Orkana is the unified workspace for serious data engineering and agentic AI. Connect once, build pipelines with Spark and Trino, deploy agents on the same governed runtime — on cloud or fully on-prem.
To put one production agent in front of real enterprise data, teams stitch together a stack of disconnected tools — each with its own auth, deployment, vendor, and on-call rotation.
Most projects never finish the plumbing. The agent ships late, on stale data, behind a queue of integration tickets.
One platform. One auth. One deployment. One on-call.
to wire a production stack before any AI value ships.
in licenses, integration work, and headcount per enterprise, per year.
of enterprise GenAI pilots deliver zero measurable P&L impact.
Source · MIT, 2025From raw Kafka stream to deployed agent. Visual workflows, native compute, agent runtime, dashboards, metadata explorer — all on the same data plane, same auth, same deployment.
Drag-and-drop DAGs where every node runs real compute — Python, TypeScript, SQL, Spark, Trino, agents, HTTP, Kafka publish.
Production-grade agents with built-in tool orchestration, retrieval, self-evaluation, and RBAC — talking to your data through the same engine.
Browse every schema, Kafka topic, S3 bucket, vector index. Columns, types, lineage and nullability inline — no second BI tool.
Drag-and-drop charts on top of any query or workflow output. Track pipeline health, agent traces, and KPIs in the same surface.
Databases, warehouses, S3, Google Drive, Slack, Telegram, Kafka, webhooks. Add a custom one in TypeScript in an hour.
Run on AWS, Azure, GCP, or fully on-prem and air-gapped. Domain-based isolation lets one deployment serve twenty teams safely.
A single canvas where every node is a real operation — a Spark job, a Trino query, a Python function, an HTTP call, an LLM step, a Slack notification, or a Kafka publish.
Build agents on the same canvas as your pipelines. They query your warehouse, read from Drive and Slack, call internal APIs, and respect RBAC — out of the box.
Postgres, MinIO, Kafka, vector indexes — one explorer with columns, types, nullability and lineage inline. Engineers stop bouncing between DBeaver, Grafana, and the warehouse console.
Drag-and-drop charts on top of any query or workflow output. Pipeline health, agent traces, and business KPIs — without spinning up a second BI tool.
One connector definition feeds workflows, agents, dashboards, and the metadata catalog. Add a custom connector in TypeScript in under an hour.
Define a knowledge base from any source — content, code, SOPs. Pick a chunker, embeddings provider, and splitter; agents query it through the same governed retrieval engine.
Java Spring Boot backend. Angular frontend. Kafka for events, Redis for state, Postgres + pgvector for data and embeddings. Spark and Trino for heavy work. Keycloak for identity. Every layer ships in the repo today.
Replace Airbyte + Airflow + Spark + Trino + Grafana + DBeaver with one workspace. Same DAGs, same RBAC, half the on-call.
Skip the LangChain glue. Build agents that already have governed access to your warehouse, your docs, and your event streams.
Deploy fully on-prem or air-gapped. Domain-based workspace isolation, audit on every read, no data leaves the perimeter.
For solo builders and evaluation. Hosted on Orkana Cloud, single workspace, community support.
For data and AI teams running production workflows on Orkana Cloud, with SSO and audit.
For regulated industries and sovereign deployments. Runs in your VPC, your DC, or fully air-gapped.
See Orkana running on your stack in 30 minutes. We'll connect a sample warehouse, build a working agent, and ship a dashboard live on the call.