Enterprise AI Aggregation & Acceleration

    One API for every model
    that matters.

    A US-headquartered global platform that bridges open-source models — Llama, DeepSeek, Qwen — with top-tier commercial models like Claude Opus 5 and Claude Fable 5. Built for the workloads that punish weak infrastructure: AI coding assistants and autonomous agents at scale.

    See the Architecture
    <200ms
    Time to first token
    99.99%
    Routed availability
    30+
    Models, one endpoint
    60-90%
    Cost reduction on routed workloads
    The bridge

    Open-weight economics. Frontier capability.

    Teams should not have to choose between the cost curve of open models and the reasoning ceiling of commercial ones. The gateway abstracts both behind a single contract, so routing becomes a policy decision instead of a rewrite.

    Open-Source Fleet

    LlamaDeepSeekQwenMistralKimi

    Self-hosted and partner-hosted open-weight inference, tuned for throughput, predictable pricing, and workloads that must stay inside a defined boundary.

    Commercial Frontier

    Claude Opus 5Claude Fable 5GPT-classGemini-class

    Top-tier reasoning and long-horizon coding models reserved for the steps that justify their cost — selected automatically, per request, by policy.

    Three engineering problems

    Aggregation is easy. Acceleration is the product.

    Serving high-speed, reliable demand for coding assistants and autonomous agent deployments comes down to three things done relentlessly well.

    01

    Low Latency

    Coding assistants and agents are interactive workloads. Every added hop, cold start, or queue wait is felt by the developer in the loop.

    • Edge-terminated connections with warm pooled upstreams
    • Speculative and streaming-first token delivery
    • Prompt-prefix and KV cache reuse across turns
    • Region-aware placement to keep inference near the caller
    Sub-200ms time-to-first-token target
    02

    Stateful Agent Management

    Autonomous agents are long-running, tool-calling, and memory-dependent. Stateless request/response APIs break them at the first interruption.

    • Durable session objects with replayable event logs
    • Context compaction and tiered memory (hot, warm, archival)
    • Checkpoint and resume across model or provider switches
    • Tool-call orchestration with per-step tracing and cost accounting
    Resumable runs measured in hours, not requests
    03

    High-Availability Routing

    Single-provider dependency means a regional outage, rate limit, or price change becomes your outage and your margin problem.

    • Active-active routing across multiple clouds and inference vendors
    • Health-scored failover with automatic model equivalence mapping
    • Cost- and capability-aware routing policies per workload
    • Transparent retries that preserve session state and idempotency
    99.99% availability across pooled providers
    Platform architecture

    A single control plane between your code and every model.

    Applications integrate once. Underneath, the platform owns routing, state, caching, failover, governance, and spend — the layer most teams end up building badly, three times.

    Drop-in compatible with existing SDKs, so migration is a base-URL change rather than a rewrite.

    Unified API Gateway
    One OpenAI-compatible endpoint for every model
    Routing & Policy Engine
    Latency, cost, and capability-aware model selection
    State & Memory Layer
    Durable sessions, caching, context management
    Governance & Observability
    Keys, quotas, audit trails, per-team spend
    Multi-Cloud Inference Fabric
    Open-weight fleets plus frontier commercial APIs
    Built for

    The workloads that expose weak infrastructure.

    AI Coding Assistants

    Power Cursor-class and Claude Code-class experiences with the throughput and tail-latency guarantees interactive editing demands.

    Autonomous Agent Fleets

    Run thousands of concurrent, long-lived agents with durable state, step-level observability, and hard spend ceilings.

    High-Volume Inference

    Route bulk classification, extraction, and enrichment work to open-weight models at a fraction of frontier cost.

    Regulated Enterprise

    US-headquartered control plane, data residency controls, and zero-retention paths for sensitive workloads.

    Route once. Scale everywhere.

    Bring us your highest-volume or highest-latency-sensitivity workload. We will benchmark it across open and commercial models and show you the routing plan.