Claude family
Demanding reasoning and long-horizon agentic work.
Long-running agentic coding and knowledge work.
Balanced speed and intelligence for production.
High-volume, latency-sensitive classification and extraction.
BigOne routes LLM inference to the models that actually perform. Strategy, intelligent fallback cascades, latency optimization, and the deterministic audit governance to keep high-throughput pipelines active without vendor lock-in.
Connect the models your team already uses. BigOne keeps provider credentials behind one consistent API surface while routing each request toward the best available model.
Demanding reasoning and long-horizon agentic work.
Long-running agentic coding and knowledge work.
Balanced speed and intelligence for production.
High-volume, latency-sensitive classification and extraction.
Frontier reasoning and complex multi-step workflows.
General-purpose intelligence for production applications.
Fast, efficient inference for high-throughput workloads.
An AI router without a stated limit is a sales claim. These are the engineering boundaries we hold to on every millisecond of inference, written into SLA contracts before the first production key is provisioned.
| INDEX | CAPABILITY | WHAT IT COVERS | WHERE IT STOPS |
|---|---|---|---|
| 01 | Intelligent Model Routing | Real-time prompt complexity classification and semantic routing across Claude 3.5 Sonnet, GPT-4o, DeepSeek-R1, and local quantized OSS endpoints. Dynamically maximizes generation fidelity while slashing input/output compute fees by up to 74%. | WHERE IT STOPS We will not downgrade or reroute an SLA-critical prompt to a cheaper model tier unless that exact fallback condition was explicitly codified in your routing manifest. |
| 02 | Sub-15ms Fallback Cascades | Autonomous health checks tracking 9 global cloud inference providers simultaneously. When an upstream provider suffers rate limiting (HTTP 429), regional outages, or 504 gateway timeouts, requests cascade instantaneously without user disruption. | WHERE IT STOPS We do not retry failed payloads against unvetted mirror providers or geographical regions outside your pre-approved sovereign jurisdiction constraints. |
| 03 | Zero-Retention Enclave Proxy | True in-flight token stream forwarding. High-velocity regex & NER masking handles synthetic PII sanitization in memory buffers prior to provider handoff, with customer-managed AWS KMS and HashiCorp Vault key rotation. | WHERE IT STOPS We never persist, store, train on, or allow human telemetry access to raw prompt texts or generated completions under any contract tier. Zero disk writes for payloads. |
| 04 | Circuit-Breakers & Token Budgets | Hardware-enforced departmental cost containment. Set strict micro-quotas per environment (Dev, Staging, Production), track velocity per minute, and execute automated rate limiting before unexpected rogue loops generate catastrophic billing. | WHERE IT STOPS We will never abruptly terminate an active critical production streaming transaction without first triggering automated webhook warnings and a grace execution window. |
baseURL: "https://api.bigone.ai/v1". No custom SDK libraries to audit, no bespoke abstractions. If it does not handle your production prompts seamlessly on day zero, you roll back with zero vendor lock-in.
| SYSTEM IDENTIFIER | BIGONE ROUTER CORE v3.4 |
| CORE ARCHITECTURE | Rust-native asynchronous streaming proxy (Zero GC Pauses) |
| PRIMARY EDGE HUBS | Singapore (SIN-01), US-East (IAD-02), Frankfurt (FRA-01), Tokyo (NRT-01) |
| SECURITY & COMPLIANCE | Security and compliance details are provided upon request. |
| SUPPORTING ENTITY | BIGX GLOBAL PTE. LTD. (UEN: 201727107K) |
| REGISTERED ADDRESS | 61 Ubi Avenue 1, #03-04, UB Point, Singapore 408941 |
An AI infrastructure vendor that advertises 100% infallible uptime and frictionless intelligence has told you nothing you can independently verify. The architectural limits stated above are enforceable boundaries in our Service Level Agreement.
If an enterprise workload requires routing configurations outside our deterministic parameters, we flag this before provisioning your production endpoints rather than during an unexpected cluster brownout.
Tell us your current monthly inference volume and the LLM providers in your stack. One provisioned trial endpoint is usually enough to verify latency reduction, failover speed, and model routing efficiency.