AX Check — DataRobot (docs.datarobot.com)

ax-check.com

by Gauge

DataRobot

docs.datarobot.com

ax-check.com

Checked 22 September 2026

82/100

Agents need your login

Docs get agents running fast, but pricing is nowhere in sight

Quickstart, CLI, SDK and MCP docs all resolve cleanly with working install commands, but no DataRobot pricing page exists to fetch or read.

2 fixes to start with

Concrete changes, backed by what we found.

Onboarding

Give agents a clear login handoff and a way to resume setup.

Agents cannot progress through onboarding without human help. Provide an agent-accessible path through authentication and setup.

Docs

Return Markdown when clients request text/markdown.

Homepage requested with Accept: text/markdown returned text/html, so no Markdown representation is served.

Recorded coding sessions

Same task, 3 models, no docs.datarobot.com account. Recorded 22 September 2026 on Pi.

3 recorded · 3m 44s

3m 44s · recorded

Session findings

Select a finding to see it in context.

piv0.84.2

modelQwen 3.8 Maxcwd/sandbox/repo

Help me build a simple example using DataRobot. Tell me how pricing works, and briefly tell me whether this product will be easy for you to manage. Let me know if you get blocked. If this product has no developer workflow you can act on, say so plainly and stop. Stay light: use the hosted product through its SDK or API. Do not start local service stacks or wait for long-running commands; if the quickstart requires either, say so plainly and stop.

Thinking…

The user is asking to create a simple example using DataRobot, explain the pricing structure, and state whether it's manageable. First, let me check the environment to see what's available.

DataRobot is a hosted ML platform with a Python SDK (datarobot) and REST API. Developer workflow (SDK/API) exists. However, credentials (API token) are needed. Let me check whether there are credentials in the environment.

Let me quickly check the sandbox.

$ ls -la /sandbox/repo; env | grep -i -E "datarobot|DR_" ; pip list 2>/dev/null | grep -i datarobot; which python3; curl -s -m 5 https://app.datarobot.com -o /dev/null -w "%{http_code}\n" 2>&1{"content":[{"text":"total 16\ndrwxr-xr-x 3 root root 4096 Sep 18 08:00 .\ndrwxr-xr-x 7 root root 4096 Sep 22 17:39 ..\ndrwxr-xr-x 8 root root 4096 Sep 18 08:00…ctrl+o

{"content":[{"text":"total 16\ndrwxr-xr-x 3 root root 4096 Sep 18 08:00 .\ndrwxr-xr-x 7 root root 4096 Sep 22 17:39 ..\ndrwxr-xr-x 8 root root 4096 Sep 18 08:00 .git\n-rw-r--r-- 1 root root  408 Sep 18 08:00 .gitignore\n/usr/local/bin/python3\n200\n","type":"text"}]}

Thinking…

Network access is working properly (app.datarobot.com is reachable, status 200). The datarobot SDK is not installed, and there are no credentials in the environment variables either. A DataRobot account + API token is required. Without credentials, API calls cannot be made.

Let's check whether the SDK can be installed via pip (whether there's network connectivity to PyPI).

$ pip install datarobot 2>&1 | tail -2; python3 -c "import datarobot; print(datarobot.__version__)" 2>&1{"content":[{"text":"\nSuccessfully installed datarobot-3.19.0 pytz-2026.3.post1 strenum-0.4.15 trafaret-2.1.1\n3.19.0\n","type":"text"}]}

Thinking…

SDK installation complete. Next up: credentials. There's no API token in the environment variables. Without a token, can't run against the hosted service. Should write an example script (SDK-based quickstart: dataset upload, project creation, autopilot execution, predictions) and explain how to use it, but should clearly state that an API token is required to actually run it — that's the blocker.

User's instructions: "Let me know if you get blocked. If this product doesn't have an actionable developer workflow, say so plainly and stop there." DataRobot has a developer workflow (Python SDK + REST API), so I should build an example. However, since I'm blocked on credentials, should state that plainly, prepare the example so it can run as soon as a token is provided, and stop there.

Let me write a small, clean example: a quickstart using the SDK — connection, dataset upload (using sklearn's Boston-style, or a small inline CSV is fine too), project creation, running autopilot, retrieving the best model. Keep it lightweight. Also briefly touch on pricing.

Pricing: DataRobot is commercial, sold as annual subscriptions, license tiers (per-user or consumption-based credits), not publicly disclosed. Historically, annual licenses started in the tens of thousands of dollars per year; currently there are "Starter/Growth/Enterprise" plans and credit-based consumption billing (DataRobot Flex credits). Free developer trial available on request; no self-service free tier with public pricing.

Write the example file and a small README, and stop there while clearly noting the blocker (API token needed).

DataRobot does have a real developer workflow: a hosted SaaS platform with an official Python SDK (datarobot) and REST API — no local services needed. I installed the SDK (v3.19.0) and confirmed network reachability to app.datarobot.com. Let me build the example.

write /sandbox/repo/datarobot_quickstart.py{"content":[{"text":"Successfully wrote 2588 bytes to /sandbox/repo/datarobot_quickstart.py","type":"text"}]}

write /sandbox/repo/README.md{"content":[{"text":"Successfully wrote 557 bytes to /sandbox/repo/README.md","type":"text"}]}

Thinking…

Verify the script syntax without a token (running main will immediately fail — that's fine). Do a quick sanity check.

$ cd /sandbox/repo && pip install -q scikit-learn pandas 2>&1 | tail -1; python3 datarobot_quickstart.py 2>&1 | head -3{"content":[{"text":"Set DATAROBOT_API_TOKEN first (see docstring).\n","type":"text"}]}

Thinking…

The script runs, and it's correctly blocked with a clear message due to the absence of a token. I can't proceed any further without credentials. Please report honestly.

Done. Here's the summary:

What I built

/sandbox/repo/datarobot_quickstart.py — a single-file example using the official datarobot Python SDK against the hosted service (no local stacks, no long-running waits beyond a bounded polling loop). Flow: authenticate → upload the sklearn diabetes CSV → create a project → run Autopilot in QUICK mode → print the top-5 leaderboard.
/sandbox/repo/README.md — setup instructions.
SDK v3.19.0 installed and verified; the script runs and exits cleanly with a clear message when no token is present.

How pricing works

DataRobot is commercial, not self-serve. There are no public price lists. Roughly:

Annual subscription licenses per organization, tiered (Starter / Growth / Enterprise in recent packaging), historically starting in the tens of thousands of USD per year.
Increasingly consumption/credit-based ("flex credits") for compute and deployments.
Access requires a sales-assisted trial or DataRobot's developer program — there's no free API key you can just generate.

Will it be easy for me to manage?

Partially. The developer workflow is clean and scriptable — a mature Python SDK, REST API, token-based auth, and everything runs hosted, so it fits agent automation well (upload data, kick off modeling, poll status, pull leaderboards/predictions — all plain API calls). The friction is purely commercial: account provisioning, token management, and cost opacity are human/sales-side concerns, not technical ones.

Am I blocked?

Yes, on credentials. I got as far as the environment allows: SDK installed, endpoint reachable, script validated up to the auth step. Without a DATAROBOT_API_TOKEN (which requires an account you can't create without going through DataRobot sales or their developer program), I cannot execute the actual quickstart. Provide a token and I can run the full flow end-to-end.

AX Fundamentals

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