A
Astound
Applying machine learning and natural language processing to automate service and support
About Astound
Astound.ai operates as an enterprise software company, developing an artificial intelligence platform aimed at transforming employee service experiences for large corporations. Founded in 2016 by CEO Dr. Naghi Prasad and Chief Product Officer Dan Turchin, the company is headquartered in Menlo Park, California. The founding duo combines Prasad's doctorate in artificial intelligence with Turchin's two decades of experience in enterprise service management and product leadership at companies like ServiceNow. This blend of technical and market expertise was directed at alleviating inefficiencies in internal IT and HR help desk requests.
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The company launched in early 2018 with $11.5 million in Series A funding, co-led by Vertex Ventures and Pelion Venture Partners, with participation from The Hive, Slack Fund, and Moment Ventures. This was followed by a $15.5 million Series B round in April 2019, led by March Capital Partners, bringing the total capital raised to $27 million. These funds were earmarked for accelerating innovation and talent acquisition.
Astound's core business revolves around its AI platform that uses machine learning and natural language processing to automate the entire lifecycle of employee service requests. It serves large enterprise clients, aiming to resolve common support issues such as password resets, application configurations, and network outages without human intervention. The platform is designed to add a layer of intelligence to existing service management systems like ServiceNow, Workday, and Atlassian's Jira, rather than replacing them. Revenue is generated through this software-as-a-service (SaaS) model.
The platform's key features include virtual support agents for automating routine tasks and contextual recommendations to assist human agents, making them more efficient. It promises to significantly reduce call volume, decrease mean time to resolution, and lower the cost per ticket. By automating up to 70% of routine requests, the system allows IT and HR professionals to focus on more complex, high-value concerns. The technology is capable of finding answers across various enterprise data sources, including emails, databases, and spreadsheets, to provide accurate solutions.
At a glance
- Status
- Operational
- Founded
- 2016
- Headquarters
- Menlo Park, United States
- Open positions
- None listed
- Dealroom signal
- 55.0/100
- Industry
- Enterprise Software
- Sector
- AI, Human Resources, Ticketing, Speech Recognition, Predictive Analytics, Hard Tech, DT and LS
- Technology
- Artificial Intelligence, Deep Tech, Machine Learning, Natural Language Processing, Recognition Technology
- Business model
- SaaS
- Client focus
- b2b
Latest news
Press, funding announcements and product moves mentioning Astound.
Funding history
Company financing events and reported valuations.
| Deal type | Date | Amount | Valuation | Investors | Source |
|---|---|---|---|---|---|
| SERIES B✓Equity / VC | Apr 2019 | $16M | $62M | Moment Ventures · Slack Fund · March Capital Partners · Vertex Holdings | — |
| SERIES A✓Equity / VC | Jan 2018 | $12M | $46M | Vertex Holdings · The Hive · Slack Fund · Pelion Venture Partners | ↗ |
Financials
Revenue, earnings and other financial measures where available. Years marked “E” are estimates.
Growth signals
Latest recorded traffic for Astound is 140 monthly website visits, down 65% over the last three months.
Similar companies
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Investors
From Dealroom's funding and investor records, grouped by the round each investor first entered.
Seed1 investor entered at this stage
Slack Fund
Series A5 investors entered at this stage
Vertex Holdings
Pelion Venture Partners
The Hive
Moment Ventures
March Capital Partners
Source: Dealroom Talent Intelligence.
Global footprint
Market sentiment
An AI-synthesised read of the highest-engagement posts about Astound on X, ranked by likes and reposts, corporate channels excluded.
Reading the room on X — pulling top posts and synthesizing themes…
Source: X recent search ranked by engagement (likes + retweets) · Synthesis by Claude · Cached for 1 hour
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