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What is Squid AI?

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

By securely connecting your preferred Large Language Model (LLM) with your data and systems using Squid's built-in retrieval-augmented generation (RAG) engine and private semantic layer, Squid AI enables organizations to develop, use, and integrate purpose-built AI agents into their existing systems and workflows, enhancing productivity and automating complex tasks.

Key Features​

Agent Studio​

A no-code approach to building AI agents and workflows, Agent Studio allows all users to create AI agents that connect to your data and systems, while developers can quickly prototype agents before customizing and extending them further using Squid AI's SDKs.

Rapid deployment​

The Squid AI platform has a built-in vector database, RAG engine, chunking, embedding, and other AI and multi-agent orchestration technologies. Coupled with a comprehensive backend and middle tier platform, Squid AI abstracts away complex technologies, allowing users to launch AI agents in days, reducing development cycles from months to weeks.

Data coverage​

Dozens of turnkey data connectors connect to a variety of data sources, including databases, APIs, and SaaS tools, all event-driven and in real time. Squid brings generative AI to your data so you can modernize in place without overhauling your current infrastructure or migrating data.

Multi-agent orchestration​

Build agents that can call other agents, pass along context, and use built-in validation agents for quality control. Source citation, chain-of-thought reasoning, and central audit logging for agents and all activities are provided within the platform.

Client and Backend SDKs​

For developers who prefer using code or for more sophisticated and highly customized agents, Squid offers SDKs and AI functions that can be used to build AI agents, AI-enabled applications, and full-stack applications.

Enterprise-grade security and compliance​

Squid AI was built for enterprises in mind from the start and is SOC 2 Type II and ISO 27001 compliant with robust secrets management, secure authentication, RBAC and ABAC capabilities, as well as highly granular access controls compatible with your existing identity providers.

Custom AI Agents​

Develop tailored AI agents capable of tasks such as summarizing information, automating workflows, and generating real-time data visualizations.

Developer Benefits​

Squid AI provides developers with comprehensive client and backend SDKs and a platform to build, test, and deploy AI agents efficiently.

The platform offers a serverless hosting environment on all major cloud providers and on private clouds, built-in data connectors with database schema and API endpoint autodiscovery, and supports multiple LLMs, including custom models.

Additionally, Squid AI features robust security features and centralized audit logging for monitoring and compliance.

The Squid AI Platform​

Squid AI Agent Platform

  • A serverless, k8s-based hosting environment - Squid is infrastructure-agnostic and can be deployed on AWS, Google Cloud, Azure, and in private clouds. If you’re interested in taking Squid AI on-premises, please contact us.

  • Comprehensive data connectors - Squid enables you to securely connect LLMs to structured and unstructured data in minutes. The platform provides database schema autodiscovery and automated API endpoint and methods mapping, handling all of the translation under the hood. It connects to both unstructured data (such as documents, files, and PDFs), structured data across multiple databases, data warehouses, REST and GraphQL APIs, and services like Slack, ServiceNow, Salesforce, and Google Drive. We're regularly adding our dozens of available connectors.

  • A variety of LLM options - Squid makes it easy to integrate with all of the major LLMs, and makes it easy to switch as needed. LLMs offered on Squid AI are always API and enterprise versions that are never used to train models, so your data is always private.

  • Powerful RAG functionality - Squid's RAG engine is a built-in real-time architecture that encompasses a vector database, embedding, chunking, and ranking using the latest algorithms and can be adjusted to meet your particular needs. Included is also a private semantic layer that can be automatically generated based on your data to enable accurate natural language querying.

  • A business logic layer - Use Squid’s backend SDK to customize your agent’s behavior with executables, AI functions, rate and quota limiting, triggers, and schedulers.

  • Advanced security - Protect your data from unauthorized access at all times. Squid integrates with your authentication provider of choice. It provides control access to your different entities, including AI agents, databases, backend functions, and APIs.

  • Audit logs - Audit logs are in the console, and can be exported to NewRelic, DataDog, or your preferred observability platform as needed.

What would you like to do next?​

Learn more about AI agents.

Learn about using Agent Studio to create AI agents without any code.

Explore AI agent use cases for ideas.