On-demand GPU clusters, serverless inference, and full-stack observability — from one API.
<60s
To first GPU
<10ms
Global p99 TTFT
Global
Edge coverage
CogniCloud provides the full stack of infrastructure primitives your AI applications need — from raw compute to production-grade serving.
Compute
NVIDIA's latest datacenter GPUs connected via NVLink at 3.35 TB/s chip-to-chip bandwidth. Up to 80 GB HBM2e VRAM per accelerator, multi-node topologies on request.
Inference
Deploy any open-source LLM — Llama 3, Mistral, Qwen — with a single API call. OpenAI-compatible endpoints, auto-scales to zero, bursts to thousands of replicas in milliseconds.
Caching
Hierarchical key-value cache for transformer attention. Reuse identical prompt prefixes across requests, slashing compute costs by up to 80% on chatbot-style workloads.
Network
Globally distributed points of presence. Anycast routing ensures user requests hit the nearest available GPU cluster, delivering sub-10 ms time-to-first-token worldwide.
Observability
Per-request GPU utilisation, token throughput, latency percentiles, and cost attribution streamed live. OpenTelemetry-compatible — plug straight into Grafana, Datadog, or your own stack.
DevOps
Define your entire AI stack in a single YAML manifest. GitOps-friendly: every deployment is versioned, diffable, and rollback-safe. Terraform and Pulumi providers coming soon.
<10ms
p99 inference latency
time-to-first-token
99.99%
uptime SLA
contractually guaranteed
Global
edge coverage
multi-region
3.35 TB/s
NVLink bandwidth
per 8-GPU node
Push model weights from Hugging Face, S3, or a private registry. CogniCloud auto-detects the architecture, provisions the right GPU SKU, and builds a containerised serving environment — no Dockerfile required.
cogni deploy \
--model meta-llama/Llama-3-70b-instruct \
--gpu high-perf --replicas 2Set a concurrency target or a latency SLO. CogniCloud's scheduler monitors live traffic and provisions or releases GPU capacity in real-time, with cold-start times under 2 seconds.
scaling:
metric: concurrency
target: 10
min_replicas: 0
max_replicas: 100Every token generated, every GPU cycle consumed, and every millisecond of latency flows into your observability stack via OpenTelemetry. Native integrations for Grafana, Datadog, and Prometheus.
GET /v1/metrics/inference
{
"p50_ttft_ms": 4.2,
"p99_ttft_ms": 8.9,
"tokens_per_second": 1840,
"gpu_utilisation": 0.94
}From research prototypes to production workloads serving millions of users — CogniCloud scales with you at every stage.
Fine-tune Llama 3, Mistral, or custom transformer architectures on multi-node GPU clusters. Gradient checkpointing, mixed precision, and distributed strategies managed automatically.
Serve any open-source or custom model via OpenAI-compatible REST and streaming endpoints. Continuous batching, speculative decoding, and tensor parallelism built-in.
Build production RAG pipelines with embedded vector search, hybrid BM25 + dense retrieval, and sub-millisecond nearest-neighbour lookup at billion-vector scale.
Process millions of records cost-effectively with GPU batch jobs. Automatic checkpointing, spot-instance fallback, and per-token cost tracking for tight budget control.
CogniCloud is in active development. We're a new company building something ambitious — here's our honest roadmap. No pricing yet; we'll work with each team to find the right fit.
On-demand high-performance GPU clusters with NVLink, provisioned in under 60 seconds. Supports single-node and multi-node distributed workloads.
OpenAI-compatible endpoints for any open-source LLM. Continuous batching, speculative decoding, and auto-scaling to zero included out of the box.
High-performance vector database built for billion-scale embedding retrieval. Hybrid BM25 + dense search, HNSW indexing, and real-time upserts.
Versioned artifact storage for model weights, configs, and evaluation results. Git-style lineage tracking, diff views, and one-click promotion to serving.
End-to-end training orchestration with experiment tracking, hyperparameter optimisation, and automated evaluation gates before production promotion.
Unified control plane across AWS, GCP, and Azure GPU capacity. Intelligent workload placement based on real-time spot pricing and availability.
CogniCloud is in active development. Join the waitlist to get early access and stay updated on our roadmap. No pricing yet — we'll work with each team to find the right fit.
No spam. No pricing pitches. We reach out personally to discuss your use case.