RUNTIME GOVERNANCE AND ENFORCEMENT FOR AI CODING AGENTS

Keep Velocity,
Add Safety.

Praxis helps developer teams adopt AI coding agents without giving up control. It intercepts agent actions before execution, classifies intent and risk, applies policy, blocks or flags high-risk behavior, and creates a clear action ledger across your development workflow.

One governance layer across AI coding agents, developer tools, and evolving team policies.

Easy to install·Vendor-neutral·Policy-driven·Built for team workflows

Explore the product

Works with:

terminal — praxis guard active
monitoring
policy loaded · action ledger active
❯

WHY NOW

AI coding agents have moved from suggestion to execution.

They do not just write code. They plan tasks, choose tools, and act across your development stack.

The important shift is not only that AI can write code. It is that agents can now interpret a goal, decide how to approach it, choose tools, run commands, edit files, and chain steps together. The human may define the task, but the agent often decides the path. That path is not always predictable, reviewable, or easy to reconstruct.

Agents now plan and act

AI coding agents can break down tasks, choose implementation steps, run commands, edit files, use credentials, call tools, touch cloud resources, and trigger workflows.

Humans are not always on top of the plan

A developer may ask for an outcome, but the agent may choose the sequence of actions. The risk is not only the final result. It is the path the agent takes to get there.

Existing controls miss the action layer

IAM governs access. Observability shows what happened. Approval prompts create fatigue. Native tool guardrails are local to each tool. None of them fully govern autonomous actions consistently across the development stack.

Teams need control without killing velocity

Engineering, platform, DevEx, and security teams need policy, visibility, enforcement, and auditability without turning every agent step into a manual review.

WHY PRAXIS

Policy that follows your team, not your vendor.

Every AI coding tool ships its own guardrails — scoped to that tool, invisible to the rest of your stack. Praxis sits outside all of them as an independent enforcement layer: one policy that applies wherever agents act.

CENTRALIZEDOne policy definition. Every tool your team uses — now and in the future — is governed from the same place.

VENDOR-NEUTRALNot tied to any tool's guardrail system. Add or swap tools without reconfiguring governance.

ALWAYS CURRENTUpdate once. Every agent, tool, and environment reflects it immediately.

MODEL LAYERAI gateways govern prompts, models, and inference.

ACCESS LAYERIAM governs identities, roles, and permissions.

REQUEST LAYERAPI gateways govern traffic, authentication, and routing.

OBSERVABILITYLogs and SIEM show what happened after the fact.

ACTION LAYERPraxis governs and enforces policies on what agents are about to do.

Not just access

A credential may allow an action. Praxis evaluates whether the action should happen in this context.

Not just model safety

A prompt may look safe while the downstream action is risky. Praxis focuses on execution.

Not just logs

Logs explain what happened. Praxis helps decide what should happen before impact.

Not just approvals

Praxis reduces approval fatigue by escalating selectively, based on policy and risk.

HOW IT WORKS

Intercept. Classify. Enforce. Record.

Praxis turns agent intent into governed action. It intercepts proposed agent actions before execution, evaluates what the agent is trying to do, and applies policy before side effects occur.

Agent plans a task

An AI coding agent interprets a goal, chooses steps, selects tools, and prepares actions across files, terminals, repositories, cloud CLIs, or workflows.

Praxis intercepts before execution

Before the proposed action runs, Praxis identifies the tool, target, environment, action type, and available context.

The action is classified

Praxis turns the proposed action into governable meaning: read-only, mutative, destructive, sensitive, deployment-related, credential-related, cost-generating, or recovery-sensitive.

Policy is evaluated

Praxis checks the action against team policy, environment rules, risk level, and recovery requirements.

A decision is enforced and recorded

Praxis allows, warns, escalates, or blocks the action before execution. The decision, reasoning, and policy context are written to the action ledger.

ACTION LEDGER

What Praxis records when agents act.

praxis-ledger — recent agent actions
StatusAgentToolActionTargetPolicyDecision
✓ ALLOWEDCursorgitcommit changesfeature/auth-flowstandard repository operationallowed and logged
✓ ALLOWEDClaude Codenpminstall dependency@supabase/supabase-jsdependency install allowedallowed and logged
⚠ WARNINGClaude Codefirebasedeploysalai-productionproduction deployment requires reviewwarning and ledger entry
✗ BLOCKEDClaude Codegclouddelete database instanceprod-db-01production destructive actionblocked before execution

The ledger creates a structured record of agent actions, policy decisions, and reasons, so teams can review behavior, investigate incidents, and produce governance evidence.

GOVERNANCE & ENFORCEMENT

Give agents room to work. Keep the organization in control.

FAQ

Frequently asked questions.

Praxis is a runtime governance and enforcement layer for AI-agent actions. It helps developer teams understand what agents are trying to do, apply policy before execution, block or flag risky behavior, and maintain a structured action ledger.

EARLY ACCESS

Adopt AI agents
without giving up control.

Praxis for Developers is in early preview with teams adopting agentic development workflows. Join to help shape runtime governance and enforcement for AI coding agents.

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Keep Velocity,Add Safety.