SaaS has dominated enterprise software for the past two decades. It is used by every information worker. But over the past 5 years, there is a clear change afoot – Intelligent Applications. Venture investor, Madrona Venture Group, believes the era of SaaS applications is drawing to a close as their intelligent application counterparts rise to prominence and the Intelligent Applications Top 40 list recognizes the companies to watch.
The Pacific NW has long been at the forefront of the development of this technology – through research institutes – UW’s Allen School and the Allen Institute of Artificial Intelligence (AI2), large technology companies, Microsoft and Amazon, and through innovative startups. Madrona Venture Group, has been investing in companies building and using this technology for nearly a decade.
In the fall of 2021, Madrona teamed up with Goldman Sachs and worked with more 40 top venture investors to research and select a list of the top 40 private companies building with AI and ML. Based on the deep experience at Madrona and working with a proven methodology, first pioneered, and developed by Wing.vc, and with thanks to group of venture capital investors and cloud companies that nominated and voted on the winners, we are proud to present the top 40 companies to watch this year.
2021 IA40 |
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Early | Mid | Growth | Enabler |
Runway ML | Abnormal Security | Gong | dbt labs |
Tesorio | Instabase | Snyk | Databricks |
Spot AI | Loom | Samsara | Hugging Face |
Auditoria | Amperity | Cribl | Cockroach Labs |
TruEra | Primer.ai | Starburst | DataRobot |
Clockwise | Hyperscience | Celonis | Fivetran |
WellSaid Labs | Axonius | Anduril | OctoML |
LinearB | Cresta | Chainanalysis | Grafana Labs |
Machinify | SeekOut | Workato | Monte Carlo |
Replicant | Moveworks | Snorkel AI | |
Synthesia |
Early – up to ~$30 M raised; Mid – ~$30 to ~$200 M raised; Growth – ~$200 M or more raised; Intelligent Application Enablers (stage agnostic) Methodology
What does this list tell us?
- Intelligent App Enablers are the most clear and well-known group of companies. Several like Databricks, DataRobot and Fivetran have emerged over the last 5+ years as market leaders, and many of the earlier stage companies like OctoMl and dbt are already gaining significant market traction.
- Machine to Human interactions are starting to become more ubiquitous – as the categories of sales (Gong), marketing (Amperity), customer success (Cresta, Moveworks) grow.
- Machine to Machine interactions continue to rise in adoption as cybersecurity platforms (Abnormal), physical security platforms (Anduril), and horizontal enterprise process automation (Celonis) reach the growth stage
- Cloud Providers: While the whole journey of intelligent applications (including model design and training) is hybrid and multi-cloud, most intelligent apps today leverage and operate on one or more of the major cloud platforms (AWS, Azure and Google Clouds)
- Investors: The investor group that has backed these Intelligent Apps largely represents some of the most venerable VC brands and current trends (for example, Tiger Global backed the most companies voted on to the list with A16Z and Sequoia tied for the second most companies)
Expectations for 2022
- Several IA Enablers will go public – as these companies see broader adoption in the market.
- There will be increased M&A and consolidation in the intelligent apps space – as both traditional software companies buy Intelligent Application companies and consolidation amongst emerging market leaders in key sub-sectors.
- Assuming macro-economic conditions hold, 2022 will set another record year in VC funding for intelligent applications across all stages of private financings – we are still in the early innings!
- Data rights and regulations will increasingly impact strategies for IA companies – which can be both headwinds and tailwinds for individual companies as they attempt to responsibly access, use and leverage the fuel that powers intelligent applications.
- Flywheels will start to emerge in various sub-sectors of intelligent applications. The flywheel of leveraging diverse and robust data to create contextually relevant machine/deep learning models that are then deployed to help solve real-world problems
For more on the IA40, please visit www.ia40.com.
If you are building intelligent applications, please get in touch with Madrona:
Ishani Ummat: ishani@madrona.com
Matt McIlwain: matt@madrona.com
Or want to work for a company building Intelligent Apps? https://jobs.madrona.com/