[ PERFORMANCE AT A GLANCE ]
[ WHAT ENTERPRISES NEED ]
Moving from prototype to production-grade AI means solving for performance, security, governance, and agent reliability simultaneously.
Low latency, high throughput, and predictable response times at 1,000+ RPS without degradation
RBAC, SSO, guardrails, PII redaction, audit logs, and compliance frameworks (SOC 2 Type II, HIPAA, GDPR)
Per-team budgets, rate limiting, virtual keys with independent limits, and real-time cost analytics
MCP gateway for tool execution, federated auth for internal APIs, agent mode with parallel execution
In-VPC deployment, vault support for key storage, no data leaving your infrastructure perimeter
Native Datadog, Prometheus, OTEL, Splunk integrations. Log exports to S3, Snowflake, BigQuery
Go-native with goroutines, pre-spawned worker pools, circuit breaker, adaptive load balancing, and clustering
3-tier role hierarchy via Okta/Entra SSO, CEL-based guardrail rules with AWS Bedrock/Azure/Patronus, immutable audit trails
Customer → Team → User → Virtual Key budget hierarchy. Per-VK rate limits (token + request), provider-level budgets
Centralized tool governance, multi-level filtering, code mode (50% fewer tokens), OAuth 2.0 with PKCE for internal APIs
Deploy in AWS/GCP/Azure VPC. HashiCorp Vault, AWS Secrets Manager, Google Secret Manager, Azure Key Vault supported
Datadog APM + LLM Observability plugin, OTEL to Grafana/New Relic/Honeycomb, log exports to S3/Snowflake/BigQuery/Redshift
[ THE PROBLEM ]
Most teams start with a single LLM provider and a direct API call. That works until traffic spikes, rate limits hit, or a provider outage takes your product offline.
Without automatic failover or model routing, your engineering team scrambles to hardcode a backup manually. Downtime is measured in hours, not seconds.
A degraded provider responds slowly instead of failing fast. Without a circuit breaker, requests queue behind timeouts, dragging down throughput for healthy providers too.
PII flows through LLM APIs without redaction. No RBAC, no audit trail, no guardrails. Compliance teams cannot approve production deployment without centralized controls.
As MCP servers multiply, each agent connects to tools independently. No centralized tool policy, no federated auth for internal APIs, no audit trail for tool executions.
At thousands of requests per second, you lose visibility into which teams, models, and providers drive spend. No unified cost analytics layer across providers.
Hand-rolled retry logic without centralized control means retry storms amplify load during the exact moments your infrastructure is most stressed.
[ HOW IT WORKS ]
Every request flows through a single Go-based gateway that handles routing, security, caching, governance, and observability transparently.
Point your existing SDK at Bifrost's base URL. Every request gets low latency routing, automatic retries, guardrails, and transparent failover.
Configure RBAC, guardrails, circuit breaker thresholds, retry policies, budgets, and audit exports from a single dashboard or config file.
[ SECURITY & GOVERNANCE ]
Bifrost ships with the security controls, access management, and compliance infrastructure platform teams need before rolling out AI tooling organization-wide.
Block PII leakage, prompt injection, and policy violations in real time. CEL-based rules with configurable input/output enforcement.
3-tier role hierarchy (Admin, Developer, Viewer) mapped from your IdP. Custom roles with resource-level permissions.
Immutable, cryptographically verified trails for auth, config changes, and data access. SOC 2 Type II, GDPR, HIPAA, ISO 27001 ready.
Auto-sync API keys from enterprise secret managers with zero-downtime rotation and periodic sync cycles.
Deploy entirely within your VPC on AWS, GCP, or Azure. All requests stay in your network. Full private subnet isolation.
Native Datadog APM + LLM Observability, OTEL export to Grafana/New Relic/Honeycomb, and log exports to S3/Snowflake/BigQuery.
[ PRODUCTION-GRADE AGENTS ]
As MCP servers multiply across your org, Bifrost centralizes tool connections, security, authentication, and audit trails. Your agents get tools. Your platform team gets control.
Bifrost acts as both MCP client and server, connecting to external tool servers and exposing them to agents with centralized policy enforcement. Tools are discovered at runtime, not hardcoded.
Federated Auth transforms existing private APIs into LLM-ready tools without writing code. Existing RBAC, audit trails, tenant isolation, and rate limiting are preserved.
[ PERFORMANCE AT SCALE ]
Bifrost manages model routing, resilience, and cost optimization transparently, giving your team high availability and predictable throughput without building custom infrastructure.
Multi-factor scoring weighing error rates (50%), latency (20%), utilization, and momentum. Provider and key selection at two independent levels.
>2% errors → Degraded, >5% → Failed with automatic rerouting. Recovery: 90% penalty reduction in 30s. Sequential fallbacks during full outage.
Go-native with goroutines, pre-spawned worker pools, sync.Pool memory reuse. 54x faster P99 and 9.5x higher throughput than Python gateways.
Exact hash matching plus semantic similarity (0.0-1.0 threshold). Weaviate, Redis, Qdrant, Pinecone. Sub-ms retrieval with streaming support.
Customer → Team → User → Virtual Key with independent limits. Rate limiting by tokens and requests. Alerts via Email, Slack, Webhook.
Context-based timeouts so slow providers fail fast. Only transient errors trigger retries. Permanent errors fail immediately.
[ COMPARISON ]
Every feature in the right column is production-ready on deploy. No custom code, no glue services, no extra infrastructure.
| Capability | DIY / No Gateway | Bifrost |
|---|---|---|
| Model routing | Manual provider switching | Adaptive routing across 1000+ models |
| Circuit breaker | Not available | Configurable thresholds (2%/5% error triggers) |
| Provider outage | Manual failover, hours of downtime | Automatic fallbacks, <5second rerouting |
| Retries & timeout | Hand-rolled, inconsistent | Centralized per-provider exponential backoff |
| Low latency | 40ms+ overhead (Python gateways) | 11µs mean overhead, 54x faster P99 |
| Throughput | GIL-bound runtimes (Python gateways) | 5,000 RPS sustained (Go native) |
| Semantic caching | Not available | Dual-layer with vector similarity |
| Cost analytics | Scattered billing dashboards | Unified tracking by team, model, provider |
| RBAC & SSO | Build from scratch | Okta/Entra OIDC, 3-tier role hierarchy |
| Guardrails | Not available | AWS Bedrock, Azure, Patronus, GraySwan |
| Audit logs | Build from scratch | Immutable trails, SIEM export, compliance reports |
| MCP gateway | Per-agent tool connections | Centralized governance, 3-level filtering |
| Vault support | Manual key management | HashiCorp, AWS, GCP, Azure vaults |
| High availability | Single point of failure | Cluster mode with gossip-based sync |
| Observability | Multiple integrations needed | Native Datadog, BigQuery, OTEL, Prometheus, log exports |
[ ENTERPRISE SUPPORT ]
Enterprise plans include hands-on support from the Bifrost team to help you deploy, scale, and operate with confidence.
Direct access to Bifrost engineers for deployment planning, architecture review, performance tuning, and production incident support.
Tailored service-level agreements with guaranteed response times, uptime commitments, and escalation paths matched to your requirements.
Private Slack or Microsoft Teams channels with your Bifrost support team for real-time communication and faster resolution.
Scoped engagements for building custom Go or WASM plugins tailored to your business logic, integrations, and workflow automation needs.
[ USE CASES ]
Real deployment scenarios where centralized gateway infrastructure solves problems that custom code and scattered tooling cannot.
Fallback chains across OpenAI, Bedrock, and Vertex. Circuit breaker reroutes traffic in seconds when a provider fails. Full visibility in Datadog.
In-VPC deployment keeps data in your network. Guardrails redact PII before it reaches any model. Audit logs export to Splunk. RBAC controls who accesses production models.
Cluster mode on Kubernetes with gossip-based sync. Throughput scales linearly. Semantic caching absorbs repeat queries, multiplying capacity without provider spend.
3-level tool filtering controls which agents use which tools. Federated auth exposes internal APIs as MCP tools without code changes, preserving RBAC and tenant isolation.
Virtual keys give each team its own budget via Customer → Team → VK hierarchy. Cost analytics slice by team, model, and provider. Semantic caching cuts redundant spend.
Native Datadog plugin sends APM traces and LLM Observability data with session tracking and W3C tracing. Log exports push daily Parquet files. Prometheus alerts on error spikes.
[ GETTING STARTED ]
Three steps from zero to production-grade scalability, security, and governance.
Run as a standalone binary or Docker container. For high availability, deploy in cluster mode on Kubernetes with gossip-based discovery. In-VPC deployment for regulated environments.
Add provider keys, set up RBAC via your IdP, enable guardrails, configure fallback chains and circuit breaker thresholds. Connect vault for key storage. All via dashboard or config file.
Connect Datadog/BigQuery or your OTEL stack. Set team budgets. Enable audit log exports. Scale by adding cluster nodes. Monitor everything from the built-in dashboard or your existing tools.
[ BIFROST FEATURES ]
Everything you need to run AI in production, from free open source to enterprise-grade features.
01 Governance
SAML support for SSO and Role-based access control and policy enforcement for team collaboration.
02 Adaptive Load Balancing
Automatically optimizes traffic distribution across provider keys and models based on real-time performance metrics.
03 Cluster Mode
High availability deployment with automatic failover and load balancing. Peer-to-peer clustering where every instance is equal.
04 Alerts
Real-time notifications for budget limits, failures, and performance issues on Email, Slack, PagerDuty, Teams, Webhook and more.
05 Log Exports
Export and analyze request logs, traces, and telemetry data from Bifrost with enterprise-grade data export capabilities for compliance, monitoring, and analytics.
06 Audit Logs
Comprehensive logging and audit trails for compliance and debugging.
07 Vault Support
Secure API key management with HashiCorp Vault, AWS Secrets Manager, Google Secret Manager, and Azure Key Vault integration.
08 VPC Deployment
Deploy Bifrost within your private cloud infrastructure with VPC isolation, custom networking, and enhanced security controls.
09 Guardrails
Automatically detect and block unsafe model outputs with real-time policy enforcement and content moderation across all agents.
[ SHIP RELIABLE AI ]
Change just one line of code. Works with OpenAI, Anthropic, Vercel AI SDK, LangChain, and more.
[ FAQ ]
Bifrost uses a circuit breaker pattern that detects provider degradation within seconds. Keys exceeding 2% error rate are marked Degraded, and above 5% triggers Failed state with automatic rerouting. Sequential fallbacks try each configured backup provider until one succeeds. Recovery is automatic with 90% penalty reduction in 30 seconds. See [Fallbacks documentation](https://docs.getbifrost.ai/features/fallbacks#fallbacks).
Bifrost adds approximately 11µs mean overhead per request at 5,000 RPS on a t3.xlarge instance. This is effectively invisible compared to typical LLM response times of hundreds of milliseconds to several seconds. Built in Go with native goroutines, it achieves 54x faster P99 latency than Python-based gateways. [Read more about Bifrost becnhmarks](https://getmaxim.ai/bifrost/resources/benchmarks).
Bifrost acts as both MCP client and server, connecting to external tool servers and exposing them to agents with centralized policy enforcement. Three-level tool filtering (client config, request-level headers, virtual key policies) controls which agents access which tools. MCP Federated Auth transforms existing internal APIs into MCP tools without code changes.
Yes. Bifrost supports full In-VPC deployment on AWS, GCP, and Azure. All LLM requests stay within your network perimeter. Combined with vault support (HashiCorp Vault, AWS Secrets Manager, Google Secret Manager, Azure Key Vault), no API keys or data leave your infrastructure. See [In-VPC deployments](https://docs.getbifrost.ai/enterprise/invpc-deployments).
