UnZip

Compress
AI Compute. CA : EuMD8NdJzD7BYEk2kBMRhGBhBVR11EyJDJfzxW5upump

[UnZip @Unzipfit]

Most teams overpay for LLMs because every call hits the provider at full price, even when the same or a similar prompt was already answered minutes ago.

$UnZip is an OpenAI-compatible gateway that sits between your app and OpenAI, Anthropic, or Groq. You change one line your base URL and keep your existing code.

From there, every request is checked against an exact cache, then a semantic cache, compressed when it's safe to, routed to the right provider, and automatically failed over if one goes down. You see the real cost and the savings on every call.

[UnZip @Unzipfit]

2026 AI meta is here.

Stop throwing money at bigger models.

Unzip compresses your compute at the infrastructure level.

One proxy. Massive savings.

Semantic cache, adaptive routing, and prompt compression working together.

Your burn rate just got a reality check.

https://t.co/9P6FKZiBN2

[UnZip @Unzipfit]

Quick question for AI builders:

What % of your token spend is actually necessary?

We help teams cut the waste.

Unzip gives you:
• Semantic cache (41%+ hit rate typical)
• Intelligent routing
• Prompt compression

All with <100ms overhead.

Ready to UnZip your compute?

https://t.co/9P6FKZiBN2

[UnZip @Unzipfit]

UnZip Vision becomes the optimization control plane for AI compute.

Instead of developers thinking about raw model calls, they route AI traffic through UnZip:

Application → UnZip Gateway → Model Providers / Local Models

UnZip decides:

• whether the request can be served from semantic cache;
• whether the prompt/context should be compressed;
• which model/provider should handle the task;
• whether requests should be batched;
• how to fallback if quality/latency/cost constraints fail;
• how much compute was saved;
• whether the output quality is acceptable.
• Long term, UnZip can become an intelligent CDN-like layer for AI workloads.

[UnZip @Unzipfit]

AI products are increasingly expensive to operate. Many teams can build useful AI features, but struggle to make the unit economics work. Every chat, agent task, code generation request, support reply, retrieval query, and summarization flow consumes tokens and compute.

• This creates several painful outcomes:
• AI SaaS margins collapse as usage grows.
• Teams limit features because inference cost is unpredictable.
• Developers manually build caching/routing hacks inside their apps.
• Companies overpay for frontier models on simple tasks.
• Product teams cannot clearly see which users/features burn compute.
• Latency increases because requests are not optimized.

[UnZip @Unzipfit]

The application is running perfectly, but we also need to improve it and add more features. Here's what we'll be adding:
• Routes/Policy Engine — Auto-select model based on cost/latency/complexity, plus a Routes page in the dashboard.
• Cache Page — Explore and delete cache entries individually + view cluster prompts.
• Advanced Cost Profiler — Cost breakdown per route/per user, and a list of the most expensive prompts.
• Streaming Response — Responses stream token-by-token (like ChatGPT typing).
• Public /v1/embeddings Endpoint — Open embeddings for direct use via the API.

[UnZip @Unzipfit]

DEXSCREENER UPDATED : https://t.co/rkQugl80at

[UnZip @Unzipfit]

CA $UNZIP : EuMD8NdJzD7BYEk2kBMRhGBhBVR11EyJDJfzxW5upump https://t.co/E1R38pTO8F

[UnZip @Unzipfit]

🔐 Just locked 110,311,909 $UNZIP tokens with @Streamflow_Fi
It's on-chain. You can check the amount, time-period and recipients.

Check it out👇
https://t.co/63oYbbYdss

[UnZip @Unzipfit]

UnZip is a compute compression layer for AI applications. It sits between an application and AI model providers, then reduces inference cost, token usage, latency, and redundant compute without requiring the developer to rewrite their product.

• Most AI applications waste compute in predictable ways:
• repeated or semantically similar requests are recomputed from zero
• small tasks are sent to expensive frontier models
• prompts and context windows are bloated
• providers are selected statically instead of by real-time cost/performance
• retries and fallbacks are inefficient;
• teams lack visibility into cost per feature, user, route, or workflow.

UnZip solves this by providing a drop-in gateway, SDK, and dashboard that automatically applies semantic caching, model routing, prompt compression, context pruning, batching, fallback, cost profiling, and quality checks.

https://t.co/mKldNhRJ0u

[UnZip @Unzipfit]

Hi world