Make AI follow
your company rules.
Corules validates every AI action against policy before it executes, in Copilot, Salesforce, or any AI stack.
The Structural Blocker
Your AI pilots work.
Your board is asking why they haven't scaled.
We’ve run the pilots. Why is AI not closing the loop on approvals?
We have no unified way to guarantee policy compliance across AI workflows.
Security and audit are not comfortable with autonomous execution.
We cannot sign off on scaled AI without defensible decision records.
The board wants to know: if AI makes a decision, can we defend it?
“If this system makes a decision, can I defend it to a regulator, auditor, or board?”
If the answer is not deterministic, AI autonomy gets blocked. Every team builds custom validation rules in every workflow separately. Governance is inconsistent. Risk accumulates without visibility.
The result:
You are not lacking AI capability.
You are lacking a deterministic enforcement layer at runtime.
What Is Actually Missing
The gap between AI output and compliant action.
Without a runtime policy layer, these two worlds do not align. So you hesitate. And that hesitation is rational.
Spread across documents
Policies live in PDFs, handbooks, contracts, and tribal knowledge. No single enforcement point.
Embedded in approval hierarchies
Approval workflows contain implicit constraints. No one has expressed them as machine-readable logic.
AI is probabilistic
Language model outputs are stochastic by design. Enterprise policy execution is deterministic by requirement.
Your organization is deterministic
You have thresholds, eligibility criteria, required sign-offs. These are rules, not suggestions.
The Job to Be Done
What leaders need before AI can act.
Only when these four conditions are met can AI move from copilot to actor.
- 01
Guarantee decisions follow internal policy
Every AI-proposed action validated deterministically against your structured policy set before it executes. Not probabilistically — deterministically.
- 02
Prevent silent rule violations
Non-compliant decisions blocked at the gate. No post-hoc audit remediation. No exceptions that slip through.
- 03
Maintain full auditability
Every outcome carries a policy version, input hash, and rule path. Replayable at any point in the future. Audit-grade from day one.
- 04
Reduce human review safely
AI executes within policy boundaries autonomously. Human review reserved for genuine edge cases and ambiguity. Not for every decision.
The Solution
A policy enforcement runtime for enterprise AI.
We sit between AI reasoning and execution. AI proposes an action. We deterministically validate it against your structured policies. Only compliant decisions proceed.
If thresholds are exceeded or rules are violated, the system blocks or escalates automatically. Every decision is logged with policy version and validation result.
AI Output
Proposed decision
Policy API
GET /v1/constraints
Validate
POST /v1/validate
Allow / Block / Escalate
Deterministic outcome
Execute
Only if allowed
Try It Live
Ve una decisión de política en menos de 60 segundos.
Selecciona un caso de uso. Revisa la política. Haz clic en Validar para ver el resultado.
Política (CEL)
discount_pct <= params.max_discount_by_tier[customer_tier] && (deal_value * (1 - discount_pct)) >= params.margin_floor
Decisión
Resultado
Click validate to run the policy evaluation
Pricing
Comienza gratis. Escala a medida que creces.
Todos los planes incluyen aplicación de políticas determinista, trazas de grado de auditoría y acceso REST + MCP.
Gratis
$0
forever
- 1 use case
- 1,000 evaluations / month
- REST API + MCP server
- Audit log (30-day retention)
- Community support
Crecimiento
$199
/ month
- 10 use cases
- 50,000 evaluations / month
- Salesforce + Power Platform integrations
- Audit log (1-year retention)
- Email support
- Policy simulator
- Parameter management UI
Empresa
Custom
contact us
- Unlimited use cases
- Custom evaluation volume
- All integrations + custom connectors
- Unlimited audit retention + export
- Dedicated customer success
- 99.9% SLA
- SSO / SAML
- Custom data residency
Before / After
You move from hesitation to controlled autonomy.
Before Corules
- AI suggests. Human reviews every single decision.
- No guarantee of policy compliance at execution.
- Violations discovered in post-hoc audit.
- Manual review scales with AI output volume.
- AI stays in advisory mode indefinitely.
After Corules
- AI acts within deterministic policy-enforced bounds.
- Every decision validated before it executes.
- Non-compliant actions blocked at the gate.
- Human review reserved for genuine ambiguity only.
- AI graduates from copilot to actor.
How It Integrates
Works where your workflows already live.
No change to your core systems. No replacement of existing workflows. Just an enforceable control layer.
AI generates structured output
Workflow calls Policy API
Policy engine validates against rules
Execution continues or escalates
Salesforce
Validate AI decisions inside Salesforce Flow and Apex callouts before committing records or approvals.
Flow + ApexMicrosoft Power Platform
Custom connector for Power Automate. Drop Corules validation into any approval flow in minutes.
Custom ConnectorCustom Agent Stacks
REST API and MCP server for any AI agent. Works with Claude, GPT, and custom LLM orchestration pipelines.
REST + MCPWho This Is For
The executives who unblock AI execution.
COO feels the bottleneck. CIO owns the integration budget. CTO validates the architecture. CISO approves the risk posture.
Remove approval bottlenecks safely.
“We’ve run the pilots. Why are we still manually reviewing every decision? AI transformation ROI is blocked by approval latency that shouldn’t exist.”
AI pilots exist but operational throughput is unchanged. Automation ROI cannot be proven without execution authority.
See COO use cases →The missing control plane for AI workflows.
“Each team builds custom rules in each workflow separately. We have no standardized enforcement layer, no central audit, and inconsistent governance across the estate.”
Fragmented AI governance is accumulating risk without visibility. Every workflow is a different implementation.
See CIO architecture →Deterministic execution gate for probabilistic AI.
“AI is probabilistic by design. We need a deterministic validation layer before any business action executes. Policy-as-code that compiles once and enforces everywhere.”
No standard architectural pattern for AI action authorization. Probabilistic outputs cannot drive deterministic enterprise decisions without an enforcement layer.
See architecture →Runtime enforcement. Audit-grade traces. Every decision.
“I cannot approve autonomous AI execution without versioned policy control and immutable audit logs. If I cannot replay the decision and defend it, I cannot approve it.”
Regulatory exposure and audit defensibility gaps block AI execution authority. Unauthorized autonomous behavior is an unacceptable risk without runtime enforcement.
See security controls →The Vision
The architecture that makes
AI decisions defensible.
Every enterprise will operate AI agents. The ones that scale will have a deterministic control layer between AI reasoning and business execution. That is what we are building.
Make your AI decisions defensible.
Join enterprise teams deploying AI with deterministic policy enforcement, audit-grade traces, and exception-based human oversight.
For enterprise teams. No credit card required.