Emergence AI, a startup founded by IBM veterans that emerged from stealth earlier this year with more than $97 million in funding, today unveiled its enterprise-grade autonomous multi-agent AI orchestrator, which it claims is among the best offerings for enterprises on the market.
Why should an enterprise go with Emergence AI, a company whose name is likely unfamiliar, over rival offerings from big tech vendors such as Microsoft with its Magentic-One framework or Salesforce with Agentforce, or even, as also announced today, Amazon’s Bedrock multi-agent orchestrator?
One simple advantage: cross-application and cross-vendor compatibility.
“Modern enterprises have hundreds of systems—some legacy, some modern,” said Satya Nitta, Co-Founder and CEO of Emergence AI, in a recent video call interview with VentureBeat. “Our technology bridges these systems, automating workflows across platforms where vendors like Microsoft or Salesforce fall short.”
Put another way: your company likely has multiple tech vendors such as Salesforce for Slack, Microsoft or Google for email, and maybe even Notion or Monday for project tracking. Emergence’s contention is that trusting a first-party solution from any of these folks would be a mistake when they don’t always play well together. It aims to sit above the fray and work well with any application and vendor that the enterprise uses, uniting them all with its orchestrator.
Emergence’s orchestrator acts as an advanced meta-agent that integrates API interactions and web navigation to optimize enterprise workflows.
The orchestrator operates as a hierarchical planner, enabling real-time planning, execution, and verification.
“We think of autonomous agents as analogous to autonomous driving—dealing with dynamic environments and requiring planning, reasoning, and deterministic execution,” Nitta said. “We are proud to announce the first multi-agent orchestrator built for web automation, featuring an over-the-top web agent and an API agent working together to tackle complex workflows.”
Emergence AI’s agents excel in performing intricate tasks, such as navigating dynamically changing interfaces, extracting data from unstructured sources, and overcoming errors like broken links or unexpected pop-ups.
These capabilities are further enhanced by secure API interactions, enabling seamless cross-application workflows and integration across enterprise systems.
“Autonomous agents are exciting but must be deterministic,” Nitta emphasized. “Enterprises won’t deploy systems that work 95% of the time—they must work every time.”
The orchestrator’s flexible architecture allows organizations to integrate new agents and prompts seamlessly. “Enterprises need runtime determinism and design-time flexibility. They should be able to adjust workflows and integrate new agents or prompts without writing code,” Nitta explained.
Real world use cases
Emergence AI has already demonstrated its orchestrator’s effectiveness across several industries:
• Supply Chain Management: API agents retrieve and update supplier data from platforms like SAP, while web agents gather insights from supplier portals, enabling comprehensive reporting and proactive decision-making.
• Financial Services: Autonomous agents combine historical data aggregation with regulatory document analysis to create in-depth financial reports.
• Quality Assurance (QA): Web agents automate testing by simulating user interactions, ensuring error-free deployments of web applications. “Our agents can plan and execute test scenarios, reducing weeks of manual effort into hours by identifying bugs and generating detailed reports. It’s a massive productivity gain,” Nitta shared.
• Research and Analytics: Agents integrate structured API data with public records and research papers for detailed analyses.
These use cases underscore the orchestrator’s ability to handle tasks previously reliant on manual intervention, significantly reducing time and resource expenditures.
Nitta also said the orchestrator can assist with travel planning and booking.
In general, for all these use cases, “these workflows often involve integrating legacy and modern systems.”
Flex pricing
Emergence AI is offering a tiered pricing model designed to cater to developers and enterprises alike. “For developers, we offer a freemium model with 100 free actions, and after that, we charge per action,” said Nitta. “Pricing ranges from five cents to $1.50 per action depending on complexity—whether it’s a simple search or something like test scenario development.”
For larger organizations, Emergence AI is testing an enterprise-focused pricing approach tied directly to measurable outcomes. “For enterprises, we’re exploring value-based pricing,” Nitta explained. “It’s about tying the cost to the ROI—like extending the capability of a data scientist or automating workflows that would otherwise take extensive manual effort.”
Future enhancements promised
Emergence AI also introduced a roadmap to expand its orchestrator’s capabilities. Planned features include a “Build Your Own Orchestrator” platform and an Agent Software Development Kit (SDK), allowing developers to create custom agents. Future updates aim to integrate Vision-Language Models (VLMs) for advanced DOM processing and introduce multi-turn conversational interfaces.
The company is addressing a gap in autonomous agent evaluation by introducing enterprise-specific benchmarks. In recent tests using the WebVoyager benchmark, Emergence AI’s orchestrator outperformed industry standards by 10-30%, affirming its leadership in web automation.
Supporting safety and scalability
Dr. Margaret Honey, President and CEO of the Scratch Foundation, commended the orchestrator’s role in advancing safety and scalability. “We are partnering with Emergence and leveraging their Multiagent Orchestrator to implement an innovative agentic solution for platform moderation at scale. This approach will be instrumental in enhancing user safety while supporting the Scratch Foundation’s mission to provide a secure and creative learning environment for children worldwide.”
Emergence AI emphasizes enterprise-grade security in its solutions. The orchestrator can be deployed within Virtual Private Cloud (VPC) or on-premises environments, ensuring compliance with stringent data protection standards. The integration of external frameworks and second-party or third-party agents allows businesses to customize solutions tailored to their specific needs.
An emerging future of enterprise innovation
Emergence AI’s orchestrator is designed to meet enterprises where they are, addressing challenges like legacy infrastructure, data privacy, and system adaptability. With a commitment to continuous innovation, the company aims to push the boundaries of AI-driven automation.
Nitta summarized the team’s expertise, stating, “We are a group of researchers and technologists from top AI labs like IBM, Google, DeepMind, Amazon, Microsoft, and Meta. We’ve built scalable AI systems used by hundreds of millions globally, not just writing papers but delivering code.”
For enterprises ready to explore tailored automation solutions, Emergence AI offers the tools to unlock new levels of efficiency and adaptability. Interested businesses can learn more by reaching out via the Orchestrator API or visiting the company’s website.
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