Move fast, iterate daily — without a dedicated MLOps team.
Startups building AI products can't afford months of infrastructure work before shipping. CogniCloud is designed for teams that need to go from idea to production endpoint in a single afternoon, with no DevOps overhead, no minimum commitments, and pay-as-you-go pricing scaled to your actual usage.
14 s
From model ID to live endpoint
$0
Cost when traffic is zero
1 API
Covers training, serving & search
0
Minimum commitment
The Challenge
Most AI infrastructure platforms are built for enterprises: complex setup, multi-week onboarding, minimum spend requirements, and pricing opacity. Startups need GPU access, a serving layer, and a vector store without a three-month procurement process.
How CogniCloud helps
Point the CLI at any Hugging Face model ID. CogniCloud handles serving container builds, hardware selection, and autoscaling. No YAML manifests, no Kubernetes.
Pay nothing when users aren't active. Sub-2-second cold starts mean your users barely notice idle periods. Your burn rate tracks your revenue, not a fixed cluster.
Drop in the CogniCloud base URL and start using every open-source model through the same familiar OpenAI SDK you already know. Migration time: 30 seconds.
No ML infrastructure to maintain. CogniCloud handles capacity planning, hardware failures, CUDA version upgrades, and security patching — your team focuses on the product.
No seats, no tiers, no upfront commitments. Pay per GPU-second for training, per token for inference, per query for vector search. Transparent, predictable costs.
Design-partner startups get dedicated Slack support, architecture reviews, and direct access to the engineering team. We succeed when you succeed.
How it works
The CogniCloud CLI and SDK are available on npm and PyPI. API keys are created instantly in the dashboard.
# Install
npm install @cognicloud/sdk
pip install cognicloud
# Authenticate
$ cogni auth login
✓ Authenticated as team@acmecorp.ai
# Deploy a model
$ cogni deploy \
--model mistralai/Mistral-7B-Instruct-v0.3Use the same API you'd use with OpenAI. Swap models, enable streaming, set autoscale limits — all from one SDK.
// Works with your existing OpenAI code
const client = new OpenAI({
baseURL: "https://api.cognicloud.net/v1",
apiKey: process.env.COGNI_KEY,
});
// All open-source models available
const models = [
"meta-llama/Llama-3-70B-Instruct",
"mistralai/Mistral-7B-Instruct-v0.3",
"Qwen/Qwen2.5-72B-Instruct",
];When your traffic grows, CogniCloud scales automatically. Move to dedicated capacity with one CLI command when you need guaranteed performance.
# Autoscale policy
$ cogni autoscale set \
--min 0 \
--max 50 \
--target-latency-ms 50
# Promote to dedicated (one command)
$ cogni promote to-dedicated \
--replicas 4 \
--sla p99=10msBuilt on
Instant model endpoints — deploy any model in seconds
On-demand training and fine-tuning without idle costs
Add semantic search to your app without running a database
Reduces per-query cost so usage-based billing stays low
LLM Fine-Tuning
Adapt foundation models to your domain — faster and cheaper.
Production Inference
Serve any LLM to millions of users at sub-10 ms TTFT.
RAG Pipelines
Ground your LLMs in real knowledge at billion-document scale.
Enterprise AI
Secure, compliant, and governed AI infrastructure at any scale.
Batch & Offline AI
Process millions of records overnight — at the lowest cost per token.
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.