• Menu
  • Skip to right header navigation
  • Skip to main content
  • Skip to primary sidebar

DigiBanker

Bringing you cutting-edge new technologies and disruptive financial innovations.

  • Home
  • Pricing
  • Features
    • Overview Of Features
    • Search
    • Favorites
  • Share!
  • Log In
  • Home
  • Pricing
  • Features
    • Overview Of Features
    • Search
    • Favorites
  • Share!
  • Log In

Dust helps enterprises build AI agents capable of taking real actions across business systems and secures sensitive information by separating data access rights from agent usage rights

July 8, 2025 //  by Finnovate

AI platform Dust helps enterprises build AI agents capable of completing entire business workflows, has reached $6 million in annual revenue — a six-fold increase from $1 million just one year ago. The company’s rapid growth signals a shift in enterprise AI adoption from simple chatbots toward sophisticated systems that can take concrete actions across business applications. The startup has been selected as part of Anthropic’s “Powered by Claude” ecosystem, highlighting a new category of AI companies building specialized enterprise tools on top of frontier language models rather than developing their own AI systems from scratch. Instead of simply answering questions, Dust’s AI agents can automatically create GitHub issues, schedule calendar meetings, update customer records, and even push code reviews based on internal coding standards–all while maintaining enterprise-grade security protocols. The shift toward AI agents that can take real actions across business systems introduces new security complexities that didn’t exist with simple chatbot implementations. Dust addresses this through a “native permissioning layer” that separates data access rights from agent usage rights. The company implements enterprise-grade infrastructure with Anthropic’s Zero Data Retention policies, ensuring that sensitive business information processed by AI agents isn’t stored by the model provider.

Read Article

Category: AI & Machine Economy, Innovation Topics

Previous Post: « Agent2.Ain’s AI agent can instantly turn complex research tasks into usable outputs in multi-formats like structured spreadsheets and presentation slides through a transparent, step-by-step breakdowns of how it searched, evaluated sources, and reached conclusions
Next Post: TNG Technology Consulting’s adaptation of DeepSeek’s open-source model R1-0528 is 200% faster, scores at upwards of 90% of R1-0528’s intelligence benchmark scores, and generates answers with < 40% of R1-0528’s output token count »

Copyright © 2025 Finnovate Research · All Rights Reserved · Privacy Policy
Finnovate Research · Knyvett House · Watermans Business Park · The Causeway Staines · TW18 3BA · United Kingdom · About · Contact Us · Tel: +44-20-3070-0188

We use cookies to provide the best website experience for you. If you continue to use this site we will assume that you are happy with it.