Oxlo.ai.

Oxlo.ai

Oxlo.ai is a privacy-first AI inference API that delivers frontier-class performance at predictable, request-based pricing. Unlike traditional token-based providers, Oxlo.ai charges a flat monthly fee per API call regardless of prompt length, making it the most cost-effective solution for teams running long-context workloads, agentic applications, and production AI systems at scale.

Product Highlights

• Request-Based Pricing: Pay a flat monthly rate per API call instead of unpredictable per-token costs, eliminating billing surprises as your usage scales
• Frontier Model Access: Run Kimi K2.6, DeepSeek V4 Flash, Llama 3.3 70B, Qwen 3 32B, and 40+ open-source models with performance matching or exceeding GPT-5.4 and Claude Opus 4.6
• Privacy-First Architecture: Zero data retention, zero training on your prompts, and complete data sovereignty with secure failover infrastructure
• Unlimited Agentic Tool Calls: Build sophisticated AI agents with unrestricted function calling, MCP compatibility, and production-ready reliability
• OpenAI SDK Compatible: Switch providers by changing one line of code—fully compatible with existing OpenAI Python and Node.js integrations

Use Cases

• Chatbots & AI Assistants: Deploy customer support bots, internal copilots, and workflow automation with predictable infrastructure costs
• Document Q&A and RAG: Power retrieval-augmented generation systems for enterprise knowledge bases, legal document analysis, and research workflows without token-cost anxiety
• Long-Context Processing: Process extensive documents, codebases, and multi-turn conversations where traditional per-token pricing would be prohibitively expensive
• Batch AI Processing: Run high-volume inference jobs, async workflows, and data processing pipelines with flat-rate cost structures
• Multimodal Applications: Build vision, speech, and audio AI features including image understanding, transcription, text-to-speech, and object detection

Target Audience

Oxlo.ai serves engineering teams, AI startups, and enterprise developers who need production-grade inference infrastructure with completely predictable costs—particularly those building agentic systems, RAG applications, or any workload where long prompts and high token counts would explode budgets under traditional pricing models.