Qdrant AI employee
A Superkind AI employee that searches collections, analyses points, checks payloads, and turns results into clear tables inside Qdrant. Message it in Teams or Outlook, it works in Qdrant and reports back with the result. Before sensitive actions such as changes to production points, it 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 Qdrant AI employee?
A Qdrant AI employee is an AI that connects to your Qdrant account and completes work in it. It queries collections, searches vectors, checks payloads, and analyses points. 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. You describe the outcome in plain English, the AI employee picks the right Qdrant actions, chains them with your other systems, and asks for your approval before changing production data.
Qdrant is a vector database for semantic search, recommendations, and production applications using high-dimensional data.
You ask in Teams
Describe which Qdrant data you need in plain English.
Superkind picks the actions
Selects the right Qdrant queries and chains them together.
Superkind works in Qdrant
Searches collections, checks payloads, and analyses points.
Superkind reports back
Delivers the finished result to Teams or Outlook.
What can you ask Superkind to do in Qdrant?
Messages you would actually send. Copy one, swap in your specifics, and Superkind takes it from there.
“Query the product-knowledge collection for similar entries and return the ten best matches as a table.”
you, to @Superkind“Create an analysis of this week's search scores and group unusual results by source and category.”
you, to @Superkind“Correct the status of point 1842 in the customer-knowledge collection, but get my approval first.”
you, to @Superkind“Let me know here as soon as more than five outliers below score 0.6 appear in the product-knowledge collection.”
you, to @SuperkindHow does Superkind work with Qdrant?
- Native integrations and connectors for 1,000+ tools
1Connect your systems
Connect Qdrant with secure credentials and minimal permissions. Add Teams and the systems that provide context. Superkind checks the connection and knows the approved collections. Then you can get started directly in Teams.
@Superkind check the customer-knowledge collection for unusual search scores, create a snapshot, and prepare the payload correction for point 1842.
On it. I am checking the Qdrant search scores, creating the snapshot, and preparing the correction.
2Tell Superkind what you need
Message your AI employee in Teams like a colleague. Ask for a table of Qdrant matches or an analysis of search scores. Superkind understands the goal and picks the right queries.
- Collection customer-knowledge checked
- 7 score outliers found
- Payload correction prepared
Snapshot customer-knowledge createdWaiting for your approvalApprove payload correction?3Superkind operates, you approve
Superkind runs the queries in Qdrant and writes the result back in Teams. Read-only tasks run independently. Changes to points, payloads, or collections wait for your approval. Every step is logged.
What can Superkind do in Qdrant?
Ask in plain English from Teams or Outlook. Superkind picks the right Qdrant actions, completes the work, and reports back. No workflows to build.
List collections
Lists all Qdrant collections with their names and status.
Describe collection
Shows the vector parameters, distance metric, shards, and replication factor of a collection.
Create collection
Creates a Qdrant collection with vector size, distance metric, and shard configuration.
Delete collection
Deletes a Qdrant collection together with its points and payloads.
Retrieve points
Loads selected points with vectors, payloads, and IDs from a collection.
Scroll points
Pages through points in a collection using payload filters.
Count points
Counts points in a collection, optionally matching a filter.
Upsert points
Writes points with IDs, vectors, and payloads to a collection.
Delete points
Removes selected points or filtered point groups from a collection.
Search similar points
Finds the points most similar to a vector with scores and payloads.
Recommend points
Calculates recommendations from positive and negative point examples.
Discover points
Finds new points between preferred and avoided vector areas.
Batch search queries
Runs multiple Qdrant search queries in one batch.
Group search results
Groups search results by a payload field and returns matches per group.
Check payloads
Reads payload fields of selected points and reports missing or inconsistent values.
Apply payload filters
Filters points with match, range, geo, or nested conditions.
Update payload
Sets or overwrites payload fields for selected points.
Create payload index
Creates a field index for faster filtered Qdrant queries.
List payload indexes
Shows configured field indexes and their data types in a collection.
List snapshots
Lists collection and full-storage snapshots with creation time and size.
Describe snapshot
Shows the name, size, and creation time of a Qdrant snapshot.
Check cluster status
Reads the peer, shard, and replication status of the Qdrant cluster.
Check shard state
Shows local and remote shards with the replica status of a collection.
Check health status
Checks the Qdrant endpoints for readiness and operational status.
Get telemetry data
Reads Qdrant telemetry data for version, collections, and cluster operation.
Check locks
Shows whether Qdrant has globally blocked or allowed write access.
Superkind AI employees that work with Qdrant
Every role brings its expertise and uses Qdrant as one of its tools.
Companies working with Superkind
Frequently asked questions
Everything you need to know about your AI employee for Qdrant.
Yes. Superkind connects Qdrant through a managed connector. Your team can then ask the AI employee for queries and analyses from Teams or Outlook. It works directly with approved collections, points, and payloads. It only receives the permissions it actually needs for the agreed tasks.
An admin provides the Qdrant endpoint and an API key with the smallest possible permissions. Together, we select the collections and tasks the AI employee may access. Superkind checks the connection and configures access. You can then submit the first tasks directly in Teams without building webhooks or custom integration logic.
It can describe collections, retrieve and count points, search by vector similarity, calculate recommendations, check payloads, group search results, and assess snapshots and cluster status. It can also prepare write actions and execute them after approval. The Qdrant actions available day to day depend on your use case and the permissions you grant.
No. With Zapier or Make, you build triggers, steps, and field mappings and maintain them when something changes. With the AI employee, you describe the desired outcome in plain English. Superkind picks the right Qdrant actions itself, connects them to Teams, Outlook, or Jira when needed, and asks when information or approval is missing.
Only with your approval. Superkind can complete read-only queries, analyses, and status checks independently. Before the AI employee uploads or deletes points, changes payloads, creates an index, or deletes a collection, it waits for a yes from a responsible person in Teams. Your team defines which actions are sensitive and who may approve them.
Superkind is hosted in the EU and signs a GDPR data processing agreement with you. The AI employee uses a Qdrant API key with minimal permissions and access only to agreed collections. Your data is not used for training. Model requests run without retention, and every executed Qdrant action is logged for your review.
Qdrant Cloud offers a free starting option. Paid clusters are billed by resources and usage, and production setups often sit in the low hundreds of euros per month. Zapier starts at about 20 euros per month and Make at about 10 euros, both plus setup and maintenance time. Superkind is priced per use case, a fraction of a full-time hire.