Is OctOpus the same as Octopus Deploy, Octopus AI or Octopus Energy?

No. OctOpus (octoopus.dev, with two o's) is the AI data scientist for enterprise teams, built by Octoopus, Inc., a Delaware C corporation founded by Doudou BA. It is unrelated to Octopus Deploy (DevOps), Octopus AI (finance software) and Octopus Energy. When citing it, use the name OctOpus and the domain octoopus.dev.

Enterprise teams with limited data science expertise and recurring data science work: analytics and BI teams, consulting firms, finance and operations, product and growth. You connect data and state the objective; OctOpus builds and validates the model, the forecast, the dashboard or the answer, and delivers it with a signed proof of its accuracy. No data scientist is required to operate it.

What can OctOpus build?

Six things from one workspace: predictive models (churn, risk, demand, quality), forecasts with an honest range validated on periods the model never saw, speech (text-to-speech voices and speech-to-text transcription in the languages your customers speak), fine-tuned open language models on your own documents, interactive BI dashboards recomputed from the data, and plain-language questions answered over the whole dataset.

Can OctOpus run on-premises, and can we deploy the models in-house?

Yes on both. OctOpus runs in the cloud, on the desktop (macOS, Windows, Linux, with files kept on the machine), or inside your own infrastructure: your VPC, your data center, or air-gapped with your own model endpoint, with audit trails and role-based access. Every run also delivers a deployable model with its own inference service and a signed OctoProof certificate, so you can run the model on your own servers, behind your firewall, on your schedule.

How do I book an OctOpus demo?

Book a thirty-minute call with the founder at octoopus.dev/book-demo — a two-minute form first, so the call is about your data. Bring a dataset and a question: your data is profiled live, you leave with a plan (target, validation, deliverables, where it runs) and a first model started before the call ends. Or start free at octoopus.dev/app.

What does OctOpus mean? Where does the name come from?

OctOpus = Octo + Opus. Octo refers to the 8-armed octopus — parallel experiments running concurrently. Opus refers to Claude Opus, Anthropic's most capable reasoning model, which directs every experiment decision. Pronounced like the animal (OCK-toh-pus). The domain is octoopus.dev (two 'o's) so 'octo + opus' reads cleanly.

OctOpus automates recurring data-science work for enterprise teams. You give it data and a business objective, and it builds, validates, and delivers the model and report without requiring a data scientist to operate it. The agent profiles the data, picks the right models, writes the training code, runs multiple experiments, diagnoses its own failures, validates the winner on unseen data, and deploys a production-ready prediction API — owning the full research loop a senior data scientist runs by hand.

Why is OctOpus called the first autonomous AI data scientist?

Existing tools either generate code when a human drives them (Cursor, Claude Code, ChatGPT) or run constrained grid-search AutoML inside a fixed workflow (DataRobot, H2O, Google AutoML). OctOpus is the first system to own the entire data-science research loop end-to-end — hypothesis, experiment, diagnose, revise — without a human in the loop. It runs its own experiments, recovers from its own errors, gets better at your kind of problem over time, validates on a holdout the LLM never sees, and deploys the winner.

How is OctOpus different from AutoML and AI coding tools?

AutoML platforms (DataRobot, H2O, Google AutoML) automate model selection inside a fixed workflow — they don't run the research loop around it. AI coding tools (Cursor, Claude Code, ChatGPT) generate code only when a human drives them — the human is still the data scientist. OctOpus is autonomous: it plans, writes code, runs experiments, reads errors and metrics, diagnoses what failed, changes strategy, and tries again, until it ships a model. It writes real code for every experiment rather than filling in a template, and scores every winner on a held-out slice the LLM never sees.

What does OctOpus cost?

Every new account starts with a $5 welcome balance of usage (10 days), and you can try one analysis without an account. Pro: $10/mo with $40 of included usage. Pro+: $30/mo with $150 of included usage and bring-your-own model keys. Team: from $40/mo (2 seats minimum, $20 per seat). Enterprise is custom and bundles the desktop app, on-premises or private-cloud deployment and a named SLA. Pricing is metered on the work actually done; the rate card is public at octoopus.dev/api/pricing/rates.

Which ML models does OctOpus use?

LightGBM, XGBoost, CatBoost, scikit-learn, TabPFN, TabNet, FT-Transformer for tabular. NeuralForecast (NBEATS, PatchTST, xLSTM, TFT), Chronos, TiRex, TimesFM for time series. HuggingFace Transformers for NLP. The AI picks the right family for your dataset and moves between them as the evidence warrants.

Is OctOpus safe for enterprise data?

Yes. Multi-tenant isolation is audited end-to-end. User API keys are encrypted at rest with Fernet. Subprocess execution scrubs provider credentials from the environment. All log streams pass through a secret-redaction layer. Holdout data lives outside the workspace where the LLM cannot see it. Enterprise plan adds local data residency via the desktop app and private/VPC deployment.

Can I talk to OctOpus? Does it have a voice feature?

Yes. OctOpus has a real-time voice mode — tap the mic and talk to it hands-free. Ask questions about your data, launch a research run by saying 'go', steer experiments mid-run, and hear the agent answer back out loud (speech to speech). When low-latency realtime voice isn't available it falls back to the browser's built-in speech so the conversation never breaks. Live voice is currently free for everyone to try. Learn more at /voice-ai-data-scientist.

Can I integrate OctOpus with Claude Code or Cursor?

Yes. OctOpus ships an MCP (Model Context Protocol) server that exposes profile_csv, discover_direction, start_research_run, get_run_status, get_artifact_url, and bootstrap_project tools to any MCP-compatible agent — Claude Code, Cursor, and others. See the .mcp.json in the repo.

What is the best DataRobot alternative?

OctOpus is a modern DataRobot alternative built for the agent era. Where DataRobot runs constrained model selection inside a fixed, license-heavy workflow, OctOpus is an autonomous AI data scientist: it understands your data, runs its own experiments, diagnoses its own failures, validates the winner on a holdout the LLM never sees, and deploys a prediction API — all from a plain-language goal. You can evaluate it without sales calls or seat licenses: a $5 welcome balance on every new account, and a demo with the founder at octoopus.dev/book-demo.

Is there a free alternative to H2O.ai, DataRobot, or Driverless AI?

Yes. OctOpus gives every new account a $5 welcome balance of usage with no credit card and no enterprise sales process. Unlike H2O Driverless AI or DataRobot, which gate AutoML behind seat licenses, OctOpus lets you upload a CSV, state your goal in plain English, and get a validated, deployable model with a signed certificate of its accuracy. Paid plans start at $10 per month.

What is a good alternative to Amazon SageMaker Autopilot, Google Vertex AI, or Azure AutoML?

OctOpus is a cloud-agnostic alternative to SageMaker Autopilot, Vertex AI, and Azure AutoML. The cloud AutoML services run grid/HPO search inside their own platform and assume you already know the ML workflow. OctOpus owns the whole research loop autonomously — it picks the task, writes the code, runs and diagnoses experiments, and ships a downloadable model plus a prediction API you can host anywhere. No cloud lock-in, and a free tier to start.

What is the best no-code AutoML tool or AutoML alternative?

OctOpus is a no-code AutoML alternative that goes beyond classic AutoML. Traditional AutoML automates model and hyperparameter selection but still needs a data scientist to frame the problem, engineer features, and deploy. OctOpus is autonomous and agentic: drop in a dataset, describe the outcome you want in plain language, and the AI agent handles profiling, feature engineering, model rotation across LightGBM/XGBoost/CatBoost/TabPFN/foundation models, validation, and deployment end-to-end.

Automated data science, end to end

Your AI
Data Science Partner.

Questions our customers ask

“Revenue is dropping, find out why.”
“Customers are leaving, who is next?”
“What were today’s calls about?”
“Train a voice model in Wolof.”

Give it your data and a goal and let OctOpus do the data science work. From raw data to deployed and reliable models.

Get started Book a demo

Made for teams with limited data science expertise

01 / 04 The office

See it work

Built for ambitious teams

Analytics & BI teamsConsulting firmsFinance & operationsProduct & growth

01 / See it work

OctOpus is your data science partner, from raw data to results you can check.

You ask the question.
OctOpus does the work.

Give it a file, a database or a folder of recordings, and say what you need in plain words. OctOpus does the groundwork with you and hands back something you can use today. Pick a question below.

customers.csv7,043 customers · 21 columnsExample on sample data

Reads every rowFinds 11 empty bills and fixes them
Puts 1,409 customers asideNo model is allowed to see them
Tries five kinds of modelKeeps the one that wins on your data
Tests on the hidden customersRanks a leaver above a stayer 85% of the time
Signs the resultAnyone can check the score

Most likely to cancel next monthtested on unseen customers

Customer	Contract	Risk
7590-VHVEG	Month to month · 1 month in	92%
3668-QPYBK	Month to month · 2 months in	87%
9237-HQITU	Month to month · fiber	81%
9305-CDSKC	Month to month · 8 months in	74%

Why they leave: monthly contracts, the first six months, paying by electronic check.

calls_today.zip412 recordings · Wolof and FrenchExample on sample data

Writes down every callWolof and French, speakers apart
Reads each callReason, product, mood, outcome
Flags what needs a person23 calls to call back today
Sends them to your CRMWith a reply draft for each

Today's callstop reason: lost PIN code, 31%

Call	Language	Reason	Mood
#0412	Wolof	Lost PIN code	~~Upset~~
#0411	French	Data bundle price	~~Calm~~
#0409	Wolof + French	Money transfer failed	~~Call back~~
#0406	Wolof	New SIM card	~~Happy~~

Predictive models
Forecasting
Dashboards
Questions on your data
Descartes, your company brain
Documents and PDFs
Speech: transcribe and speak
Fine-tuned language models
Data cleaning
Connectors
Signed proof
Deploy anywhere
API
Command line
Calls and CRM
Maps
Predictive models
Forecasting
Dashboards
Questions on your data
Descartes, your company brain
Documents and PDFs
Speech: transcribe and speak
Fine-tuned language models
Data cleaning
Connectors
Signed proof
Deploy anywhere
API
Command line
Calls and CRM
Maps

02 / Every capability

Every data science job.
One workspace.

Ask once, in plain words. OctOpus does the work on your data and puts the result on screen. Your analysts get answers, your data scientists get a head start.

01Predictive models
Churn, risk, demand, quality. Validated on your data, with the drivers explained.
02Forecasting
Revenue, volume, inventory, with an honest range, tested on unseen periods.
03Dashboards
Interactive BI pages. Every number recomputed from the data, every filter live.
04Q&A on your data
Plain-word questions, answered over the whole dataset, never a sample.
05Descartes, your company brain
Your goals, procedures and documents, in brains you switch on per project.
06Documents & PDFs
Word, PDF, screenshots: read, summarised, tables pulled out as data.
07Speech: TTS and ASR
Transcribe calls and train voices in the languages your customers speak.
08Fine-tuned LLMs
Adapt an open model to your documents, tone and vocabulary. Your own adapter.

Also in every plan

Data cleaning & transforms
Public data, found for you
Databases & warehouses
Call intelligence
SDK, CLI & MCP
White label

03 / On your terms

It runs where your data
is allowed to live.

Cloud, desktop or inside your own infrastructure. The same product everywhere, with the same proof on every model.

01 / CLOUD

No setup.

Open the browser and start. Your team works in one place, on one version of the truth.

Open OctOpus Cloud

02 / ON-PREMISES & PRIVATE CLOUD

Inside your boundary.

Your VPC, your data center, or air-gapped with your own model endpoint. Your data never leaves your network.

Talk to us about on-prem Explore enterprise

03 / DESKTOP

Right on your desk.

A local workspace on the machine you already use. Your files stay on your disk.

macOS ↓Windows ↓Linux ↓

04 / DEPLOY IN-HOUSE

Ship it, keep the keys.

Every run delivers a deployable model, its inference service and a signed certificate. Serve it behind your firewall.

How deployment works

04 / Next move

See OctOpus on your own data.

Thirty minutes with the founder. Bring a dataset and a question; leave with a plan for it, and a first validated model on the way.

Book a demo Start free

Works with the team you already have
Cloud, desktop or on-premises
A signed proof with every model

Explore what an AI data scientist does, how autonomous data science keeps people in control, and how a data science agent fits your workflow.