VernaOne is the layer between your app and every LLM — a router in the request path, a versioned prompt registry, and cost + quality analytics in one. One tool instead of five. And because it sits in the path, it doesn’t just show you the bill — it lowers it.
One API in the request path in front of every model and tool you already use
The whitespace
Teams buy a gateway to route, an observability tool to watch, and a prompt store to remember — three products that don’t overlap. The intersection is nearly empty. That’s where VernaOne lives.
In the path, but blind
Watching, but powerless
In the path AND the source of truth
Gateways are in the path but blind. Observability tools watch but can’t act. VernaOne is in the request path and the source of truth — so it can route, remember, and observe in one call.
Active cost control
Cost control on your LLM usage is only possible from inside the request path. Observability tools sit beside it — they can attribute spend, never reduce it.
Passive. After the fact.
In the path. Acts on every call.
Cost routing is gated by your eval checks — a call only drops to a cheaper model if it still passes. Cost and quality are decided together, in the same request, so lowering spend never quietly lowers quality.
The data behind it
Routing to the cheapest model that still passes your checks only works if something knows what everything costs, today. That is a live index of 1502 models from 86 companies, rebuilt every day and read straight from the sellers.
Read from source, every day.
In the request path, not in a report.
We sell a router, and the index still lists the routers we compete with. It has to: an index that quietly omits a seller is not an index. Prices are published with the evidence behind them, disagreements between sources are shown rather than resolved in our favour, and where we cannot verify something we say so. Last rebuilt 2026-09-11.
The whole platform
Author, version, route, and observe prompts as model-agnostic endpoints. Not just a gateway — LLMs, media, live search, and scraping through one API.
One API across OpenAI, Anthropic, Google, xAI, DeepSeek, Mistral, Groq, Cohere and Perplexity. Because it sits between your app and the model, it can act on every call — not just log it.
Every prompt a named, model-agnostic endpoint with templated inputs, an output contract, and one-click promote/rollback. The source of truth the observability tools only watch.
An outage, rate limit, or price hike fails over to the next best model — no code change, no paged engineer.
Lossless JSON compaction cuts 28–49% of input tokens on data-heavy prompts. Real spend, gone.
Cost, latency, success and eval checks per prompt version — the reporting layer, built in.
Web search, scraping, and image/audio/video/music routing behind the same one call.
Consolidation
Most teams shipping LLM features stitch four tools that don’t know about each other. VernaOne is all of them — and the only one in the request path.
One API
Call a named prompt and VernaOne routes it — to an LLM, a media model, live web search, or a web scraper — with automatic fallback across providers, all from inside the request path.
Compare & choose
Pick your models, hit run, and see each one’s output, latency, and cost side by side. Choose the winner with hard data — then promote it to the versioned endpoint your app already calls.
Free tools
Single-purpose, no signup. Great on their own — and a taste of the platform.
Paste a prompt, get an instant portability score and every provider-lock-in issue.
interactiveCompare monthly cost across providers and see fallback + compression savings.
copy-paste promptAudit any prompt for lock-in and token waste; get a model-agnostic rewrite.
Route, version, and observe every LLM call from one place — free to start, bring your own keys.
Launch VernaOne →VernaOne is the runtime layer between your app and every LLM. It combines three things teams normally buy separately: a multi-provider router that sits in the request path (routing, fallback, cost control), a versioned prompt registry (prompts as named, model-agnostic endpoints), and cost + quality analytics on top. One tool instead of five.
Those tools each cover one layer. Gateways like Helicone, Portkey and LiteLLM sit in the request path and route, but have no prompt registry or studio. Observability and eval tools like Langfuse, LangSmith and Braintrust watch your calls after the fact — they can report cost, but they are not in the request path, so they cannot act on it. VernaOne is in the path AND the source of truth: it routes, remembers, and observes in one place.
Because it runs in the request path, it can act on cost, not just report it: route each call to the cheapest model that passes your quality checks, fail over automatically instead of paying premium retries, compress input tokens losslessly (28–49% on data-heavy prompts), and reuse cache/dedup hits. Observability tools can only show you the bill after it is spent.
No — routing is gated by your eval checks. VernaOne only moves a call to a cheaper model if it passes the checks you set, so you get cheaper without getting worse. Cost and quality are decided together, in the same request.
OpenAI, Anthropic, Google, xAI, DeepSeek, Mistral, Groq, Cohere and Perplexity, plus OpenRouter — behind one API. It also reaches media models (fal, Replicate, Mureka) and tools (Tavily search, Scrappey scraping). You call a named prompt; VernaOne routes it and falls back across providers on failure.
Yes — a free tier and a free desktop app. Bring your own provider keys and routing is free, with a monthly execution allowance on every plan. There are also free tools like the Prompt Auditor, Portability Linter, and Cost Calculator, with no signup.