Dataset Finder is a workspace for AI training data, built by the data-labelling team at Innovatiana. Search a curated catalogue in plain language, read a full dataset card before you commit, order custom data when nothing fits, and keep a record of what went into each model.
Comparing options? Jump to Dataset Finder vs Scale AI, Sama, Labelbox, Hugging Face and 12 more.
Most AI teams find data in one place, judge it in another, buy labelling from a third vendor and track it all in a spreadsheet. Dataset Finder puts the four jobs together.
Type what you're building in plain language: the task, the domain, the languages.
Read the top picks and their cards: licence, quality, bias, fine-tuning readiness.
Found it? Go to the source and download under its licence. Gap? Order custom data with credits.
Link the dataset to your project so its lineage and licence stay on file.
| The status quo | Dataset Finder |
|---|---|
| Browse 5 different directories, filter by keyword | Dataset discovery across tens of thousands of curated AI datasets |
| Read research papers to evaluate dataset quality | Automated analysis on 30+ criteria per dataset |
| Hire labelers, write guidelines, run QA yourself | Custom data on-demand · labelers, QA, delivery handled |
| Quote-and-wait procurement (often weeks to start) | Self-serve credit ordering · kick off in minutes |
| Bring your own pipeline, scale headcount internally | Plug our trained annotators into your existing tools |
| Decisions live in Slack threads & lost wikis | Project workspace with notes, links, and lineage |
| Reinvent the wheel for every fine-tuning project | Community AI recipes reviewed & validated by our team |
| Scramble before audits, scattered evidence | Built for GDPR & EU AI Act audit-ready by default |
| Discovery, labeling, governance across 4+ different vendors | One workspace for the full training data lifecycle |
Dataset Finder overlaps with four categories without being any one of them. These are general patterns across the vendors we compared; individual vendors vary.
| Capability | Dataset Finder | Dataset hubs & search | Labelling platforms | Managed labelling services | Data marketplaces |
|---|---|---|---|---|---|
| Search existing datasets | Yes: Natural-language search over a curated catalogue | Yes: Keyword or full-text search with filters | No: Built for your own data | No: Not the focus | Partly: Their own catalogue, to license |
| Analysis of each dataset | Yes: Automated analysis on 30+ criteria, curated catalogue | Partly: Cards written by uploaders or publishers | No: Not applicable | No: Not applicable | Partly: Documented by the vendor |
| Custom annotated data | Yes: Managed annotators, paid in credits | No: Not offered | Partly: Tool first; services as an add-on | Yes: The core offer, usually by quote | Yes: Collection on request |
| Published, self-serve prices | Yes: €0, €9.90 or €29.90 a month | Yes: Free; Hugging Face also has paid tiers | Partly: Some free tiers; paid tiers often on request | No: Mostly quote-based | No: Mostly by quote |
| Works inside your labelling tool | Yes: Label Studio, CVAT, Labelbox, Encord and more | No: Not applicable | No: You label in their tool | Partly: Varies; often their own platform | No: Not applicable |
| Training-data inventory & lineage | Yes: Projects, recipes, lineage, audit trail | Partly: Repos and version history | Partly: History for the data you label there | No: Not the focus | No: Not the focus |
Patterns from the vendors compared below, checked 26 October 2026. Each comparison page lists its sources.
Side-by-side comparisons with the labelling companies, platforms and dataset hubs AI teams ask us about. Each one sets out where Dataset Finder differs and lists its sources.
Companies that produce or annotate data for you, usually by quote.
Software your own team labels in, often with optional annotation services.
Vendors that license their own off-the-shelf datasets.
Where open datasets are hosted or indexed.
Dataset Finder is built by Innovatiana, a data-labelling company. Its annotators and domain specialists, including medical students and clinicians, linguists, lawyers and developers, produce the custom data you order, supervised by a dedicated Data Labeling Manager. Innovatiana's main delivery centre is in Majunga, Madagascar.
A workspace for AI training data. You search a curated catalogue of tens of thousands of datasets in plain language, read a full dataset card before you commit, order custom annotated data when nothing fits, and keep a record of what went into each model.
No. There is no annotation editor to learn. Custom data is produced by Innovatiana's annotators, who can work inside your existing tool (Label Studio, CVAT, V7, Labelbox, Encord, Roboflow, SuperAnnotate or Prodigy) or provide one.
No. Dataset Finder keeps each dataset's metadata and its own analysis, and sends you to the original source (Hugging Face, an academic page, a government portal) under that source's licence. The exception is custom data you order, which the team delivers to you directly.
Those are hubs that host files, with cards written by uploaders. Dataset Finder hosts nothing: it covers a curated selection across sources (many on Hugging Face), adds automated analysis on 30+ criteria to each card and searches by intent. See Dataset Finder vs Hugging Face and vs Kaggle.
Those companies produce or annotate data for you, mostly by quote, and some (Appen among them) also license ready-made datasets. Dataset Finder adds a search step first, so you can check what already exists before commissioning anything, and lets you order custom data self-serve with credits. See vs Scale AI, vs Sama and vs Appen.
Trained annotators and domain specialists recruited and managed by Innovatiana, including medical students and clinicians, linguists, lawyers and developers, supervised by a dedicated Data Labeling Manager. Not an open crowd.
Free to start. Startup is €9.90 a month and Pro €29.90 (or €99 and €299 a year). Custom data is paid in credits, per task or per dataset delivered, with no set-up fee. Details on the pricing page.
It keeps the documentation those rules ask for: which datasets each project uses, their licences and lineage, preprocessing notes, governance metadata and an audit trail, plus a record of who annotated what on custom data. That's evidence for your compliance work, not legal advice or a certification.
Discover tens of thousands of curated AI datasets, order custom training data, and turn fragmented data pipelines into production-ready AI assets, all in one workspace.