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SECENG WORKBENCH · MODEL GATEWAY

Governed AI Routing, Policy Enforcement & Spend Control

Control model routing, policy, logging, and provider boundaries.

SecEng Model Gateway centralizes model access, routing rules, provider policy, sensitive-data handling, approval gates, logging, fallback behavior, spend controls, and enforcement decisions across LLM applications and agent workflows.

WHO CONTROLS WHAT MODELS CAN DO?

Cost-aware routing

Route AI requests to local models, cached completions, or hosted APIs based on cost and policy rules.

OpenAI-compatible interface

Drop-in replacement for OpenAI client calls — no SDK changes required in existing applications.

Policy enforcement

Apply content controls, rate limits, model allowlists, and data retention rules at the gateway layer.

Sensitive-data handling

Control what leaves the environment and what must be redacted, blocked, or reviewed.

Fallback chains

Define ordered fallback chains across providers, models, and local runtimes for resilience.

SecEng Model Gateway — governed AI routing dashboard with policy modes, routing targets, and evidence capture

Core capabilities

What SecEng Model Gateway does.

Cost-aware routing and fallback

Route requests through approved local, hosted, or CLI-backed executors with policy-controlled fallback. Keep work moving without bypassing enforcement.

OpenAI-compatible gateway

Keep the API shape existing tools expect while routing through a governed control point — no SDK changes required.

Policy and approval enforcement

Apply redaction, approval gates, allowlists, rate limits, project rules, and secret-handling controls before prompts reach any executor.

Sensitive-data handling

Control what leaves the environment and what must be redacted, blocked, reviewed, or logged before reaching a model provider.

Routing evidence

Log routing decisions, policy events, approvals, blocked requests, cost signals, and retest artifacts for audit, governance, and buyer security review.

Routing targets

One interface, many executors.

Keep the OpenAI-compatible interface your tools already expect while routing execution to the right target for each request type.

Claude Code CLISubscription-backed; repo-aware
Codex CLILocal repo context
Gemini CLISubscription-backed
Local modelOllama, llama.cpp, or similar
Hosted APIOpenAI, Anthropic, Gemini, and others
Fallback chainOrdered, policy-controlled sequence

Policy modes

Control what leaves the environment.

Define per-route or global policies. Enforce them before prompts reach any executor.

AllowPass through with logging
Redact then allowStrip PII and secrets first
Review firstHold for human approval
BlockReject with policy reason
Log onlyObserve without intervention

Evidence capture

Every model workflow leaves a trail.

The gateway logs routing decisions, policy events, approval actions, cost signals, and output traces. Export them for buyer review, auditor inspection, or governance sign-off.

Prompt and response logsRouting decisions and target selectionApproval events and reviewer identityBlocked requests and policy reasonsCost signals and token spend estimatesRedaction eventsRetest artifactsAudit-export packages

SECENG WORKBENCH

Put model access behind a control point.

Scope a gateway review for routing, policy, provider boundaries, logging, approvals, and evidence.