Understanding Inference
AI inference is the process of running trained machine learning models to generate predictions, classifications, or outputs from new input data. Unlike training—which is computationally intensive and happens offline—inference runs in real-time when users interact with your application.
Every time you use an AI assistant, generate an image, or get a recommendation—that's inference. It's the production phase of machine learning, where trained models deliver value to end users. The challenge is doing this at scale with low latency, high reliability, and cost efficiency.
Why It Matters
Real-time applications need sub-100ms response times. Delays degrade user experience and reduce engagement.
Production workloads can spike from hundreds to millions of requests. Infrastructure must scale instantly.
GPU compute is expensive. Efficient inference—through optimization and batching—directly impacts your margins.
AI is becoming mission-critical. Downtime isn't acceptable when businesses depend on inference.
SVECTOR Inference
SVECTOR provides inference infrastructure for every use case—from simple API calls to custom model deployments.
Access SVECTOR models instantly through our API. No infrastructure to manage—just integrate and start building.
Spec-3, Theta-35, and more—all via simple REST endpoints
Real-time streaming for chat, batch processing for offline work
Only pay for what you consume. Start free, scale as you grow
Under the Hood
SVECTOR BLACK — Custom inference framework for maximum throughput and minimum latency.
Global Network — Inference runs close to your users with points of presence worldwide.
Auto-Scaling — Scale automatically based on traffic. Scale to zero when idle.
Optimization — Quantization and distillation for faster inference.
Available Models
Access our complete model portfolio via API—from foundation models to specialized systems.
General-purpose language models for text, reasoning, and code.
Advanced models for complex multi-step reasoning.
Models that understand images and combine modalities.
99.8%
Uptime SLA
<300ms
P50 Latency
Global
Edge Distribution
1.1M+
Daily Requests
Use Cases
Build conversational interfaces for support, internal tools, or products.
Integrate AI into developer tools for code completion and debugging.
Generate marketing copy, descriptions, and creative content at scale.
Extract and analyze information from documents, PDFs, and images.
Run AI analysis on datasets for insights and pattern recognition.
Build AI agents that can reason, plan, and take actions.
