Draft:Botpress
Submission declined on 11 June 2026 by CopyleftEverything (talk).
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Submission declined on 20 April 2026 by RangersRus (talk). This draft reads like an advertisement. Wikipedia is an encyclopedia, not a platform for promotion or marketing. Drafts that are exclusively promotional may be deleted without notice.
Declined by RangersRus 5 months ago.Wikipedia articles must be written neutrally in a formal, impersonal, and dispassionate way. They should not read like a blog post, advertisement, or fan page. Rewrite the draft to remove:
Instead, only summarize in your own words a range of independent, reliable, published sources that discuss the subject. If you have a conflict of interest (e.g. you are the subject, an employee, or a relative) or are being paid to edit, you must disclose this to comply with Wikipedia's Terms of Use. | |
Comment: Likely LLM authorship. Lots of WP:OVERATTRIBUTION. Rewrite and resubmit. CopyleftEverything (talk) 03:27, 11 June 2026 (UTC)
Botpress is a Canadian software company that develops software for building conversational AI applications and AI agents. The company originated as an open-source chatbot development project and later shifted its focus toward software for large language model (LLM)-based agents.[1][2]
History
[edit]Botpress was founded by Sylvain Perron and Justin Watson.[3] According to TechCrunch, Perron started the project after concluding that existing bot-building tools were insufficient for his needs, and the first version was released in 2017.[4]
In 2021, Botpress announced a US$15 million Series A funding round led by Decibel, with participation from Inovia Capital and other investors.[5][6] In 2025, BetaKit reported that the company had raised a further US$25 million in Series B financing led by Framework Venture Partners, bringing its total disclosed funding to US$45 million.[7]
Products
[edit]Botpress initially developed software for building and managing chatbots and other conversational applications for enterprise use.[8][9] By 2025, the company was described by BetaKit as focusing on software for building, deploying, and monitoring AI agents based on large language models.[10]
References
[edit]- ↑ Miller, Ron (28 April 2021). "Botpress nabs $15M Series A to help developers build conversational apps". TechCrunch. Retrieved 20 April 2026.
- ↑ Scott, Josh (23 June 2025). "Botpress closes $34-million CAD Series B to help companies build and deploy AI agents". BetaKit. Retrieved 20 April 2026.
- ↑ Kirkwood, Isabelle (3 May 2021). "Today in funding: Botpress, Sherpa, Kinetyx, Realize Medical, G2V Optics, Solvera Solutions". BetaKit. Retrieved 20 April 2026.
- ↑ Miller, Ron (28 April 2021). "Botpress nabs $15M Series A to help developers build conversational apps". TechCrunch. Retrieved 20 April 2026.
- ↑ Miller, Ron (28 April 2021). "Botpress nabs $15M Series A to help developers build conversational apps". TechCrunch. Retrieved 20 April 2026.
- ↑ Kirkwood, Isabelle (3 May 2021). "Today in funding: Botpress, Sherpa, Kinetyx, Realize Medical, G2V Optics, Solvera Solutions". BetaKit. Retrieved 20 April 2026.
- ↑ Scott, Josh (23 June 2025). "Botpress closes $34-million CAD Series B to help companies build and deploy AI agents". BetaKit. Retrieved 20 April 2026.
- ↑ Kirkwood, Isabelle (3 May 2021). "Today in funding: Botpress, Sherpa, Kinetyx, Realize Medical, G2V Optics, Solvera Solutions". BetaKit. Retrieved 20 April 2026.
- ↑ Miller, Ron (28 April 2021). "Botpress nabs $15M Series A to help developers build conversational apps". TechCrunch. Retrieved 20 April 2026.
- ↑ Scott, Josh (23 June 2025). "Botpress closes $34-million CAD Series B to help companies build and deploy AI agents". BetaKit. Retrieved 20 April 2026.
Please delete the portions which were LLM-generated, and summarize in your own words a range of independent, reliable, published sources that discuss the subject. If you have used an LLM but you believe that your use is covered by one of the two exceptions (basic copyediting and translation between two languages in which you are fully fluent), please provide a transcript of the prompt(s) you used while writing your draft (see the how-to guide). Reviewers can make mistakes. If you have not received any LLM assistance, you may seek a second opinion at the AfC Help Desk.
See the advice page on large language models for more information.