confident wrong answers. You need something that checks the meaning actually matches, and a freshness rule so it never serves stale data.
Cheaper model does not mean cheaper request. Some cheap models are wordy and burn more tokens per answer than a pricier one that gets to the point.

p/corectic-ai

•

3mo ago

We're live on Product Hunt today 🚀

CoreCtic AI centralizes every AI provider you use behind one API key, with semantic caching, real time cost tracking, and reseller billing built in for agencies.

Support and feedback very welcome

p/corectic-ai

•

3mo ago

We go live tomorrow! Happy to answer any questions before then

Hey everyone

CoreCtic AI officially launches on Product Hunt tomorrow, and I wanted to drop by the discussion here first.

Quick recap of what it does: a single, OpenAI compatible API key that routes across 11 LLM providers (OpenAI, Claude, Gemini, Mistral and more) with automatic fallback if one goes down. On top of that, semantic caching that matches questions by meaning (not just identical prompts) to cut repeat query costs, real time cost tracking, and native reseller monetization so agencies and freelancers can bill their own clients for AI access with a real margin, no extra billing tooling needed.

If you've got questions about how the routing, caching or reseller billing actually works, or anything else, ask away, I'll be checking back throughout the day. And if you want a heads up when we go live tomorrow, following the page here will do it.

View all

Forum Threads

p/corectic-ai

•

3mo ago

Everyone watches their OpenAI bill. Almost nobody knows which feature is burning it.

I spent a year shipping AI features and the hardest part was never the AI. It was the bill.

A few things I learned the hard way:

The total bill is the least useful number you have. Attribution per feature and per model is what tells you where to cut.
A lot of traffic repeats more than you think. Support questions, retries, docs lookups. Caching the answer to those saved me more than swapping to a cheaper model ever did.
But naive caching is dangerous. Matching on wording alone serves confident wrong answers. You need something that checks the meaning actually matches, and a freshness rule so it never serves stale data.
Cheaper model does not mean cheaper request. Some cheap models are wordy and burn more tokens per answer than a pricier one that gets to the point.

p/corectic-ai

•

3mo ago

We're live on Product Hunt today 🚀

CoreCtic AI centralizes every AI provider you use behind one API key, with semantic caching, real time cost tracking, and reseller billing built in for agencies.

Support and feedback very welcome

p/corectic-ai

•

3mo ago

We go live tomorrow! Happy to answer any questions before then

Hey everyone

CoreCtic AI officially launches on Product Hunt tomorrow, and I wanted to drop by the discussion here first.

View all