An AI agent proposes a refund, a deploy, a quote or a journal entry. Predictika checks it against your actual rules and returns allow, needs approval or block, with the reason, before anything executes.
Built on a patented deterministic engine. More than 1,700 validators built and tested against it. A first validator for a new domain in under 2 days.
Predictika
{
"valid": true,
"llm_messages": [],
"audit_messages": ["Refund within limits"],
"user_messages": []
}Your agent keeps its own model and tools. Before it runs anything that matters, it asks the validator, and the validator answers from your rules, not from a language model's guess.
Any agent, any framework, calls the validator through MCP or an endpoint with the action it wants to take and the choices behind it.
Your policies, catalogs and price lists are loaded as constraints. The engine reasons over all of them together, in any order the choices arrive.
Separate messages go to the agent, the audit log and the user. A hard failure rejects the action.
How does a validator stop an agent’s wrong action before it runs? →
A validator earns its place where several interdependent choices must hold together, a wrong answer is expensive, and someone will ask why.
Refunds, production deploys, access changes, network commands, email. Same action, different verdict, depending on who asks, what came before and what is left in the budget.
See how it worksProduct configuration, pricing, bill of materials and delivery commitments, with stacked discounts, renewals and approvals. For teams whose quoting rules are hard to model, slow to change, tough to explain or difficult to trust.
See how it worksProcure to pay, journal entries, tax positions, segregation of duties, sustainability materiality. Rules an auditor can read, with a reason attached to every finding.
See how it worksSanctions, AML and KYC checks, loans, insurance claims, and trading or digital-asset orders. Every decision gets a verdict and the rule behind it.
See how it worksMore than 1,700 validators and the list keeps growing. Each one checks a quote, order or decision against rules modeled from the product's public information, and plays back a run recorded on the live engine. A new set appears every day.
Google Cloud compute quote-time pricing check for VM fleets and commitments.
Configuration check for Woodward MicroNet Plus turbine control systems.
Data center cooling unit order validation (sizing and siting).
These are independent demonstrations. Each validator was built from publicly available information, with fictional customers and example prices. Predictika does not claim these companies as customers, and they have not reviewed or endorsed these examples.
Tell us the agent action you worry about most. We build a first validator from your public catalog, policies or price list and send you a private link in under 2 days. Point your own agent at it and see what it catches.
uv tool install pdtk-val-mcpEarly access. Runs as an MCP server named predictika-validator-mcp. Developer quickstart