Daita is a data agent platform for building AI agents that connect to databases, APIs, and other data systems. It is aimed at creating and running custom AI agents and multi-step workflows, with a focus on deploying, managing, and iterating on them from a single dashboard.
Its documented features include automatic tracing and observability, which traces every LLM call, tool invocation, and database query without instrumentation. The platform also provides persistent memory across sessions, so agents can remember context, decisions, and preferences, with importance-scored entries scoped to a workspace and shared across a team. Another supported capability is natural-language access to data: Daita can connect to a database, query it in plain English, discover schema, infer domain context, and provide analyst-style actions such as pivoting, correlating, and forecasting.
Daita includes a free local Python SDK with tool-calling, streaming, and auto-tracing, along with a command-line interface for initializing projects, running agents, and deploying to cloud. It also offers a Python client for interacting with deployed agents via HTTP. The service supports deployment as webhooks or scheduled cron jobs, and its page also describes HTTP endpoints with built-in infrastructure. Native plugins listed on the site include PostgreSQL, MySQL, MongoDB, Snowflake, S3, Slack, and Elasticsearch.
A free plan is available and includes automatic tracing and observability, connection to any database or API, and one-click deployment to managed cloud. The site also states that every core component of Daita is open source and free to inspect, extend, and contribute to, and identifies Daita Corp. in the copyright notice.
Daita is a Frameworks & runtimes project. It focuses on simplifying the creation, deployment, and management of AI agents for data and workflow automation. Daita is a B2B product aimed at data engineers. A free plan is available. It runs on the web and the command line.
Behind Daita is Daita, and it first shipped in 2026. Development happens publicly on GitHub with 12 commits in the last 90 days. Key capabilities include agent deployment, workflow automation, and database/API connectors. It exposes integrations via a public API.
Summary written by a language model from the project’s public pages.
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