Unified OpenAI-compatible endpoint
Applications can use an AlphaProxy base URL and the model value "auto" or a supported model name instead of maintaining separate provider integrations.
AlphaProxy
Freemium
AlphaProxy é um gateway compatível com OpenAI que encaminha solicitações entre mais de 450 modelos e 100 provedores, com um runtime de agentes para trabalhos em várias etapas e fluxos agendados. Um único endpoint oferece acesso a modelos, ferramentas conectadas e resultados verificáveis.
O que é AlphaProxy?
AlphaProxy is an OpenAI-compatible gateway that provides one API key and endpoint for access to 450+ models from 100+ providers. It routes requests according to task requirements such as quality, latency, cost, model capability, host health, and fallback availability.
Beyond model access, AlphaProxy runs multi-step agent tasks and scheduled workflows. Its decision layer classifies requests before generation, while the runtime can coordinate tools, sandboxes, files, browsers, connected sources, and verification checks for work that needs more than a single model response.
O que AlphaProxy pode fazer?
Task-aware model routing
The decision layer classifies each request and selects a model, provider host, and fallback chain per call. Routing can account for quality, cost, latency, and provider health.
Non-generative decision layer
Requests are evaluated before generation for concerns such as safety, routing, memory, artifact intent, delegation, completion, and sandbox preparation. The site reports typical decision latency of about 300ms and zero generated tokens for this step.
Multi-agent execution
Complex tasks can be divided among ephemeral specialist agents that run in parallel with isolated sandboxes, shared context, and task-appropriate models. A completion gate checks the merged result before delivery.
Workflow automation
Users can describe recurring work and attach schedules, connected sources, guardrails, budget caps, retry policies, delivery destinations, and per-run logs.
Files, tools, and connected workspaces
The platform supports agent-ready work involving browsers, files, sandboxes, and connected tools. Changelog material also documents model discovery, skills preparation, file processing, and generated report, sheet, slide, and app outputs.
Casos de uso
“Research and competitive analysis”
Ask the runtime to compare competitors or build a market map. The documented examples describe specialist research, analysis, sourced materials, and deliverables such as reports or spreadsheets.
“Software investigation and delivery”
An agent workflow can inspect a repository, reproduce a regression in a sandbox, propose or create a fix, and use completion checks such as tests or CI status before reporting the result.
“Multi-step product or infrastructure work”
Users can describe a larger goal, such as specifying a token model and preparing a testnet, then let the runtime plan sequential steps involving research, coding, browser access, and verification.
“Recurring operations reporting”
A scheduled workflow can combine information from connected documents and spreadsheets, produce a weekly report or presentation, deliver it through email or Slack, and retain a run trace with cost and model status.
“Model evaluation and selection”
Teams can compare many models against an evaluation set and use routing or pinned model controls to select an option that meets their quality and cost requirements.
Perguntas frequentes
How does AlphaProxy connect to applications?
AlphaProxy presents an OpenAI-compatible endpoint. The site shows replacing a provider base URL with the AlphaProxy API base URL and using "auto" or a model name, so existing OpenAI-compatible integrations can be adapted without changing the core application flow.
Does AlphaProxy always generate text for a request?
No. Every request first passes through a non-generative decision layer that classifies, scores, and routes it. Generation is used when a produced artifact or response is required; the site reports about 300ms typical decision latency and zero generated tokens for that decision step.
Can AlphaProxy run multi-step or multi-agent tasks?
Yes. The documented runtime can create ephemeral specialist agents, run independent work in parallel, provide isolated sandboxes and shared context, and check the merged result before delivery.
Can workflows run on a schedule?
Yes. The site describes durable scheduled jobs with connected sources, model policies, guardrails, budget caps, retry policies, delivery destinations, and per-run logs. A weekly report assembled from documents and spreadsheets is given as an example.
Is pricing publicly documented?
No pricing tiers, rates, usage limits, or billing terms are provided in the supplied product pages. The pricing URL returned a not-found page, so prospective users would need current product information from AlphaProxy.
Informações rápidas
- Category
- AI model gateway and agent platform
- Access model
- One API key and OpenAI-compatible endpoint
- Model coverage
- 450+ models and 100+ providers
- Decision layer
- Typical latency of about 300ms; zero generated tokens for the decision step
- Workflow support
- Multi-agent tasks, scheduled automations, files, browsers, sandboxes, and connected tools
- Operator
- Alpha Proxy Corporation; developed by Alpha Labs
Análise de tráfego de AlphaProxy
Os dados de tráfego são apenas para referência.
- Classificação do domínio
- 0
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