AI · alternatives · 2026
24 alternatives to Mona
Platform that enables AI teams to monitor model performance
Below are 24 products that do a similar job, ranked by how close each is in meaning and then by launch-day votes. Mona launched in 2020; newer entries below may have overtaken it.
- 1
- 2
- 3
- 4
Panorama▲367AI that finds your team’s workflows and hidden structures
Apr 2026 · withpanorama.com · its alternatives →
- 5
- 6
Dreambase.ai▲264Fully integrated analytics from Supabase. Free to use.
2025 · dreambase.com · its alternatives →
- 7
- 8
DataSquirrel.ai▲305Data analytics and BI for non-tech managers
2024 · datasquirrel.ai · its alternatives →
- 9
Supaboard 3.0▲323AI data analysts that understand your business
May 2026 · supaboard.ai · its alternatives →
- 10
- 11
- 12
- 13
- 14
Uncover gaps in your tech team and hire the best fit with AI
2024 · its alternatives →
- 15
AI analytics, ask anything to analyze instantly
2024 · analytics-model.com · its alternatives →
- 16
- 17
- 18
- 19
- 20
- 21
AI-driven marketing platform to fuel ad performance
2022 · its alternatives →
- 22NB
Michael and Yury here – we're building a no-code analytics platform for growth teams that automatically generates actionable data insights. After working in the data space for many years, we realized there was still a huge gap in the marketing analytics market. Growth teams have so much marketing and advertising data, yet this siloed data is not actionable. The existing BI and search-driven analytics solutions are designed for data-savvy people. In our experience (previously built an NLP company called FriendlyData), non-technical people just don't know what questions to ask. So we decided…
2022 · narrative.bi · its alternatives →
- 23
- 24IA
Hey HN! This is Steve from integrate.ai (https://integrate.ai). Our platform unlocks a range of machine learning and analytics capabilities on data that would otherwise be difficult or impossible to access due to privacy, confidentiality, or technical hurdles. Traditional approaches to machine learning and analytics require centralization and aggregation of data sources. Given the increasingly distributed nature of data - across organizations, across borders, and across connected devices - centralizing the data necessary for machine learning and analytics often requires complex…
2022 · its alternatives →
Also compare
Ranked by how close each launch is in meaning, then by votes. Prices were read from each product’s own site when checked and can change. Refine with your own description →