AI TOOL PROFILE

Qoris AI: AI Governance Platform

Qoris helps enterprise and mid-market companies manage the risks of deploying autonomous AI agents. It is designed for teams that need a centralized security layer to intercept and audit agent actions before execution.

Pricing

Plans start at $149/month (billed annually) for the Starter tier, which includes 200 credits. Other tiers include Growth ($599/mo) and Professional ($2,499/mo), with Enterprise annual contracts starting at $60,000/year. A 14-day free trial is available.

At a glance

Best for
Enterprise companies, Mid-market companies, Internal AI platform teams, Developers building production AI agents
Key use cases
Regulated Industry Deployment, Cross-Departmental AI Memory, AI Agent Governance, Operational Automation
Integrations
OpenClaw, LangGraph, CrewAI, AutoGen, LangChain
Visit QorisQoris software interface screenshot

How AI is used

Qoris is an AI governance platform designed to act as a trust layer for companies deploying AI agents. It provides a centralized system for memory, reasoning, and security that supports different LLMs and agent frameworks.

The software is built for enterprise teams, internal platform leads, and developers moving AI agents into production. It helps these users maintain persistent memory for agents and ensures that autonomous actions are reviewed against company policies.

Key functionality centers on the Knox security layer, which intercepts agent actions to either approve them or flag them for human review. This is designed to help businesses in regulated industries maintain audit trails.

Buyers should confirm if their specific agent frameworks are compatible via the Model Context Protocol (MCP) and whether the credit-based pricing model aligns with their expected volume of agent tasks.

Key Features

  • Knox Security Layer

    Intercepts and reviews agent actions against defined policies before execution, supporting automated blocking or human flagging.

  • Memory & Context Engine

    Provides persistent, shared memory across different agents and sessions to help maintain continuity.

  • Thinking Agent OS

    A reasoning layer that helps agents interpret goals and form execution plans.

  • Agent Orchestration

    Coordinates multi-step workflows and handoffs between different agents across tools and teams.

  • Audit Logs

    Maintains timestamped records of agent decisions and memory access for compliance and observability.

Use Cases

  • Regulated Industry Deployment

    Using the Knox layer to help AI agents follow compliance rules and provide auditability for actions taken.

  • Cross-Departmental AI Memory

    Connecting sales, marketing, and support agents to a shared memory engine to preserve customer context across teams.

  • AI Agent Governance

    Establishing a central control plane to set permissions and policies for agents built on frameworks such as LangChain or CrewAI.

  • Operational Automation

    Supporting internal operations by coordinating multiple agents through a shared orchestration layer.

Integrations

  • OpenClaw
  • LangGraph
  • CrewAI
  • AutoGen
  • LangChain
  • MCP

FAQ

What is the Knox security layer in Qoris?

Knox is a governance layer that intercepts agent actions before they execute, checking them against defined policies to approve, flag, or block the action.

Which AI models and frameworks does Qoris support?

Qoris works with various LLMs (such as GPT, Claude, and Gemini) and agent frameworks (including LangChain, CrewAI, and AutoGen) via MCP integration.

How does Qoris pricing work?

Pricing is based on monthly or annual subscriptions starting at $149/month. Plans include a set number of credits used for agent tasks, Worker operations, and memory.

Source category: Software Development

Source subcategory: Compliance Management

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