Snapshot
Continue to About ↓- What it does
- A production LLM inference platform built on the open-source vLLM engine, deployable in the customer's own cloud or datacenter (BYOC) or on GPUs provisioned by Inferact (Inferact Cloud).
More detail
- It adds autoscaling, authenticated endpoints, metering, observability, day-zero optimized model support, custom kernels, forward-deployed vLLM engineers, and security/governance controls.
- Best for
- AI labs, enterprises, and agentic/RL workload teams that want turnkey, optimized production inference for open-weight models while keeping their weights, prompts, and logs in their own environment or on Inferact-provisioned GPUs.
- Pricing
- No public pricing is disclosed.
More detail
- Commercial terms require booking a meeting or contacting the company; costs are unknown.
- Main limitation
- Teams wanting only free open-source vLLM without a commercial platform, buyers requiring public list pricing or self-serve signup, teams needing hosted access to closed-weight proprietary models, and buyers requiring independently verified (non-first-party) performance benchmarks.
- Record
- Living and monitored
- Reviewed
- Evidence
- Public web research
- Machine access
- Structured profile ↗
About
- A production LLM inference platform built on the open-source vLLM engine, deployable in the customer's own cloud or datacenter (BYOC) or on GPUs provisioned by Inferact (Inferact Cloud).
- It adds autoscaling, authenticated endpoints, metering, observability, day-zero optimized model support, custom kernels, forward-deployed vLLM engineers, and security/governance controls.
What it helps with
- Raw vLLM is not turnkey for production: Inferact layers autoscaling, authentication, metering, observability, and cost t
- Slow day-zero support for new models and hardware: Inferact claims model-lab partnerships so new frontier open models ru
- High inference cost: autoscaling releases idle GPUs, and custom kernels and speculators aim to improve tokens per dollar
- Data sovereignty concerns: BYOC and data residency controls keep weights, prompts, and logs in the customer's environmen
- Agentic and RL workloads need sustained performance for long-running sessions, long prefixes, and repeated tool calls.
Capabilities
A practical view of what is available and where limitations apply.
| Offering | Available | Detail |
|---|---|---|
| BYOC / self-hosted deployment | Yes | Inferact Platform runs in the customer's own cloud or datacenter. |
| Managed Inferact Cloud on provisioned GPUs | Yes | Inferact provisions GPUs for customers under Inferact Cloud. |
| Autoscaling | Yes | Scales compute up and down based on demand. |
| Authenticated endpoints, rate limits, token accounting, governance | Yes | Described as endpoints and metering capabilities. |
| Observability | Yes | Track throughput, latency, and cost per workload. |
| Day-zero optimized model support | Yes | First-party claim of optimized support for new frontier open models on launch day via model-lab partnerships. |
| Custom kernels and trained speculators | Yes | Includes TPU megakernels and in-platform tuning by the Inferact team. |
| Forward-deployed vLLM engineers | Yes | vLLM maintainers embedded with the customer from pilot through production. |
| SOC 2 compliance | Yes | Self-reported on the official site. |
| Data residency controls | Yes | Pin deployments to required regions and jurisdictions; specific regions are not disclosed. |
Bot trust
How confidently AI systems can verify this profile from public evidence.
—of 100
ChatGPT—/100
Claude—/100
This profile has not completed a Bot Score assessment yet.
Evidence
Where this record came from, when it was reviewed, and how confidently it can be used.
- Verification
- Scribble researched these facts from the linked public sources.
- The owner has not manually confirmed every field.
- Last reviewed
- Primary source
- inferact.ai
Technical profile details
Record ID
831d765b-fed6-4b01-b84c-b5b18f26ec66Canonical URLhttps://profiles.scribble.network/listing/inferact-platform-831d765b