You can also browse Wikipedia:Featured articles and Wikipedia:Good articles to find examples of Wikipedia's best writing on topics similar to your proposed arti
Submission declined on 7 August 2026 by M kuhner (talk).
provide significant coverage: discuss the subject in detail, excluding routine coverage like product launches, staff appointments, or financial reports and listings in databases or listicles;
are reliable: from reputable outlets with editorial oversight;
are independent: not connected to the subject, such as press releases, the subject's own website, or sponsored content.
Please add references that meet all three of these criteria. If none exist, the subject is not yet suitable for Wikipedia.
If you would like to continue working on the submission, click on the "Edit" tab at the top of the window.
If you have not resolved the issues listed above, your draft will be declined again and potentially deleted.
If you need extra help, please ask us a question at the AfC Help Desk or get live help from experienced editors.
Please do not remove reviewer comments or this notice until the submission is accepted.
Where to get help
If you need help editing or submitting your draft, please ask us a question at the AfC Help Desk or get live help from experienced editors. These venues are only for help with editing and the submission process, not to get reviews.
If you need feedback on your draft, or if the review is taking a lot of time, you can try asking for help on the talk page of a relevant WikiProject. Some WikiProjects are more active than others so a speedy reply is not guaranteed.
To improve your odds of a faster review, tag your draft with relevant WikiProject tags using the button below. This will let reviewers know a new draft has been submitted in their area of interest. For instance, if you wrote about a female astronomer, you would want to add the Biography, Astronomy, and Women scientists tags.
Please note that if the issues are not fixed, the draft will be declined again.
Comment: It may help to read WP:CORPTRIV for a list of things that generally don't establish notability: most of the sources here are CORPTRIV such as earnings, product lines, and collaborations. Source 2 is more substantive but one has the impression all the information comes straight from Encord and is not independent. M kuhner (talk) 04:02, 7 August 2026 (UTC)
Encord is a British–American technology company that develops data infrastructure software for artificial intelligence. Its platform is used to manage, curate, annotate, and evaluate multimodal data, including images, video, audio, text, and LiDAR point clouds for artificial intelligence model development.[1][2][3][4][5]
Encord was founded in 2021 by Eric Landau and Ulrik Stig Hansen.[8] The company participated in Y Combinator's Winter 2021 batch, where the first version of its product was launched.[9] Its early products focused on data labelling for computer vision, particularly annotating medical images in healthcare.[10][1] The company is dual-headquartered in San Francisco and London.[9]
In June 2021, Encord raised US$4.5 million seed round led by CRV.[11][12] By April 2022, the company had raised US$17.1 million in combined seed and Series A funding.[10] In August 2024, Encord raised US$30 million in a Series B round led by Next47, with participation from CRV, Crane Venture Partners, and Y Combinator.[9][13]
In 2025, Encord released its LiDAR annotation product for robotics and autonomous driving applications.[14] In October 2025, the company released E-MM1, an open-source multimodal dataset that it described as the largest of its kind.[14] In November 2025, it released EBIND, a multimodal embedding model built on E-MM1 that retrieves information across audio, video, text, images, and LiDAR point clouds, using any one modality as input.[14]
In February 2026, Encord announced a US$60 million Series C funding round led by Wellington Management, bringing the company's total capital raised to US$110 million.[15][8][16] Other investors included Y Combinator, CRV, Bright Pixel Capital, and Isomer Capital, among others.[17]
Physical AI data operations
Encord generates and sells data on human and robotic movement to companies developing humanoid robots.[2] At a test facility in Hayward, California, operators use control rigs to guide robotic arms through tasks such as pouring liquids and sorting objects, capturing training data for robot motor skills.[2] The company has said it plans to open a teleoperations centre at the facility to allow remote operation of deployed robots.[2]
Informasi ini disarikan dari Wikipedia dan disajikan kembali untuk tujuan edukasi. Konten tersedia di bawah lisensi CC BY-SA 3.0. Kami tidak bertanggung jawab atas ketidakakuratan data yang bersumber dari kontribusi publik tersebut.
The information displayed on this website is sourced in part or in whole from Wikipedia and has been adapted for the purpose of restating it. We strive to provide accurate and relevant information, however:
There is no guarantee of absolute accuracy. Wikipedia is an open, collaborative project that can be edited by anyone, so information is subject to change.
It is not intended to constitute professional advice. The content displayed is for informational and educational purposes only. For important decisions (e.g., medical, legal, or financial), please consult a professional.
Content copyright. Wikipedia is licensed under the Creative Commons Attribution-ShareAlike License (CC BY-SA). This means that content may be reused with appropriate attribution and shared under a similar license.
Responsible use. Any risk arising from the use of information from this website is entirely the responsibility of the user.
- provide significant coverage: discuss the subject in detail, excluding routine coverage like product launches, staff appointments, or financial reports and listings in databases or listicles;
- are reliable: from reputable outlets with editorial oversight;
- are independent: not connected to the subject, such as press releases, the subject's own website, or sponsored content.
Please add references that meet all three of these criteria. If none exist, the subject is not yet suitable for Wikipedia.