Snowflake AI employee
A Superkind AI employee that queries data in Snowflake, creates analyses, and carries out approved changes directly. Message it in Teams or Outlook, it does the work in Snowflake and reports back with the result. Anything sensitive waits for your approval.
- Hosted in the EU
- GDPR data processing agreement
- Ready to start today
- Works in Teams, Slack and more
What is a Snowflake AI employee?
A Snowflake AI employee is an AI that connects to your Snowflake account and completes work in it. It does not just answer questions about your data, it takes the actions: running queries, analysing tables, checking tasks, and correcting approved records. Superkind builds this AI employee with your company knowledge and delivers the finished result to wherever your team works.
Unlike workflow builders such as Zapier or Make, there is nothing to configure. No triggers, no zaps, nothing to maintain. You describe the outcome in plain English, the AI employee picks the right Snowflake actions, chains them with your other systems, and asks for your approval before anything sensitive runs.
A cloud data platform for storing, processing, analysing, and securely sharing data.
You ask in Teams
Describe what you need from your data in plain English.
Superkind picks the actions
Selects the right Snowflake actions and chains them together.
Superkind works in Snowflake
Runs queries, checks tables, and creates analyses with your real data.
Superkind reports back
Delivers the finished result to Teams or Outlook.
What can you ask Superkind to do in Snowflake?
Messages you would actually send. Copy one, swap in your specifics, and Superkind takes it from there.
“Query the August revenue data and give me a table grouped by region and product.”
you, to @Superkind“Create a margin analysis for last quarter from the FINANCE.MONTHLY_REVENUE table.”
you, to @Superkind“Correct the record for customer 1842 in Snowflake, but wait for my approval before saving it.”
you, to @Superkind“Let me know here as soon as daily revenue in any region deviates over 20 percent from average.”
you, to @SuperkindHow does Superkind work with Snowflake?
- Native integrations and connectors for 1,000+ tools
1Connect your systems
We connect Snowflake with the minimum permissions required. Teams becomes the place where your team assigns work and receives results. Other systems such as Outlook, SharePoint, or Jira can be added when needed. Superkind handles the connection and gets to work.
@Superkind check today's orders in Snowflake for outliers and prepare the correction for customer 1842.
On it. I am checking the ORDERS table and preparing the correction for approval.
2Tell Superkind what you need
Message your AI employee in Teams like a colleague. Ask it to analyse a Snowflake table or inspect query history. Plain English is enough. Superkind understands the outcome and picks the right actions.
- 3 outliers found in ORDERS
- DACH region above average
- Correction for record 1842 prepared
Correction record 1842Waiting for your approvalUpdate record 1842 in Snowflake?3Superkind operates, you approve
Superkind runs the queries in Snowflake and writes the result back to Teams. It handles read access on its own. Changes to data, warehouses, or roles wait for your approval. Every step is logged.
What can Superkind do in Snowflake?
Ask in plain English from Teams or Outlook. Superkind picks the right Snowflake actions, runs the work, and reports back. No workflows to build.
Run query
Runs a SQL statement in Snowflake and returns the result rows.
Fetch result
Fetches the result of a Snowflake query using its query ID.
Check query history
Lists queries with status, duration, warehouse, and executing role.
Explain query
Explains a SQL statement and summarises the tables, joins, and filters used.
Inspect query profile
Checks runtime, scans, and bottlenecks in the Query Profile of a Snowflake query.
List tables
Lists tables in a Snowflake schema with type, owner, and comment.
Describe schema
Describes columns, data types, nullability, and constraints of a Snowflake table.
Export data
Unloads query results from Snowflake to a named stage for delivery.
Correct record
Changes selected values of a record in a Snowflake table.
Delete rows
Deletes selected rows from a Snowflake table using clear criteria.
List tasks
Lists Snowflake tasks with schedule, state, warehouse, and predecessors.
Check task history
Checks Task History for failed or delayed runs.
Check pipe status
Reads the status of a Snowpipe pipe and reports pending files or errors.
Inspect streams
Shows Snowflake streams and their current change state for downstream tasks.
List warehouses
Lists virtual warehouses with size, state, auto suspend, and clusters.
Check warehouse status
Checks the state, running queries, and load of a virtual warehouse.
Resume warehouse
Resumes a suspended virtual warehouse for approved Snowflake work.
Suspend warehouse
Suspends a virtual warehouse and stops new compute usage.
List users
Lists Snowflake users with state, default role, and default warehouse.
Inspect roles
Shows account roles and database roles with their hierarchies.
Inspect grants
Lists privileges and grants for a Snowflake user or role.
Grant role
Grants a Snowflake user an account role or database role.
Analyse costs
Analyses credit consumption, warehouse usage, storage, and data transfer.
Report outliers
Compares metrics in Snowflake and reports unusual deviations to Teams.
Build tag inventory
Lists Snowflake tags and their assignments to databases, schemas, and tables.
Create table
Creates a Snowflake table with agreed columns, data types, and comment.
Superkind AI employees that work with Snowflake
Every role brings its own expertise and uses Snowflake as one of its tools.
Companies working with Superkind
Frequently asked questions
Everything you need to know about your AI employee for Snowflake.
Yes. Superkind connects Snowflake through a managed connector. Once connected, your team can put the AI employee to work in Snowflake from Microsoft Teams or Outlook. It can query data, analyse results, and carry out agreed actions. It only receives the Snowflake permissions it genuinely needs for the specific use case.
An admin creates a dedicated role in Snowflake with the minimum required privileges and confirms the secure connection. The account is then available to the AI employee for the agreed databases, schemas, and warehouses. We set up the connection with you, check the permissions, and test the first tasks before the team starts in Teams.
It can run SQL queries, deliver results as tables, inspect Query History and Task History, describe tables and schemas, monitor warehouses, and analyse credit consumption. After approval, it can also correct records, delete rows, grant roles, or create tables. The available Snowflake actions depend on the tasks and permissions agreed with your team.
No. With Zapier or Make, you build triggers, steps, and field mappings and maintain them whenever something changes. With the AI employee, you describe the desired outcome in plain English. Superkind picks the right Snowflake actions itself, connects them to Teams, Outlook, or Jira when needed, and asks when data or instructions are unclear.
Only with your approval. The AI employee can handle queries, summaries, and checks within its permissions on its own. Changes to production data, deleting rows, suspending warehouses, or granting roles wait for a yes from a responsible person in Teams. Your team decides which Snowflake actions count as sensitive.
Superkind is hosted in the EU and we sign a GDPR data processing agreement. The AI employee uses a dedicated Snowflake role with minimum permissions for selected databases, schemas, and warehouses. Your data is not used for training. Queries, results, approvals, and completed Snowflake actions are logged so every access remains traceable.
Snowflake offers Standard, Enterprise, and Business Critical and mainly charges for consumed credits, storage, and data transfer, not a fixed amount per user. Zapier starts at about 20 euros per month and Make at about 10 euros per month, both plus setup time. Superkind is priced per use case, a fraction of a full-time hire.