We provide an OpenAI-compatible orchestration layer that lets teams compose their own “virtual models” on top of any LLM - combining prompts, reasoning, review, and guardrails, and use them everywhere from your IDE to your backend. Key features 🔌 One OpenAI-compatible API for many LLMs 🧱 Custom models you name & reuse 🧠 Reasoning mode on demand ✅ Built-in review mode 🛡️ Guardrails & PII masking 🧑💻 IDE & CLI integrations 📊 Analytics & cost controls
Hey Product Hunt! 👋
I'm Shreyans, cofounder of AskCodi.
After years of building askcodi as an frontend layer for constant AI releases. We are moving away from consumer tech and focusing on our expertise bring Research to Consumers.
First step building an LLM orchestration layer that lets you build your own custom coding models on top of any LLM and making it accessible using openai compatible api.
Instead of calling gpt-5.1 directly, you call things like:
- code-generator-model
- bugfix-with-review
- secure-code-review
Each “custom model” is a recipe: prompts + reasoning + review + guardrails.
- Stack prompts, tools, reasoning, review, and guardrails into a single model name you can call anywhere.
- Enable reasoning and self-check flows for complex coding tasks, even on non-reasoning base models.
- Add an automatic review pass: generate, then review for bugs, security, and style in one call.
- Mask sensitive data and enforce organization policies at the model layer.
Our goal is simple: make small and open-source models as effective as frontier LLMs at a fraction of the cost.
If you’re experimenting with AI in your dev workflow or already rely on tools like Codex, CC, Copilot, or Cursor.
I’d love your feedback and support.
Interesting! Is it possible to remove ChatGPT’s restrictions? It currently limits certain topics, and I don’t need such restrictions in my project.
@AskCodi@shreyans_assistiv Custom LLMs without training is clever, most tools require massive datasets and compute.
Does AskCodi work well for design-adjacent workflows (like generating design system docs or component descriptions), or is it purely code-focused?
Also curious about the OpenAI-compatible API, does that mean it's a drop-in replacement for existing GPT integrations?
Wow, this sounds really powerful! 😄 An OpenAI-compatible orchestration layer that lets you build custom virtual models on top of any LLM is super flexible. Love the built-in reasoning, review, and guardrails plus IDE & CLI integrations make it super practical for teams. Excited to see how people use this!
Congratulations. And happy product launch. @sachinsharma
Congrats on the launch! Love the idea of turning coding workflows into callable custom models. How you handle model evaluation across different LLMs?
Amazing work, Shreyans! Saving time while improving code quality is exactly what developers need.
Hey everyone! 👋
I’m one half of the AskCodi founding team, and I wanted to share a quick personal angle on why this launch matters to me.
Over the past few months, I’ve been using AskCodi with Cline daily for my own dev work. I’d been relying on another agentic app/CLI before, but it started slowing me down, rate limits, sluggish generations, and a drop in quality as my projects got more complex.
AskCodi changed that. Full control over prompt engineering let me finally get reliable, high-quality outputs. And with AskCodi’s orchestration layer, I could:
plan with a smaller, cheaper model,
switch to a stronger one for execution,
and keep it all wrapped in one custom setup.
Plus, with how fast new LLMs are coming out, AskCodi makes it dead simple to swap them in without reworking your whole workflow. That alone has saved me a ton of time.
This launch is special to me not just as a builder, but as someone who’s shipped real work using this system. If you're into agentic workflows or just want more control than typical coding assistants offer, I’d love to hear what you think. 🚀
