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What is Squid AI?

Squid AI is an enterprise AI agent platform designed to simplify the creation, deployment, and management of AI agents and applications within enterprise environments.​

An AI agent is a system that can reason, plan, and act using your data and systems. Unlike generic AI tools, Squid AI was created to contain all of the pieces that an AI agent requires to be effective. Teams can deploy working agents in just a few days, without migrating data or training models.

Why Squid?​

Squid AI works with your data where it lives—whether that's in the cloud, hybrid environments, or fully on-premises. There's no need for costly data migrations or lengthy setup projects. The platform is designed for fast time-to-value, with most organizations deploying functional agents in 2-4 days using pre-built connectors and automated setup processes.

The platform follows responsible AI principles by default. Your data is never used to train models without explicit consent, and you maintain full control over how information is stored, accessed, and processed. Beyond just answering questions, Squid agents are action-oriented—they can trigger workflows, enforce business rules, and integrate with your existing processes.

Core Components​

Squid AI is built from three layers that work together to make AI accessible across both business and technical teams:

AI Agent Studio​

A no-code interface where non-technical users can build agents by selecting data sources and defining behavior, allowing business users to solve their own problems without waiting for engineering resources.

AI Agent Platform​

For advanced needs, technical teams have access to development tools and SDKs to extend and customize agents. This dual Studio and SDK approach means organizations can handle both simple use cases and complex custom workflows within the same platform.

Data Integration and Business Translation Layer​

Squid connects to all types of data and systems such as databases, APIs, files, and business apps (Salesforce, ServiceNow, Zendesk, Slack, and more). The business translation layer converts raw database tables into familiar terms like "active customers" or "quarterly revenue." This ensures answers are consistent and easy to understand while also giving the AI a structured map of your data for accurate querying.

Common Use Cases​

Organizations typically start with a single agent to solve an immediate pain point and then expand into more use cases and broader workflows. Some of the most common starting points include:

Knowledge management​

Organizations apply Squid AI across a wide range of scenarios, typically starting with knowledge management where agents answer questions about policies, documentation, or procedures. This proves especially valuable for onboarding new employees who can get up to speed quickly.

Technical customer support​

Technical customer support represents another common application which requires agents to reference vast volumes of data from multiple systems, including customer data, transactions data, logs, ticket history, and product information to guide support teams or handle complex scenarios.

Data analysis & reporting​

Squid agents can query databases and generate visualizations and summaries in plain language, making insights more accessible to non-technical team members. Process automation extends this further, with agents handling repetitive tasks like updating records, sending notifications, or routing approvals through proper channels.

Security & risk​

Security and risk management teams find particular value in having agents provide natural-language dashboards that surface anomalies and diagnostic information, making it easier to monitor systems and respond to potential issues. Agents can handle repetitive tasks like updates, alerts, or approvals.

Next Steps​

Head to the overview page to learn more about the platform.

Or if you're ready to get started, the path forward depends on your team's technical comfort and immediate needs:

  • Business users begin with the Agent Studio, where they can create agents by connecting data sources and configuring behavior through a guided setup. No coding required.

  • Technical teams may prefer to start with Squid's SDKs, which enable advanced integrations, custom logic, and specialized workflows that go beyond what's possible through no-code interfaces. Check out an AI tutorial for a hands-on learning experience.

  • Organizations with complex, compliance, or integration requirements can work with the Squid team to implement enterprise-wide deployments that meet specific organizational standards and policies.