Sipp Commercial gives teams a managed backend for hybrid AI. Run inference on-device, route requests through a secure gateway, manage and fine-tune models, and reserve dedicated single-tenant capacity through the same client you already use locally.
Built for teams that need clear control over where inference runs, where data lives, and which systems are allowed to see sensitive context.
Onboarding early-access design partners before general availability.
Host, version, fine-tune, and observe your model fleet from one console, with LoRA support and built-in vector memory.
Keep keys and data server-side with PII stripping, caching, routing, fallbacks, and rate limits before requests reach a provider.
Run your weights on dedicated, single-tenant GPU and accelerator clusters for predictable, high-throughput workloads.
Sipp turns the hard parts of deployment into managed infrastructure your team can control.
The challenge
Prompts, documents, and proprietary context often move through shared clouds, provider APIs, and client apps without a clear control boundary.
With Sipp Commercial
Run inference on-device when data should stay local, strip PII before cloud handoff, and use single-tenant capacity for sensitive workloads.
The challenge
Versioning, latency, token spend, and behavior drift become difficult to manage across providers, environments, and customer deployments.
With Sipp Commercial
Host, version, fine-tune, and monitor models from one console, with visibility into TTFT, ITL, and per-tenant token usage.
The challenge
Embedding provider keys in clients and writing custom fallback logic creates avoidable security risks and brittle traffic paths.
With Sipp Commercial
Keep credentials server-side, cache repeat work, enforce token-aware limits, and route traffic across local, hosted, and provider models.
The challenge
On-demand inference can create cold starts, noisy-neighbor latency, and usage spikes that are difficult to plan around.
With Sipp Commercial
Use dedicated single-tenant clusters for steady production traffic, then blend in provider inference when elastic capacity makes sense.
Keep the client you run locally. Point it at the gateway, then route work to on-device inference, managed models, provider APIs, or your dedicated cluster without rewriting your app.
Your app
Sipp client
Secure gateway
Keys · cache · routing
Managed models
Dedicated capacity
import { Sipp } from "@sipp/sipp";
const sipp = new Sipp();
// Local, on-device inference. Available today
sipp.add({ kind: "local", model: "llama-3.2" });
// Managed gateway and dedicated capacity. Sipp Commercial
sipp.add({ kind: "gateway", url: "https://your-team.sipp.ai" });
const reply = await sipp.chat("Summarize this contract…");import { Sipp } from "@sipp/sipp";
const sipp = new Sipp();
// Local, on-device inference. Available today
sipp.add({ kind: "local", model: "llama-3.2" });
// Managed gateway and dedicated capacity. Sipp Commercial
sipp.add({ kind: "gateway", url: "https://your-team.sipp.ai" });
const reply = await sipp.chat("Summarize this contract…");Illustrative. The local runtime is open-source and available today. Gateway, model management, and dedicated capacity ship with Sipp Commercial.
Start with the layer you need, then add more as your AI workload moves from prototype to production.
A managed backend for hosting, fine-tuning, and monitoring your model fleet without building an internal MLOps platform.
Managed hosting and versioning
Deploy and hot-swap base models across pools, with version history and zero-downtime rollouts.
LoRA fine-tuning and steering
Train and hot-swap lightweight LoRA adapters to tune behavior by user, organization, or context.
Vector memory
Use built-in embeddings and retrieval so application context can live close to inference.
Telemetry and observability
Track TTFT, ITL, and per-tenant token consumption across production workloads.
A deployable gateway for secure, cache-aware routing across local models, provider APIs, and Sipp-managed infrastructure.
Secure key custody
Store, rotate, and scope provider credentials behind the gateway instead of shipping them in client apps.
Privacy-preserving routing
Strip and tokenize PII locally before any cloud handoff, keeping sensitive context under your control.
KV and vector caching
Serve repeated prompts, context, and retrieval work from cache before calling expensive upstream models.
Intelligent routing
Route requests between fast local models, hosted models, and deeper reasoning endpoints based on policy.
Token-aware rate limiting
Protect downstream clusters from runaway loops, abuse, and surprise usage spikes.
Dedicated, single-tenant infrastructure for running proprietary and open-weight models with predictable performance.
Custom and MoE model hosting
Run large Mixture-of-Experts and custom architectures on infrastructure tuned for your workload.
Hybrid provider and instance inference
Blend dedicated capacity with provider routing through the gateway for elastic, cost-aware execution.
Reserved capacity
Reduce cold starts and noisy-neighbor risk with isolated clusters dedicated to your models and traffic.
Symmetric with the SDK
Use the same Sipp client for local WebGPU inference and remote execution on your dedicated cluster.
Sipp is founded by University of Waterloo PhDs in Computer Science. Sipp Commercial builds on their research into hybrid edge-to-cloud inference, including real-time LoRA steering, privacy-preserving routing, and compressed grammars for efficient front-end and back-end models.
We are opening academic and applied research partnerships around joint training and efficient model grammars. If that is your domain, we would like to work with you.
Foundations and memory
Core acceleration, local vector RAG, and a persistent gateway dashboard with traffic shaping.
Persistence and interception
Gateway-level KV and vector caching, plus a cloud control plane for model and LoRA management.
Commercial fleet and research
Managed bare-metal clusters, enterprise observability, and compressed-grammar research for co-trained front-end and back-end models.
We are onboarding a first cohort of design partners for model management, the inference gateway, and dedicated capacity. Add your work email and we will reach out as space opens.
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