Unified gateway to global enterprise AI
Effortless, stable, compliant and cost-effective access to global AI ecosystems — full enterprise governance, security, operations and optimisation in one platform.
Product Architecture
Four-layer architecture for enterprise AI infrastructure
From network infrastructure to model optimization — a complete enterprise AI access and governance platform.
Product Capabilities
Enterprise AI governance across every dimension
HAI Gateway turns Token usage from a technical cost centre into a manageable, auditable digital asset — covering cost, access, audit, stability, and developer experience.
From end-of-month surprises to pre-set budget control
Turn AI spend from unpredictable technical overhead into a manageable budget item.
Set budgets at org, dept, project, and Key level. Pre-validate quota before every request. Multi-tier alerts at 80% / 95% / 100%. Auto-block or rate-limit on ceiling hit. Cost aggregated by dept × model for chargeback.
Who can call, what they can call, and whose budget it comes from
Turn Token into a controllable enterprise asset — eliminate risks from key leakage, over-privileged calls, and offboarding residue.
RBAC permission matrix covering creation, usage, rotation, revocation, and audit of every Key. Each Key binds to a project, member, model scope, budget cap, and RPM limit — every call has a clear owner.
Every model call is traceable and attributable
Turn model usage from "black-box consumption" into full-chain observable and attributable data.
Real-time monitoring of requests, Tokens, failure rates, model distribution, and call details. Every record carries project, Key, time, and source. Filter by any dimension — locate anomalies in seconds, not days.
Intelligent routing and failover for production-grade reliability
AI capability runs as reliably as your core systems — upstream failures are absorbed transparently.
Smart routing selects the optimal channel by model, availability, cost, and latency. Auto-failover on upstream throttling or timeout. Concurrency protection with circuit breaker isolation. Real-time vendor health monitoring across all providers.
Minimal code changes, maximum compatibility
Claude Code · Codex · LangChain · ChatBox — connect via native protocol. Migration means changing only Base URL and API Key.
Compatible with OpenAI, Anthropic, and domestic model protocols. Developers call HAI Gateway exactly as they would the original provider — no SDK changes, no business logic refactoring, switch models with a single parameter.
client = OpenAI(
base_url = "https://api.hai.network/openai",
api_key = "sk-pat-***" # HAI Token
)
Industry Cases
Real problems. Real changes.
How enterprises across industries use HAI Gateway to bring AI usage under control.
Developers used Claude Code, Cline, and internal Agents — keys scattered across local configs, CI/CD, git history, and test scripts. Management saw spend rising fast but couldn't trace which team or project was responsible. When employees left, nobody could say which keys were still active under their name.
Tools only need a Base URL and API Key swap. Team and project quotas are issued by the admin. Coding tools shifted from "personal productivity" to "enterprise R&D assets".
Dozens of projects running simultaneously — pre-sales, delivery, and ops all used AI, but keys were scattered across laptops, expenses, and vendor bills. When project managers calculated margins, the AI line item was basically an estimate.
Each project gets a dedicated Key and budget. Model access for each team is configured separately. AI costs tied to project accounting for the first time.
A multi-step financial agent: intent recognition, retrieval, report parsing, risk assessment, answer generation — each step possibly calling a different model. Once live, the biggest pain: total costs visible, breakdowns weren't. No way to know which step cost most or which model swap wouldn't hurt quality.
Developer calls brought into team budgets. The agent tags each step when calling — the gateway records tokens, latency, errors, and cost per step.
From API aggregator to enterprise AI compute backbone
Three years of iteration: from a two-vendor API aggregator to a multi-vendor, high-availability enterprise AI API management platform.