BONACCI STUDIO

The agentic data
engineering platform

Describe a pipeline in plain English, or wire it up visually. An AI agent builds, tests, and deploys it on Apache Spark and Kafka. From idea to running pipeline in minutes, not sprints.

Start free Watch a 5 minute demo

No credit card. Bring your own model keys.

studio.bonacci.thinkingdbx.com

Pipelines

▸ orders_cdc

○ events_stream

○ daily_rollup

Sources

⛁ postgres_prod

⌁ kafka_events

you: load orders from Postgres, dedupe by id, stream to the warehouse agent building...

postgres_prod dedupe(id) warehouse

Runs on Apache Spark Apache Kafka Apache Camel Spring Boot PostgreSQL

The platform

Between your data and production, one agent-run platform

Sources on one side, running pipelines on the other. In the middle, Studio's agent builds, tests, deploys, and monitors on real distributed infrastructure.

How it works

You describe the outcome. The agent writes the pipeline.

Studio turns plain language into real, version controlled pipeline code that runs on distributed infrastructure. You stay in control of every step.

1
Chat or canvas
Type what you want, or drag nodes on the visual builder. Both stay in sync.
2
Real execution
Pipelines compile to Spark and Kafka jobs. Production infrastructure, not a sandbox.
3
Your models, your keys
OpenAI, Anthropic, Gemini, Groq, or local Ollama. No lock in, no per seat AI tax.

orders_cdc.pipeline

# generated by the agent, editable by you
source postgres_prod {
  table    = "public.orders"
  mode     = "cdc"        # change data capture
}

transform dedupe {
  by   = ["id"]
  keep = "latest"
}

sink warehouse {
  engine = spark
  to     = "analytics.orders"
}

What is inside

Everything you need to ship a pipeline

One platform instead of a stack of tools. The agent handles the plumbing so you stay on the outcome.

✦

AI pipeline builder

Go from a sentence to a running pipeline. Chat or drag nodes on the visual canvas, the agent keeps both in sync.

⛃

Connect anything

Databases, REST APIs, files, and Kafka streams. 50+ connectors with cross database ETL and CDC out of the box.

⚡

Runs on real infra

Pipelines execute on Spark and DataFusion with Kafka streaming. Production grade distributed compute, not a toy runtime.

◇

Agents and tools

Named, versioned agents with tool calling and the Model Context Protocol. Pick the right model per agent.

❖

Built-in memory

Agents remember your schemas, fixes, and decisions across sessions and workspaces, so they get better as you work.

▸

Deploy and monitor

One click deploy, live execution, quality scoring, and bottleneck detection with context aware fix suggestions.

Built for real work

From a quick load to streaming in production

ETL

Database pipelines

Cross database moves, change data capture, dedupe, and transforms. Postgres, MySQL, and the warehouse, wired in minutes.

Streaming

Real-time on Kafka

Consume events, transform on the fly, and sink continuously to the warehouse. Backpressure and recovery handled for you.

Files and APIs

Ingest from anywhere

CSV, Parquet, and JSON files, plus REST endpoints on a schedule. Paste, upload, or let an agent fetch it for you.

Demos

See it in action

Real, interactive walkthroughs that run right in the browser. No signup required.

studio.bonacci.thinkingdbx.com/demo · full product flow

Connect sources, design on the canvas, run the agent, and ship.

Minutes

idea to deployed

50+

connectors

Spark + Kafka

real distributed infra

Any model

bring your own keys

Proof, not promises

Case studies we ran on Studio itself

Real analyses where the agent wrote the pipelines, ran them on Spark, and rendered the results. Published with the data.

Case study

Intelligence is deflating: 938× cheaper in three years

Pricing data across 12 providers and three years, analyzed end to end by an agent in Studio.

read the analysis →

Case study

Is AI taking jobs? We joined the data to find out

Four public datasets, three occupation coding schemes, one crosswalk, built in Studio.

read the analysis →

Case study

The state of the AI ecosystem, in 613 data points

25 months of GitHub, arXiv, and Hugging Face activity. The agent wrote and ran the PySpark.

read the analysis →

Design partner program

Run Studio on your real pipelines. Help shape what we build.

We are onboarding a small group of design partners: teams who use Studio on production work, meet with the founders monthly, and get lifetime free access. Limited seats.

Pricing

Start free. Scale when the pipelines do.

Every paid plan starts with a 21-day Pro trial, no credit card. Bring your own model keys on every tier.

Free

For individuals getting started

Free

✓3 pipelines
✓3 connections
✓10 executions / day
✓10 MB file size
✓Community support

Start free

Basic

For small teams and projects

$250/month

or ₹23,000/month (India)

✓10 pipelines
✓10 connections
✓50 executions / day
✓50 MB file size
✓Apache Spark
✓Email support

Start free trial

Watch an agent build a real pipeline in 5 minutes

No slides. We open Studio, describe a pipeline in plain language, and ship it to Spark while you watch.

Start free Book a demo

0:30

Describe the pipeline

Plain English. Source, transform, destination.

2:00

The agent builds and tests it

Generates the pipeline, runs it against sample data.

4:30

Deployed and querying

Running on Spark and Kafka, rows landing in the warehouse.

Between your data and production, one agent-run platform

You describe the outcome. The agent writes the pipeline.

Chat or canvas

Real execution

Your models, your keys

Everything you need to ship a pipeline

AI pipeline builder

Connect anything

Runs on real infra

Agents and tools

Built-in memory

Deploy and monitor

From a quick load to streaming in production

Database pipelines

Real-time on Kafka

Ingest from anywhere

See it in action

Case studies we ran on Studio itself

Intelligence is deflating: 938× cheaper in three years

Is AI taking jobs? We joined the data to find out

The state of the AI ecosystem, in 613 data points

Run Studio on your real pipelines. Help shape what we build.

Start free. Scale when the pipelines do.

Watch an agent build a real pipeline in 5 minutes

Describe the pipeline

The agent builds and tests it

Deployed and querying