LLMs, GPU pods, and CPU jobs through a single key. Our routing engine decides the cheapest, fastest, most reliable provider for every request — using performance data your agents can't see on their own. Hard spend caps and idle auto-stop, built in.
Waitlist signups are onboarded into the private beta ahead of public launch.
Prices shift. Models update. Providers go down. Idle pods keep billing. Your agent doesn't know any of that. It calls whatever you hardcoded and hopes for the best.
Hypersave turns "which provider, which model, what limit" from a question you have to answer into a decision the platform makes for you, every request.
OpenAI-compatible endpoint for LLMs. Unified API for GPU pods and CPU jobs. One credential, one bill, one place to see what's running.
Your agent sends a request. We pick the provider and model that win on cost, latency, and reliability for that specific workload — using continuous benchmarking across every provider we support.
Every request comes back with what you paid, what it would have cost on each alternative provider, and why we routed it that way. The savings are on the dashboard, not in marketing copy.
Server-side spend caps that actually stop. Idle GPUs that actually shut down. Anomaly alerts when an agent loops. Prepaid credits so you can never be billed for more than you've loaded.
Get one API key. Add prepaid credits. Set your spend caps.
LLM calls, GPU jobs, CPU workloads — same key, same billing.
Our engine picks the best provider per request. You see the math, the savings, and every dollar in real time.
Today, every agent hardcodes a model and a provider. Tomorrow, that choice is stale — a cheaper model launched, the provider degraded, the price changed.
Hypersave gives your agent live decision data: which provider is winning on cost right now, which is winning on latency, which had an incident in the last hour. The agent calls one endpoint. We do the benchmarking, the failover, the math.
You load credits. We spend against them. You can't be charged for more than you've put in.
Spend limits live on our servers, not in your code. Even a runaway agent can't exceed your limit.
You see what each provider charges and what you pay. The math is on the dashboard.
We don't store prompts beyond what's needed for usage attribution, and you can delete logs anytime.
Sub-processor list, data-flow diagram, and DPA available for vendor security reviews. SOC 2 Type II preparation underway alongside public launch.
Volume commitments, named SLAs, dedicated support, and signed MSAs available for teams projecting $10K/month or above.
Hypersave passes upstream costs through transparently. The routing fee covers per-request decisioning, metering, dashboards, and spend protection. No subscriptions, no minimums, no commitments.
Cost of each upstream call (OpenAI, Anthropic, Together, DeepInfra, Groq, and more) plus a 5% routing fee. Volume tiers kick in above $5K/month.
Per-second metering across RunPod, Lambda, Vast, and hyperscaler GPU as partner enrolments complete. Idle auto-stop included.
Sandboxed CPU compute for non-GPU workloads. Per-second metering, same key, same bill.
Volume commitments, named SLAs, and dedicated support. Email partners@hypersave.ai for teams projecting $10K/month or above.
Private beta is live with select developers now. Public launch is scheduled for Q3 2026. Waitlist members are onboarded into the beta ahead of public access.
OpenRouter aggregates LLM APIs. Hypersave aggregates LLMs, GPU rental, and CPU compute under one key — with agent-native routing across all three and spend protection built in from day one.
You get one bill instead of five. A routing engine that picks the cheapest reliable option per request instead of hardcoding one provider forever. Hard spend caps providers don't offer. Idle auto-stop on GPUs.
Two things. First, the API surface is designed for autonomous callers — clear error semantics, predictable rate limits, no human-only auth flows. Second, our routing engine factors in what an agent can't see on its own: live provider performance, current pricing across vendors, recent reliability data. Your agent gets the right answer without having to gather the data.
Prepaid credits. You pay provider rates plus a small platform fee, fully visible on every request. No subscriptions, no minimums, no commitments.
At launch: OpenAI, Anthropic, Google (Vertex AI), Together, DeepInfra, and Groq for LLM inference. RunPod, Lambda Labs, and Vast for GPU pods. CPU compute across multiple providers. AWS, Azure, Google Cloud, and Oracle Cloud GPU + Bedrock/Foundry/Vertex/Generative AI integrations are rolling out as our partner enrolments complete. New providers added based on customer demand.
Yes. Standard OpenAI-compatible interface for LLM calls. Standard REST for compute. Leave anytime, take your data with you.
Yes. For teams projecting $10K/month or above, we offer volume commitments, named SLAs, dedicated support, and signed MSAs. Email partners@hypersave.ai with your projected workload to start a conversation.
We store the minimum data needed for usage attribution and billing. Customer prompts and outputs are not used to train any model. Sub-processor list, data-flow diagram, and DPA are available for vendor security reviews. SOC 2 Type II preparation is underway alongside public launch. Email security@hypersave.ai for the current documentation pack.
Hypersave operates as a unified broker. Wholesale partnerships with hyperscalers (AWS, Azure, Google Cloud, Oracle) are in active enrolment; specialty providers (RunPod, Lambda, Together, Groq, DeepInfra, and others) are integrated via their public APIs and partner programs. You always see what each provider charges and what you pay through Hypersave.
Waitlist members are onboarded into the private beta ahead of public launch — real pricing, real support, and direct input on the roadmap.