Enterprise AI Gateway
A single, governed entry point for every model, prompt and AI service used across the organization.
What breaks without this
- Teams integrate directly with multiple model providers, each with its own authentication, logging and rate-limit behavior.
- No single point exists to enforce data-handling policy before a prompt leaves the corporate network.
- AI spend and usage across departments stay invisible until the invoice arrives.
Centralizes access to first-party and third-party language models behind one authenticated, policy-enforced interface, so every Application layer agent inherits the same routing, logging and cost controls without duplicating integration work.
What it does
Unified API surface across model providers with provider-agnostic routing and automatic failover.
Request and response logging with configurable retention for audit and incident review.
Pre-flight PII and secrets redaction on outbound prompts, and content filtering on inbound completions.
Per-team, per-application quota and budget enforcement with usage attribution.
Model version pinning and staged rollout controls for provider or model upgrades.
From request to result
Register
Applications and agents register through the gateway with scoped credentials rather than direct provider keys.
Route
Each request is evaluated against routing policy — cost, latency, data residency, model capability — and sent to the selected endpoint.
Inspect
Outbound and inbound payloads pass through configurable policy checks: redaction, filtering, logging.
Report
Usage, cost and policy events are recorded centrally for governance and finance review.
Built to be audited, not just used
- Every request is attributable to a team, application and end user for audit purposes.
- Data-residency routing keeps regulated workloads on approved endpoints.
- A kill switch can disable a model or provider instantly across every consuming application.
Fits existing infrastructure
Exposed to agents through the Model Context Protocol (MCP) for tool and data access, and Agent-to-Agent (A2A) messaging for multi-agent handoff — so third-party and custom agents can integrate without proprietary connectors.
Outcomes to expect
Qualitative, directional outcomes. We do not publish unverified performance figures — see the case studies section for engagement-specific, authorized results.
- AI spend and usage become visible and attributable at the team and application level.
- New model providers can be added or swapped without re-integrating every downstream application.
- Security and compliance teams gain one control point instead of reviewing each integration separately.
Works alongside
Agentic Orchestration Platform
Coordinates multi-step, multi-agent workflows across tools, data sources and human approval points.
FoundationAI Governance & Observability
Continuous visibility into what every agent did, why, and whether it stayed inside policy.
FoundationSovereign / Private AI Deployment
Runs models inside an organization's own environment when residency, sovereignty or isolation requirements rule out shared public endpoints.
Evaluate Enterprise AI Gateway for your environment
Talk to an architect about integration into your existing stack, or request a scoped demo against a representative use case.