Next-gen enterprise AI infrastructure
The private
LLM service gateway.
Unified management, smart routing, quotas and full observability — one gateway to govern every LLM call in your enterprise.
Core capabilities
AI Gateway: auth · routing · observability · security — unified.
Capability gallery
The gateway at a glance
Unified ingress · multi-model fan-out
One entry — smart routing to vendors and in-house models. No more point-to-point integrations.
Enterprise data security
Bidirectional masking, sensitive-content blocking and full audit trails for keys and calls.
Full-stack observability
Volume, latency, error rate and quality — visualized in real time to drive governance decisions.
Call topology
Enterprise apps → Gateway → Multi-model services
- OpenAI-compatible protocol — zero code change
- Header / SDK / sidecar onboarding options
- Tag every request for downstream governance
- Multi-tenant with fine-grained ACL
- Quotas by QPS / TPM / budget thresholds
- Sensitive-content blocking and bidirectional masking
- Multi-objective routing by latency / cost / quality
- Automatic fallback and multi-route redundancy
- Semantic cache and batching cut cost
- OpenAI, Anthropic, Qwen, Zhipu, DeepSeek and more
- In-house and fine-tuned models served uniformly
- Canary releases, A/B testing and version rollback
- Volume / latency / error / quality — four quadrants
- Cost attribution by key / project / org / model
- Full audit logs for compliance traceability
Why TokensChain Gateway
Six product advantages.
Unified multi-model ingress
Onboard and standardize calls across vendors — end fragmented per-app integrations and master a multi-vendor ecosystem.
Flexible routing policies
Dynamic routing, load balancing and failover combining traffic and model signals — protecting SLAs and stability.
Fine-grained governance
Configure model permissions, traffic and quotas per user, API key, project or organization.
Precise cost accounting
End-to-end cost attribution across user, key, project, organization, model and compute.
Full-stack model observability
Multidimensional metrics for volume, latency and quality — powering governance, lifecycle and routing decisions.
Enterprise data security
Bidirectional masking, sensitive-content blocking and audit trails — keep every call compliant and traceable.
Use cases
Where it fits
Centralize model resources and expose a consistent, governed entry point for apps and agents.
Cut per-call cost with caching, batching and routing strategies.
Smart fallback, throttling and redundancy protect mission-critical SLAs.
Run in-house, open-source and third-party APIs side by side behind a single entry.
See all model traffic, cost, errors and quality in one place.
Customer voices
From frontline ops teams
"As permission tiers, quotas and cross-org usage tracking grew, our legacy API gateway couldn't keep up. This gateway delivers fine-grained governance, cross-cluster HA, fast degradation and full-trace observability — a major boost to ops efficiency."
"Smart routing by business type and context length protects differentiated SLAs; sampling, A/B testing and canary releases make iteration disciplined."
FAQ
Common questions
Why does an enterprise need an LLM gateway?+
Diverse model sources, inconsistent protocols, fragmented call paths, inconsistent SLAs and opaque cost — a gateway solves all of these centrally.
We already have an LLM API — do we still need a gateway?+
Yes — the gateway adds routing, quotas, audit, observability and governance above raw APIs. It's a critical infrastructure layer.
Does the gateway add network overhead?+
Added latency is typically <5ms; with caching and locality routing the end-to-end latency often drops.
How does it control cost?+
Semantic cache, batching, per-key/project/org quotas, and routing to cost-optimal models — combined.
Is on-prem deployment supported?+
Yes — deployable in your IDC/VPC with zero data egress, plus Xinchuang hardware and GM-crypto options.
Unify your AI traffic.
One gateway. Every model call governed.