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Everything the platform team asks for before they say yes

Cost and routing get you in the door; governance, observability and control get you through procurement. All of it shipped and live today.

Token compression

Log analysis, RAG, and long-context prompts are mostly repetition. NeuroRoute's compression pipeline strips it before the request is billed — typically ~40% off input tokens on long prose, with zero code changes, composable and per-key configurable. Every response reports its own compression ratio and tokens saved.

Governance & observability

Guardrails, in and out

A configurable rule pipeline screens prompts and responses — PII redaction, banned content, custom webhook checks. Per-org and per-key, fail-closed, with blocked requests logged for review.

Full request-log observability

Search every request by model, cost, status, or your own custom metadata tags. Stream traces to your own APM over OpenTelemetry, with usage rollups and SLO dashboards built in.

SSO, workspaces & roles

Log in with your identity provider via generic OIDC single sign-on. Split an org into workspaces (teams), assign granular roles (viewer, member, billing, admin), and issue scoped service keys limited to exactly what they need.

Bring any model

Beyond the built-in providers: register any OpenAI-compatible endpoint, use Azure OpenAI, tap DeepInfra's 10-vendor open-weight catalog with automatic OpenRouter failover, or point at your own self-hosted models.

Config-as-code routing

Version your routing policy like code: pin a model or run a weighted A/B split, matched on request metadata and workspace — reviewed, rolled forward, and rolled back without a redeploy.

Automation & alerts

Scheduled usage exports to your cloud storage, event webhooks (budget tripped, key created, data erased) signed with HMAC, and spend alerts over email or webhook — so the platform tells you, you don't have to watch it.

Eval framework

Benchmark models and routing strategies against your own prompt suites — quality score, cost, and latency per case. Compare a routing-config version against a model pin or a strategy override before you promote it to production.

Model catalog + auto-decommission

A weekly sync discovers new models from every provider. A model unreachable for 48 hours is flagged for decommission. Admins promote discovered models to live routing with one click — and the catalog never hard-deletes anything.

Dedicated inference EARLY ACCESS

Most teams should route to shared models — it's cheaper. But past a certain sustained volume, dedicated capacity wins on both cost and predictability. Reserved capacity and BYOM are onboarding design partners now, on the Enterprise tier.

Reserved capacity

Reserve dedicated replicas of any open-weight model in the NeuroRoute catalog — GLM-5.2, Kimi K2.7, Llama 3.3 70B, DeepSeek-V3 and more. Your own GPUs, your own throughput ceiling, billed per GPU-hour, not per token.

BYOM — bring your own model

Have a fine-tuned or proprietary model and no wish to run GPU infrastructure? We host it on capacity isolated to your tenant alone, behind the same OpenAI-compatible endpoint, with the same routing, budgets, guardrails and audit trail.

Predictable latency

Dedicated replicas do not queue behind other tenants. A known throughput ceiling and stable tail latency — what agentic loops, batch document processing and coding assistants actually need.

Choose your region

Capacity is provisioned per region so data residency is a deployment choice rather than a policy promise.

Overflow, not failure

Saturating your reservation degrades into routing overflow to a shared model instead of rate-limit errors. You keep serving.

One bill, one ledger

Reserved and BYOM usage lands in the same ledger and the same invoice as your routed traffic — no separate GPU console to reconcile.

Every other lever

Semantic + prompt caching

Repeated and near-duplicate prompts return from cache; supported providers cache your system prefix for up to ~90% off repeated input tokens.

7 strategies, including Fusion

Cascade (cheap-first, escalate on failure), task-aware, and Fusion — fan the same prompt to the top-N models in parallel; an independent judge picks the winner verbatim.

Native MCP server

Use NeuroRoute directly from Claude, IDEs, and agents over the Model Context Protocol — with OAuth 2.1 click-to-connect.

Self-hosted option

Route sensitive or high-volume workloads to your own vLLM models on your own hardware, through the same API.

Observability built in

Every decision is explainable: paste a request ID into the Routing Explorer to see which models were considered and why one won.

Learns your workload

Thumbs-up / down feedback tunes routing to your definition of quality — not a generic benchmark.

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