AI Studio & AI SDK

Easily build no-code agents and agentic AI applications

Get Collate Free

Fast AI agent creation

Easily build agents with simple AI prompts to define tasks

Fine-tuned agent skills

Choose from a set of well-defined skills to enable task specialization and work accuracy

Data and business expertise

Leverage the Collate semantic metadata graph so agents understand your data and business context

Fast AI Agent Creation

Create agents in AI Studio. Put them to work through the Collate UI or via apps built on AI SDK

AI Studio for no-code data agents

Create agents in an easy-to-use UI that entails selecting the relevant data management skills for the agent and specifying the task via AI prompt

AI SDK for custom AI agents and applications

Create AI applications using Python, Java, or TypeScript that leverage AI agents and the semantic intelligence in Collate

Use agents the way you want

Run AI Studio agents on-demand or on a schedule, or call them via external applications built on AI SDK

Self-service development

Empower users with access to build their own agents to perform tasks such as tagging, testing, translating

Fine-tuned AI agent skills

Specialize agent skills with a persona and specific capabilities to accurately direct the AI

Simple configuration

Select a few input parameters to specify the task scope of your agents then type an AI prompt to define the tasks

Behavior & Personality

Select from specific personas (Data Analyst, Database Administrator, Data Engineer, Data Steward) to direct the AI on the knowledge the agent needs for your task

Tools & Capabilities

Select one or more capabilities (Data Lineage and Exploration, Data Quality and Testing, Discovery and Search, Metadata Management, SQL Analysis) to focus on the agent’s skill set

Agent Actions

Define the specific task(s) to run as an AI prompt

Data and business expertise

Agents understand the semantics captured in the platform to take action on the right data

Documentation Agent

Agents understand and even suggest data descriptions to automate the documentation effort

Classification Agent

Let agents find personally identifiable information (PII) and automatically tag them for you, and identify relationships with related topics like regulations

Tiering Agent

Have your agents scan your data and set tiers to rate the importance or value of data sets

Quality Agent

Have agent automatically create and run data quality tests tailored to the unique shape and business context of your data

SQL Query Agent

Generate optimized SQL queries based on user requirements and tuned to your data landscape

Built for modern data & AI practices

Designed for changing needs of data & AI teams

AI-Driven Automation

Improve productivity, enforce governance and reduce costs with AI driven automation

Unified Platform

One platform for all your teams for data discovery, observability and governance

Collaborate Around Data

Accelerate development of data assets with social workspaces and knowledge centers

Get started with Collate today for free

Get Collate Free

Managed Service for Production Data Teams

Book a Demo

FAQs

Collate AI Studio is the no-code UI for building agents in Collate that perform data management tasks like tagging/documenting data, suggesting/creating/running data quality tests, tracing data lineage, finding PII, etc. AI Studio agents are self-contained so there are no external dependencies you have to set up.

Collate AI SDK is a software development kit for the Python, Java, and TypeScript languages that let you build agentic AI applications using the semantic metadata graph captured in Collate. AI SDK applications are easy to write because they call agents built with AI Studio, so all you need to pass is an AI prompt that defines the task to perform. No external technologies are needed to create and run AI SDK applications.

The Collate AI agent architecture is intended to drastically simplify the development of agents by creating a self-contained environment that does not require you to set up external technologies. With an MCP server integration, you need to write code to handle task orchestration, or add LangChain into the mix, which adds more complexity than necessary.

For AI Studio agents, you don’t need any special skills since they are created in an easy-to-use AI. You simply need to specify an AI prompt that defines the task to perform.

For AI SDK applications, you need to know how to develop applications in Python, Java, or TypeScript. No other technologies or specialized skills are needed.

AI Studio and AI SDK are designed to handle a wide range of data management tasks. If you can do it in the UI, you can create an agent to automate it for you. For example:

Identify and tag every table containing patient health information as part of HIPAA
Monitor tier 1 tables daily, and automatically create data quality tests whenever schemas change or new tables are added
Check if pipelines are running on time and without failures
Check if we are catching schema drifts before problems arise
Verify that we are inline with the company’s GDPR policy
Creates quick summaries on data readiness, especially on whether a dataset is trustworthy and ready for AI or analytics use, and how it has been used by others

AI Studio and AI SDK were designed to be complete, self-contained agent frameworks that do not need external technologies. Unlike other agent frameworks that require external technologies to build robust applications, Collate agents were designed to be easy to build and run. However, if you want to include other technologies like LangChain and MCP servers, those are supported as well.

Agents on other platforms have a very limited understanding of data. They read metadata to categorize data, but they do not have deeper information through semantic ontologies (i.e., semantic intelligence) about relationships and meaning, leading to inaccurate results due to assumptions the AI makes.

With Collate, the unified semantic graph captures metadata and relationships between metadata and data sets (e.g., PII is related to GDPR, which is related to “compliance”) so the agents have a clearer understanding of data. All of the relationship information is captured in the platform and does not have to be explicitly called out in the tasks, making the agent definition process much easier for anyone, including those who are not data experts.