Serve
Deploy REST and gRPC inference endpoints with autoscaling, batching and streaming support for LLM serving and real-time AI workloads across hybrid cloud environments.
Production inference · BN on file · Toronto
INFERENCEAI · TORONTO
Infer I1 — 2026
Production inference at scale — real-time ML serving, LLM endpoints and edge AI infrastructure built for Canadian enterprises.
Real-time ML inference, LLM serving endpoints and edge AI infrastructure for Canadian enterprises — low-latency, production-grade and responsibly governed.
INFERENCE MANIFESTO
We architect production inference systems — not campaigns, not websites, not helpdesk tickets.
InferenceAI exists because machine learning models only create value when they serve predictions reliably under real-world load. Our platform engineers model deployment pipelines, GPU orchestration layers, latency-aware routing and observability stacks that keep neural networks, large language models and computer vision endpoints running in production across Canadian enterprise environments.
From our studio on the Eglinton corridor in Midtown Toronto, we partner with ML engineers, platform architects and DevOps leads who need measurable throughput, responsible governance and infrastructure that scales without sacrificing inference quality. We design real-time AI endpoints, edge AI serving paths and NLP model pipelines — applied artificial intelligence infrastructure with engineering rigour.
We are an AI inference platform. We do not operate as a marketing agency, web design studio or general IT outsourcing firm. Every engagement centres on model serving, production ML operations and scalable AI infrastructure — the substance of modern artificial intelligence deployment, not peripheral services.
8ms
Median p50 latency
2.4B+
Daily inference calls
99.97%
Platform uptime SLA
SIX INFERENCE PILLARS
Serve S3
Node N2
Infer I1
Serve S3
Node N2
Infer I1
End-to-end model serving capability
Scale
GPU orchestration and horizontal pod autoscaling tuned for neural network inference peaks — from burst traffic to sustained generative AI demand without idle capacity waste.
Monitor
Production inference monitoring with latency histograms, drift detection, token throughput dashboards and alerting aligned to ML operations best practices.
Optimise
Quantisation, kernel fusion and latency optimisation sprints that reduce p99 response times while preserving model accuracy for computer vision and NLP models.
Govern
Responsible AI controls including audit trails, PIPEDA-aligned data handling, model versioning and access policies for regulated Canadian corporate markets.
Deploy
Blue-green model serving cutovers, canary releases and edge AI deployment tracks that move models from sandbox to production with minimal downtime risk.
STACK ARCHITECTURE
From model artefact to production endpoint
Our inference pipeline connects model artefacts to scalable endpoints through orchestrated GPU pools, intelligent request routing and continuous production ML monitoring — the backbone of enterprise AI automation.
OPERATIONS CENTRE
GPU orchestration under real production load
Canadian enterprises running generative AI and machine learning at scale need visibility into GPU utilisation, queue depth and token throughput. Our platform surfaces the metrics that matter for latency optimisation and capacity planning — not vanity dashboards disconnected from inference reality.
Whether you operate LLM serving clusters or computer vision inference at the edge, InferenceAI integrates observability into every deployment sprint so your AI infrastructure team can act before SLA breaches occur.
INFERENCE DASHBOARD
Production-grade monitoring for every endpoint
Track p50 and p99 latency, error rates, model version drift and request volume across all scalable AI endpoints from a unified operations view. Built for platform engineering teams who treat inference monitoring as a first-class discipline, not an afterthought bolted onto deployment day.
Explore observability services
PROGRAMME PREVIEW
INF-101
INF-201
INF-601
Structured paths from pilot to production certification
Real-Time Inference Foundations
Core model serving concepts, endpoint design and latency-aware architecture for teams entering production ML. From C$4,200.
View module →LLM Serving & Endpoint Design
Token streaming, batching strategies and generative AI endpoint patterns for large language models. From C$5,800.
View module →Production Inference Certification
Capstone validation of deploy, govern and monitor competencies across your inference stack. From C$9,400.
View module →
FREQUENTLY ASKED
Platform clarity before you engage
Is InferenceAI a marketing agency, web design studio or IT outsourcing firm?
No. InferenceAI is an AI inference platform providing model serving, GPU orchestration and production ML endpoint infrastructure. We do not offer marketing campaigns, website design services or general IT helpdesk support.
Does InferenceAI guarantee zero-latency inference or fully autonomous deployments?
No. Our platform accelerates inference architecture — outcomes depend on infrastructure, model size and workload patterns. Human oversight and exception handling remain essential.
Where is data processed for Canadian clients?
We prioritise Canadian and North American data residency options aligned with PIPEDA requirements. Specific hosting regions are confirmed during architecture review.
What GPU platforms do you support?
Our orchestration layer integrates with major cloud GPU offerings and on-premise NVIDIA clusters. Compatibility is validated during the pilot programme intake.
How long does a typical pilot take?
Most pilot programmes run four to eight weeks from sandbox provisioning through first production endpoint, depending on model complexity and integration scope.
What are your support hours?
Platform support is available Monday to Friday, 09:00–17:00 Eastern Time. Critical production incidents receive escalation per your service agreement.
Ready to architect your inference stack?
Book a briefing with our Toronto platform team and map your path from model artefact to production endpoint.
Request an inference briefing