Alkera is an agentic data platform for data engineering, analysis, and science teams. It connects data tools, business knowledge, monitoring, lineage, and collaborative workspaces so agents can help investigate incidents, analyze data, and prepare changes for human review.
Alkera is an agentic data platform for data engineering, analysis, and science. It brings people and software agents into shared workspaces connected to the tools already used across a data stack, including databases, warehouses, transformation systems, orchestration tools, BI products, documentation sources, and communication platforms.
The platform is designed to keep data work contextual and reviewable. Its agents can trace data dependencies, use recorded business knowledge, monitor jobs and data quality, investigate incidents, and prepare changes for review. Repairs are tested in sandbox environments rather than applied directly to production, while lineage, pull requests, CI/CD checks, and approval workflows provide points for human oversight.
Trace dependencies from ingestion through warehouses, transformations, and dashboard charts at the column level. Before a change, an agent identifies affected downstream assets and asks for approval when it detects a possible break.
Store business context beside tables, columns, and dashboards. Entries record their author and trust level, support private or team sharing, and can be synced from sources such as Google Docs, Notion, and Confluence.
Monitor warehouses and jobs using query and job history, Airflow and dbt runs, and Datadog monitors. Teams can define checks for missing, duplicate, stale, or reference-related data across whole tables or new rows.
Agents investigate incidents and prepare repairs using operational context, lineage, documentation, and code history. Changes are tested in isolated environments before production, with pull requests and checks available through GitHub.
Work in shared spaces where people and agents can address data engineering, analysis, and science tasks together. Connected tools include databases, warehouses, orchestration systems, transformation tools, BI platforms, knowledge sources, and team communication services.
When a team needs to remove or modify a field, Alkera can trace that field from ingestion through transformations to dashboards, identify downstream dependencies, and present the impact before approval.
When a warehouse or scheduled job fails, agents can combine monitoring signals with execution history, lineage, team knowledge, and code history to investigate the incident and prepare a repair for review.
Teams can define checks for missing, duplicate, stale, or invalid reference data and apply them to complete tables or newly added rows, helping identify rule violations before bad data moves further through the stack.
Analysts can use a connected notebook-style workspace to ask questions, create charts, and refine an analysis collaboratively, while agents perform data tasks and respond to follow-up requests such as adding a regional breakdown.
Alkera connects with data, orchestration, transformation, monitoring, documentation, communication, and BI tools listed on its site, including Snowflake, BigQuery, Databricks, Redshift, PostgreSQL, MySQL, Airflow, dbt, Datadog, GitHub, Slack, Google Docs, Notion, Confluence, Tableau, Looker, Sigma, and Hex. The available connections may depend on the plan and workspace configuration.
Alkera agents can investigate warehouse and job failures, review execution logs, lineage, knowledge-base items, and code history, then propose pipeline repairs. Proposed changes are tested in sandbox environments before production, and fixes can be reviewed through pull requests and CI/CD checks.
Yes. Teams can create an organization with shared connections and permissions. Members can work alongside agents, receive incident updates in Slack, and approve or reject requests from the messaging platform.
Alkera offers Free, Plus, Pro, and Enterprise plans. The Free plan is listed as free forever with 10 GB of storage and limited usage; Plus and Pro add more storage and usage, while Enterprise is custom and includes options such as SSO/SAML, SCIM and IAM, audit logs, VPC or on-premises deployments, data residency controls, and available SLAs.
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