Everything it does
One API for every model and tool.
VernaOne isn't just an LLM router. It's a prompt-centric API for LLMs, media generation, live web search, and web scraping — with fallback, compression, flows, agents, evals, and analytics. Here's the whole platform.
Try VernaOne free → ↓ Download desktop app
~15 providers & tools behind one API — LLMs, media, search & scraping
One API for every model — and tool
Call LLMs, media models, live web search, and web scraping through one consistent, prompt-centric API. Build the integration once; add any capability without new SDKs.
Provider-agnostic router
Call OpenAI, Anthropic, Google, OpenRouter, xAI, DeepSeek, Mistral, Groq, Cohere, and Perplexity through one API. Switch or blend providers without rewriting application code.
Live web search
Ground prompts in real-time results via Tavily (search, extract, map, crawl — a synthesized answer plus sourced results) and Perplexity. Same prompt API, no separate search integration.
Web scraping
Fetch and render any URL — even Cloudflare/CAPTCHA-protected pages — with Scrappey, and feed the content straight into a model. Scrape prices, weather, news, or docs on demand.
Media generation
Generate images, video, audio, and music through fal, Replicate, and Mureka using the same governed prompts and routing as your text models — with async submit/poll/cancel built in.
Embeddings
Create embeddings through the same project-scoped API and provider routing, for search, RAG, and clustering.
Unified response envelope
Text or media, sync or async, every execution returns the same predictable shape. Handle any model or tool exactly the same way.
Prompt registry
Every prompt is a governed, versioned, named endpoint — not a string scattered across your code.
Versioned registry
Each change is an immutable version you can review, compare, and roll back to. Ship prompt updates with the confidence of a software release.
Activate & roll back
Promote any version to active with a click and roll back instantly if it underperforms. Production always points at the exact version you choose.
Typed input parameters
Declare {{variables}} with types and required flags so every call is validated before it reaches a model — catch bad inputs before you pay for a failed generation.
Structured JSON output
Ask for clean, parsed JSON and get structured objects back, with an optional schema to steer the model. Delete brittle string-parsing glue.
Enforce JSON structure
When a model truncates its answer, VernaOne repairs the JSON and hands your code a valid object instead of an error — every repair flagged so you can tune token budgets.
Lifecycle controls
Gate execution with active, paused, and inactive states so only approved prompts run. Pause a misbehaving prompt in seconds without losing history.
Resilience & optimization
Stay up, stay cheap. Fallback across providers, and cut tokens automatically.
Model fallback & retries
Define a primary plus an ordered list of fallbacks so an outage or rate limit fails over to the next best option — your users keep getting answers.
Lossless token compression
Large JSON inputs are losslessly compacted (columnar form) before they reach the model — typically 28–49% fewer input tokens on data-heavy prompts, with no data loss.
Output shaping
Trim preamble and restated input on prompts where terse output is fine, cutting output tokens without changing the answer.
Prompt-cache alignment & cache-hit analytics
Stabilize the prompt prefix so providers can cache it across fallback retries and comparisons, and see your cache-hit potential in analytics.
Per-request options
Override temperature, max tokens, seed, and reasoning effort on any individual call — no prompt edit or redeploy.
Flows & agents
Chain prompts and tools into pipelines and governed agent loops — no orchestration code.
Visual flow builder
Chain prompts into multi-step pipelines on a visual canvas. Compose sophisticated AI workflows entirely from your existing, governed prompts.
Composable steps
Build flows from prompt, parallel, map, and transform steps — run work in sequence, concurrently, or across arrays with fan-out and data shaping built in.
Flow versioning & run tracing
Version flows like prompts and watch every run with step-level status, retries, and configurable error policies.
Agentic tool-callingPreview
Let a model call tools — web search, web scrape, HTTP request, and your own prompts — inside a governed, provider-agnostic agent loop with cost and iteration caps.
Quality & observability
Know what happened, catch regressions, and prove ROI.
Multi-model compare
Submit a prompt once and run it across many models in parallel to compare quality, speed, and cost side by side — choose the winner with hard data.
Automated eval rules
Attach checks — schema match, contains, regex, length — that grade every output pass or fail, catching regressions before customers notice.
Scenarios
Capture every iteration of a prompt as a reusable test workspace with its inputs and saved outputs. Turn ad-hoc experiments into a repeatable record.
Interactions explorer
Inspect a searchable history of every execution — inputs, outputs, model, cost, latency, errors. Audit exactly what happened, when, and why.
Cost & usage analytics
Track spend, latency, and quality across prompts, models, and projects over time. Spot expensive prompts and silent regressions early.
Lab Assistant
AI that helps you write and improve prompts — never start from a blank editor.
Compose with AI
Describe the task and get a working, model-tuned prompt drafted for you, complete with rationale.
Optimize & cohort tuning
Rewrite a prompt to perform better on one model — or across a whole cohort of models at once.
Refine, Coach & Explain
Make surgical edits, get best-practice feedback, and get plain-language explanations of inherited prompts.
Variations & Translate
Generate multiple high-quality variations to test in parallel, and convert a prompt between provider styles.
Platform & developer experience
Multi-tenant, secure, and callable from your code by name.
Call prompts from code
Invoke any prompt by name over HTTP or the TypeScript SDK — your code never references a vendor SDK or a hardcoded model id. Ship prompt changes without redeploying.
Bring-your-own-key
Connect your own provider accounts and keys, stored encrypted and scoped to your project. Keep control of billing and rate limits.
Projects, roles & API keys
Isolate prompts, models, keys, and usage per project with environment scoping and team roles. Issue scoped x-api-keys for your apps and partners.
Interactive API docs
Explore and try every endpoint from built-in OpenAPI/Swagger docs. Onboard developers with live, always-accurate reference.
Free desktop app
The Postman for AI — test and compare prompts across models with your own keys, on macOS and Windows.
All of it, behind one prompt call.
Author a prompt once and call it by name — VernaOne handles the model, the tool, the fallback, and the cost. Free to start.
Launch VernaOne →Frequently asked
What can VernaOne do?
VernaOne is a prompt registry and multi-provider router — one API for LLMs, media generation, live web search, and web scraping. It gives you versioned model-agnostic prompt endpoints with automatic fallback across providers, lossless token compression, visual flows and agentic tool-calling, side-by-side model comparison, eval rules, cost analytics, a Lab Assistant, an SDK, and a free desktop app.
Does VernaOne support live web search?
Yes. VernaOne exposes live web search through Tavily (search, extract, map, and crawl — returning a synthesized answer plus sourced results) and Perplexity, callable through the same prompt-centric API as your models. You can ground a prompt in real-time web results without a separate search integration.
Can VernaOne scrape web pages?
Yes. VernaOne can fetch and render any URL — including Cloudflare/CAPTCHA-protected pages — via Scrappey, and feed the page content straight into a model. Useful for scraping prices, weather, news, or documentation on demand and using it as prompt input.
Does VernaOne support multi-step flows and agents?
Yes. The visual flow builder chains prompts into pipelines from prompt, parallel, map, and transform steps, with versioning and run tracing. Agentic tool-calling (models calling web search, web scrape, HTTP request, and your own prompts in a governed loop with cost and iteration caps) is in preview.
How does VernaOne reduce token cost?
It losslessly compacts large JSON inputs (columnar form) before they reach the model — typically 28–49% fewer input tokens on data-heavy prompts — plus output shaping and prompt-cache alignment, and automatic fallback to cheaper equivalent models.
Which providers does VernaOne support?
OpenAI, Anthropic, Google, OpenRouter, xAI, DeepSeek, Mistral, Groq, Cohere, and Perplexity for text; fal, Replicate, and Mureka for media; and Tavily and Scrappey for search and scraping — around 15 providers and tools behind one API.