PromptUnit

What is PromptUnit?

PromptUnit is an AI inference proxy that automatically routes API requests to the cheapest capable model while keeping output quality stable. Teams swap one base URL and gain smart routing, prompt compression, token inflation detection, and live cost analytics without touching their application code.

Top Features:

• Smart provider routing: dispatches requests across OpenAI, Anthropic, Google, Groq, and DeepSeek automatically.
• Prompt compression: uses TF-IDF to shrink token counts before billing kicks in.
• Token inflation guard: detects and blocks suspicious bloating before requests hit paid providers.
• Live cost dashboard: tracks spend by feature, user, and route in real time clearly.

Use Cases:

• Reducing GPT-4 overuse: shift simpler tasks to cheaper models without rewriting prompts manually.
• Spend visibility: attribute LLM costs to individual product features and customer accounts cleanly.
• Failover protection: route around provider outages automatically without paging engineers at night.
• Pre routing observation: watch traffic for 14 days before enabling routing to set baselines.

Who Can Use PromptUnit?

• AI product engineers: shipping features that hammer expensive LLM APIs at large scale.
• FinOps teams: chasing line item visibility into LLM bills across many internal teams.
• Startup CTOs: hunting for quick wins on burn rate without slowing product velocity.
• Platform engineers: centralizing model access policy across multiple internal applications quickly.

Pricing

• Free observation (14 days): traffic logging and analytics with no routing and no charges.
• Performance based (20% of savings): you only pay when the proxy provably cuts your LLM spend.
• Enterprise (custom): tailored support, contracts, and integrations for large production AI workloads.

Pros and Cons

Pros:

• One line integration: change the base URL and existing code keeps working without edits.
• Aligned incentives: billing only on real savings means you never pay for nothing.
• Provider coverage: works across the major LLM vendors so vendor lock in stays low.

Cons:

• Proxy dependency: all production traffic flows through PromptUnit, adding one extra failure point.
• Routing for simple stacks: single model apps see less benefit than diverse production workloads.
• Savings vary: the 20% fee depends on real reductions that PromptUnit can actually deliver.

FAQs:

1) How do I integrate PromptUnit?

You change the base URL of your existing OpenAI compatible client to point at PromptUnit.

2) Which providers does it support?

It currently routes across OpenAI, Anthropic, Google, Groq, and DeepSeek in production today.

3) When do I get billed?

PromptUnit charges 20% of provable savings, so flat usage with no savings means no bill.

4) What does prompt compression do?

It uses TF-IDF analysis to trim redundant tokens before forwarding requests to the chosen provider.

5) Is there a free trial?

Yes, a 14 day observation period logs traffic without routing or any charges to your account.